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0000000000000000000000000000000000000000..ede4da1ec97556f687076d6adc87769f2b299dcb --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/area_estimation.json @@ -0,0 +1,54 @@ +{ + "case_id": "sample_000135__area_estimation", + "sample_id": "sample_000135", + "family": "area_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Estimate the total deforested area in hectares inside this AOI for event year 2021. Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000135/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000135/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..fe4de529c34f536bdf9529735c9761deff43e6d6 --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000135__baseline_canopy_assessment", + "sample_id": "sample_000135", + "family": "baseline_canopy_assessment", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000135/questions/change_window_estimation.json b/data/source_assets/deforestation/000135/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..5275f1584ee9e9c6c15f0bf839cfccaa32b748ac --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/change_window_estimation.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000135__change_window_estimation", + "sample_id": "sample_000135", + "family": "change_window_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000135/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000135/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..325dbb02f039f353e5917b73e597dffb1a84083e --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/cross_modal_concordance.json @@ -0,0 +1,77 @@ +{ + "case_id": "sample_000135__cross_modal_concordance", + "sample_id": "sample_000135", + "family": "cross_modal_concordance", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000135/questions/false_positive_rejection.json b/data/source_assets/deforestation/000135/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..b2e1863ff4cc3b78b51478dd01aeae91431ff337 --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/false_positive_rejection.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000135__false_positive_rejection", + "sample_id": "sample_000135", + "family": "false_positive_rejection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000135/questions/forest_loss_detection.json b/data/source_assets/deforestation/000135/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..037b525d48e705a82f89b098a2121eff85df68d8 --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/forest_loss_detection.json @@ -0,0 +1,82 @@ +{ + "case_id": "sample_000135__forest_loss_detection", + "sample_id": "sample_000135", + "family": "forest_loss_detection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2021-04-02 and 2021-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000135/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000135/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..188619eb1d6f275a8a2cadc4d552ed022c1a4f9d --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000135__multi_year_loss_attribution", + "sample_id": "sample_000135", + "family": "multi_year_loss_attribution", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000135/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000135/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..0f40420445601814b2894645d5ee126c4e0e49f8 --- /dev/null +++ b/data/source_assets/deforestation/000135/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000135__severity_proxy_numeric", + "sample_id": "sample_000135", + "family": "severity_proxy_numeric", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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+ "usable": true + } +} \ No newline at end of file diff --git a/data/source_assets/deforestation/000136/questions/area_estimation.json b/data/source_assets/deforestation/000136/questions/area_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..f1d5c5fe2b9d52e3c86f7d45256e30d9eb3721e9 --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/area_estimation.json @@ -0,0 +1,54 @@ +{ + "case_id": "sample_000136__area_estimation", + "sample_id": "sample_000136", + "family": "area_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Estimate the total deforested area in hectares inside this AOI for event year 2021. Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000136/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000136/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..d2cb0e9c7d8137ddce77551ee1db725ac7d8f11a --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000136__baseline_canopy_assessment", + "sample_id": "sample_000136", + "family": "baseline_canopy_assessment", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000136/questions/change_window_estimation.json b/data/source_assets/deforestation/000136/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..89481465625918c18ce363f912fd6af801fc0095 --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/change_window_estimation.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000136__change_window_estimation", + "sample_id": "sample_000136", + "family": "change_window_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000136/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000136/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..04cc4bbe8e9fa08ae658aa047d68e222791694d7 --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/cross_modal_concordance.json @@ -0,0 +1,77 @@ +{ + "case_id": "sample_000136__cross_modal_concordance", + "sample_id": "sample_000136", + "family": "cross_modal_concordance", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000136/questions/false_positive_rejection.json b/data/source_assets/deforestation/000136/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..3c43a9cdec8829f5ebe9607df551fa2d4af47dcc --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/false_positive_rejection.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000136__false_positive_rejection", + "sample_id": "sample_000136", + "family": "false_positive_rejection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000136/questions/forest_loss_detection.json b/data/source_assets/deforestation/000136/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..d228c45cff762505d014bdfad505e46c80a163fd --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/forest_loss_detection.json @@ -0,0 +1,82 @@ +{ + "case_id": "sample_000136__forest_loss_detection", + "sample_id": "sample_000136", + "family": "forest_loss_detection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2021-04-02 and 2021-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000136/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000136/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..6d85ccc0e1d5ef6612e5e6ca9e9b96afa06ef97d --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000136__multi_year_loss_attribution", + "sample_id": "sample_000136", + "family": "multi_year_loss_attribution", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000136/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000136/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..1de636efb148dc17b8b401fd4b696c194576eb29 --- /dev/null +++ b/data/source_assets/deforestation/000136/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000136__severity_proxy_numeric", + "sample_id": "sample_000136", + "family": "severity_proxy_numeric", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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newline at end of file diff --git a/data/source_assets/deforestation/000138/questions/area_estimation.json b/data/source_assets/deforestation/000138/questions/area_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..871bf7a15e368b620fb42c92dde41e3019ba4f8c --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/area_estimation.json @@ -0,0 +1,54 @@ +{ + "case_id": "sample_000138__area_estimation", + "sample_id": "sample_000138", + "family": "area_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Estimate the total deforested area in hectares inside this AOI for event year 2021. Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000138/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000138/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..035fb0d98d1abf24727e8e6afb25d6a4f327525e --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000138__baseline_canopy_assessment", + "sample_id": "sample_000138", + "family": "baseline_canopy_assessment", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000138/questions/change_window_estimation.json b/data/source_assets/deforestation/000138/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..fd2da9119f82201508952fa1c62f2a0e223986a2 --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/change_window_estimation.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000138__change_window_estimation", + "sample_id": "sample_000138", + "family": "change_window_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000138/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000138/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..6badacb051d1973af1b1a951bd0eb80559db5719 --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/cross_modal_concordance.json @@ -0,0 +1,77 @@ +{ + "case_id": "sample_000138__cross_modal_concordance", + "sample_id": "sample_000138", + "family": "cross_modal_concordance", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000138/questions/false_positive_rejection.json b/data/source_assets/deforestation/000138/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..2361f4d777154a838378d77f932b2953a4b096df --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/false_positive_rejection.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000138__false_positive_rejection", + "sample_id": "sample_000138", + "family": "false_positive_rejection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000138/questions/forest_loss_detection.json b/data/source_assets/deforestation/000138/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..3aab8e2657378e5ece82c5542a4785805a9d8ae7 --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/forest_loss_detection.json @@ -0,0 +1,82 @@ +{ + "case_id": "sample_000138__forest_loss_detection", + "sample_id": "sample_000138", + "family": "forest_loss_detection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2021-04-02 and 2021-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000138/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000138/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..c2147a85da8c98009f2d0b9a0fa690dbeb15402c --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000138__multi_year_loss_attribution", + "sample_id": "sample_000138", + "family": "multi_year_loss_attribution", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000138/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000138/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..7b35c9e7db76301fde8b9ab7a2e10a548d822827 --- /dev/null +++ b/data/source_assets/deforestation/000138/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000138__severity_proxy_numeric", + "sample_id": "sample_000138", + "family": "severity_proxy_numeric", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Brazilian Amazon / Rondonia / Para / Mato Grosso", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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0000000000000000000000000000000000000000..436be0885da818727435a24f810101df43359c4f --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/area_estimation.json @@ -0,0 +1,52 @@ +{ + "case_id": "sample_000149__area_estimation", + "sample_id": "sample_000149", + "family": "area_estimation", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Estimate the total deforested area in hectares inside this AOI for event year 2022. Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2022.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000149/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000149/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..46800aff55b875ccdf623a9230d1247887ca48eb --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000149__baseline_canopy_assessment", + "sample_id": "sample_000149", + "family": "baseline_canopy_assessment", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000149/questions/change_window_estimation.json b/data/source_assets/deforestation/000149/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..ab322bbec57f9a3cfc8bd4325bcd8c79d3cf6c0c --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/change_window_estimation.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000149__change_window_estimation", + "sample_id": "sample_000149", + "family": "change_window_estimation", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2022.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2022-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2022-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2022-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2022-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2022-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000149/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000149/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..3d296eb701033cddecb1a4c2ae3722e10a81f464 --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/cross_modal_concordance.json @@ -0,0 +1,75 @@ +{ + "case_id": "sample_000149__cross_modal_concordance", + "sample_id": "sample_000149", + "family": "cross_modal_concordance", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2022-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2022-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2022-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2022-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2022-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000149/questions/false_positive_rejection.json b/data/source_assets/deforestation/000149/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..2a0db33849cbe618c048c48bff5d64195edd645c --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/false_positive_rejection.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000149__false_positive_rejection", + "sample_id": "sample_000149", + "family": "false_positive_rejection", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2022.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2022-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2022-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2022-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2022-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2022-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000149/questions/forest_loss_detection.json b/data/source_assets/deforestation/000149/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..052c35762d9d3adeaf5fb2b0876d891559dd6063 --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/forest_loss_detection.json @@ -0,0 +1,80 @@ +{ + "case_id": "sample_000149__forest_loss_detection", + "sample_id": "sample_000149", + "family": "forest_loss_detection", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2022-04-02 and 2022-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2022.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2022-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2022-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2022-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2022-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2022-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000149/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000149/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..ede7bb7e4c33f71e2055c3a5c4ab803c14bfa1b1 --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000149__multi_year_loss_attribution", + "sample_id": "sample_000149", + "family": "multi_year_loss_attribution", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000149/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000149/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..b9ffdcbb75477deec22198322965e4d5c980267f --- /dev/null +++ b/data/source_assets/deforestation/000149/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000149__severity_proxy_numeric", + "sample_id": "sample_000149", + "family": "severity_proxy_numeric", + "event_year": 2022, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2022-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2022-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2022-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2022-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2022-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000208/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000208/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..737378053e2e26860938db80bca92d2ab63762dd --- /dev/null +++ b/data/source_assets/deforestation/000208/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000208__baseline_canopy_assessment", + "sample_id": "sample_000208", + "family": "baseline_canopy_assessment", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000208/questions/change_window_estimation.json b/data/source_assets/deforestation/000208/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..4e1b998623a369561447f63b3a91f8df748962f7 --- /dev/null +++ b/data/source_assets/deforestation/000208/questions/change_window_estimation.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000208__change_window_estimation", + "sample_id": "sample_000208", + "family": "change_window_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000208/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000208/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..407c26e7bd7928428fbed0d2d33c3d0065ba2a5e --- /dev/null +++ b/data/source_assets/deforestation/000208/questions/cross_modal_concordance.json @@ -0,0 +1,75 @@ +{ + "case_id": "sample_000208__cross_modal_concordance", + "sample_id": "sample_000208", + "family": "cross_modal_concordance", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000208/questions/false_positive_rejection.json b/data/source_assets/deforestation/000208/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..853f55b589d3f7619400938fe832daf1878a1bf4 --- /dev/null +++ b/data/source_assets/deforestation/000208/questions/false_positive_rejection.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000208__false_positive_rejection", + "sample_id": "sample_000208", + "family": "false_positive_rejection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000208/questions/forest_loss_detection.json b/data/source_assets/deforestation/000208/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..7c4b5bc812698041b589ae8ae36aa7b5d090e2c4 --- /dev/null +++ b/data/source_assets/deforestation/000208/questions/forest_loss_detection.json @@ -0,0 +1,80 @@ +{ + "case_id": "sample_000208__forest_loss_detection", + "sample_id": "sample_000208", + "family": "forest_loss_detection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2021-04-02 and 2021-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000208/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000208/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..661f145a0d15f937099c511ee00f5da0da604840 --- /dev/null +++ b/data/source_assets/deforestation/000208/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000208__multi_year_loss_attribution", + "sample_id": "sample_000208", + "family": "multi_year_loss_attribution", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000208/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000208/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..64700d609b16fd2fecc9bf6d02d960621e47abe2 --- /dev/null +++ b/data/source_assets/deforestation/000208/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000208__severity_proxy_numeric", + "sample_id": "sample_000208", + "family": "severity_proxy_numeric", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000209/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000209/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..c2bee5bf82370d3adbe7e856b4d8953051b8abbb --- /dev/null +++ b/data/source_assets/deforestation/000209/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000209__baseline_canopy_assessment", + "sample_id": "sample_000209", + "family": "baseline_canopy_assessment", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000209/questions/change_window_estimation.json b/data/source_assets/deforestation/000209/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..56bc8dd986fdea62764d93f4d3762fc8c06805b1 --- /dev/null +++ b/data/source_assets/deforestation/000209/questions/change_window_estimation.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000209__change_window_estimation", + "sample_id": "sample_000209", + "family": "change_window_estimation", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000209/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000209/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..98b12d3fd3f708599c9d1b8a21833509bb5a6a43 --- /dev/null +++ b/data/source_assets/deforestation/000209/questions/cross_modal_concordance.json @@ -0,0 +1,75 @@ +{ + "case_id": "sample_000209__cross_modal_concordance", + "sample_id": "sample_000209", + "family": "cross_modal_concordance", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000209/questions/false_positive_rejection.json b/data/source_assets/deforestation/000209/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..277a5e07b9dec432ef81d254bf4b271dfb10547d --- /dev/null +++ b/data/source_assets/deforestation/000209/questions/false_positive_rejection.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000209__false_positive_rejection", + "sample_id": "sample_000209", + "family": "false_positive_rejection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000209/questions/forest_loss_detection.json b/data/source_assets/deforestation/000209/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..c26b4f8a5c70077f76cf699aefddf334fa15ef0f --- /dev/null +++ b/data/source_assets/deforestation/000209/questions/forest_loss_detection.json @@ -0,0 +1,80 @@ +{ + "case_id": "sample_000209__forest_loss_detection", + "sample_id": "sample_000209", + "family": "forest_loss_detection", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2021-04-02 and 2021-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2021.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000209/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000209/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..354f590aed856d2f7d3a45ac514fade670c21d43 --- /dev/null +++ b/data/source_assets/deforestation/000209/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000209__multi_year_loss_attribution", + "sample_id": "sample_000209", + "family": "multi_year_loss_attribution", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000209/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000209/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..3ae307c06ffb4a0e6570a3432f9c6f5ee740598d --- /dev/null +++ b/data/source_assets/deforestation/000209/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000209__severity_proxy_numeric", + "sample_id": "sample_000209", + "family": "severity_proxy_numeric", + "event_year": 2021, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2021-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2021-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2021-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2021-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2021-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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"sample_000273", + "family": "area_estimation", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Estimate the total deforested area in hectares inside this AOI for event year 2019. Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2019.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000273/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000273/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..8af00a0188704944e6d6401fba5424f47b349a4a --- /dev/null +++ b/data/source_assets/deforestation/000273/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000273__baseline_canopy_assessment", + "sample_id": "sample_000273", + "family": "baseline_canopy_assessment", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000273/questions/change_window_estimation.json b/data/source_assets/deforestation/000273/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..ff7df819ad2d6d8a37fa71163609953e10770717 --- /dev/null +++ b/data/source_assets/deforestation/000273/questions/change_window_estimation.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000273__change_window_estimation", + "sample_id": "sample_000273", + "family": "change_window_estimation", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2019.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2019-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2019-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2019-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2019-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2019-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000273/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000273/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..e8fd299a35ed13d4d31e218571c9efdc258cb81c --- /dev/null +++ b/data/source_assets/deforestation/000273/questions/cross_modal_concordance.json @@ -0,0 +1,77 @@ +{ + "case_id": "sample_000273__cross_modal_concordance", + "sample_id": "sample_000273", + "family": "cross_modal_concordance", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2019-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2019-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2019-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2019-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2019-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000273/questions/false_positive_rejection.json b/data/source_assets/deforestation/000273/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..08accdba0ebf010e2832fbc133810ad84335b6d6 --- /dev/null +++ b/data/source_assets/deforestation/000273/questions/false_positive_rejection.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000273__false_positive_rejection", + "sample_id": "sample_000273", + "family": "false_positive_rejection", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2019.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2019-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2019-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2019-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2019-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2019-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000273/questions/forest_loss_detection.json b/data/source_assets/deforestation/000273/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..53a5db82bad273c0dbbad97aa7727e0f88ba698b --- /dev/null +++ b/data/source_assets/deforestation/000273/questions/forest_loss_detection.json @@ -0,0 +1,82 @@ +{ + "case_id": "sample_000273__forest_loss_detection", + "sample_id": "sample_000273", + "family": "forest_loss_detection", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2019-04-02 and 2019-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2019.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2019-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2019-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2019-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2019-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2019-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000273/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000273/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..378ab0c25424731c0bc2f1715c27c16c20729ec2 --- /dev/null +++ b/data/source_assets/deforestation/000273/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000273__multi_year_loss_attribution", + "sample_id": "sample_000273", + "family": "multi_year_loss_attribution", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000273/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000273/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..a1bd125e901cf99e4546349bbe6f2544a72cd07d --- /dev/null +++ b/data/source_assets/deforestation/000273/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000273__severity_proxy_numeric", + "sample_id": "sample_000273", + "family": "severity_proxy_numeric", + "event_year": 2019, + "region_group": "Amazon", + "region_name": "Peru / Bolivia / Colombia Amazon", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2019-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2019-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2019-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2019-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2019-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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0000000000000000000000000000000000000000..3e1d5903d67b324dcf296c444ddda0c123816f2d --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/area_estimation.json @@ -0,0 +1,52 @@ +{ + "case_id": "sample_000280__area_estimation", + "sample_id": "sample_000280", + "family": "area_estimation", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Estimate the total deforested area in hectares inside this AOI for event year 2020. Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000280/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000280/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..040370345b18ca52ffae043bd0d5b175562b97f1 --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000280__baseline_canopy_assessment", + "sample_id": "sample_000280", + "family": "baseline_canopy_assessment", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000280/questions/change_window_estimation.json b/data/source_assets/deforestation/000280/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..e7a8ca5043a852c476921a9639f33155c0f7d9b7 --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/change_window_estimation.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000280__change_window_estimation", + "sample_id": "sample_000280", + "family": "change_window_estimation", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000280/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000280/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..ffc4cd8fdcffdf4ac9043d139fd4fd19b74c0cb7 --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/cross_modal_concordance.json @@ -0,0 +1,75 @@ +{ + "case_id": "sample_000280__cross_modal_concordance", + "sample_id": "sample_000280", + "family": "cross_modal_concordance", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000280/questions/false_positive_rejection.json b/data/source_assets/deforestation/000280/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..c030c3981cafe91bbb75b5ec378953b24101eebb --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/false_positive_rejection.json @@ -0,0 +1,84 @@ +{ + "case_id": "sample_000280__false_positive_rejection", + "sample_id": "sample_000280", + "family": "false_positive_rejection", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000280/questions/forest_loss_detection.json b/data/source_assets/deforestation/000280/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..476ef3d71d3fbfbb050c457530f17536cf9ff3f0 --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/forest_loss_detection.json @@ -0,0 +1,80 @@ +{ + "case_id": "sample_000280__forest_loss_detection", + "sample_id": "sample_000280", + "family": "forest_loss_detection", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2020-04-02 and 2020-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000280/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000280/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..fb4ed3237f27a7b5c0e294d0be7401a3fc5ff853 --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000280__multi_year_loss_attribution", + "sample_id": "sample_000280", + "family": "multi_year_loss_attribution", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000280/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000280/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..f04cb83174302091ba0e56417133ebe29c4747cf --- /dev/null +++ b/data/source_assets/deforestation/000280/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000280__severity_proxy_numeric", + "sample_id": "sample_000280", + "family": "severity_proxy_numeric", + "event_year": 2020, + "region_group": "Amazon", + "region_name": "Bolivia Amazon / Santa Cruz / Beni / Pando", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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"sample_000300__area_estimation", + "sample_id": "sample_000300", + "family": "area_estimation", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Estimate the total deforested area in hectares inside this AOI for event year 2020. Use the Hansen GFC 2025 v1.13 loss-year mask, then validate the signal with NDVI/NBR drops in the same region.", + "expected_answer_shape": { + "loss_area_ha": "float", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "nbr_drop": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ExtractObjects", + "MeasureArea", + "CompareSources", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000300/questions/baseline_canopy_assessment.json b/data/source_assets/deforestation/000300/questions/baseline_canopy_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..252e835a0ca3e4b129fa847403f8dc716dc15a21 --- /dev/null +++ b/data/source_assets/deforestation/000300/questions/baseline_canopy_assessment.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000300__baseline_canopy_assessment", + "sample_id": "sample_000300", + "family": "baseline_canopy_assessment", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Compute the arithmetic mean Hansen treecover2000 percentage over all valid pixels in the packaged AOI raster (exclude non-finite values and declared nodata 255; treat zero as valid). Return dense_forest when the mean is >60%, open_canopy when 30% <= the mean <= 60%, or sparse when the mean is <30%. Report both the unrounded mean and the class.", + "expected_answer_shape": { + "treecover2000_mean_pct": "float", + "baseline_class": "dense_forest | open_canopy | sparse" + }, + "available_data": { + "cache": { + "masks": [ + "masks/treecover2000.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000300/questions/change_window_estimation.json b/data/source_assets/deforestation/000300/questions/change_window_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..33d5393f63244e7e08c007153c5323168814bec1 --- /dev/null +++ b/data/source_assets/deforestation/000300/questions/change_window_estimation.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000300__change_window_estimation", + "sample_id": "sample_000300", + "family": "change_window_estimation", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Using AOI-wide means for the available Sentinel-2 epochs in canonical order (pre_3, pre_2, pre_1, post_1, post_2, post_3), identify the dominant adjacent clearing interval by maximizing NDVI_drop + 0.5*NBR_drop; skip any undeclared epoch. Return label deforestation and that interval only when Hansen event-year loss is at least 0.5 ha; otherwise return label no_deforestation and a null interval. Report Hansen loss area; the whole-period NDVI drop within positive event-year loss pixels, falling back to AOI-wide valid pixels when none exist; Sentinel-1 VH delta dB; and the selected-window NDVI drop, NBR drop, and composite score (the selected-window fields are null when the interval is null).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "change_window": "{start_epoch,end_epoch} | null", + "evidence": { + "hansen_loss_area_ha": "float", + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "selected_window_ndvi_drop": "float | null", + "selected_window_nbr_drop": "float | null", + "composite_drop_score": "float | null" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "DetectChange", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000300/questions/cross_modal_concordance.json b/data/source_assets/deforestation/000300/questions/cross_modal_concordance.json new file mode 100644 index 0000000000000000000000000000000000000000..d765307241ae1e4b590d1735deff62c601d5fc2a --- /dev/null +++ b/data/source_assets/deforestation/000300/questions/cross_modal_concordance.json @@ -0,0 +1,77 @@ +{ + "case_id": "sample_000300__cross_modal_concordance", + "sample_id": "sample_000300", + "family": "cross_modal_concordance", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Compare whole-AOI optical and SAR signals using the available declared pre/post epochs. Define optical change as mean-pre minus mean-post NDVI drop > 0.10 and SAR change as mean-post minus mean-pre VH delta < -1.0 dB (equality at either threshold is no change for that modality). Return 'concordant' when both indicate change, 'discordant' when only one does, or 'no_change' when neither does. Report NDVI drop, contextual NBR drop, and VH delta dB.", + "expected_answer_shape": { + "concordance": "concordant | discordant | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "vh_delta_db": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 6, + "tool_budget_max": 6, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000300/questions/false_positive_rejection.json b/data/source_assets/deforestation/000300/questions/false_positive_rejection.json new file mode 100644 index 0000000000000000000000000000000000000000..0ec8241568e4b57617ade193dfc6d907dbd4b424 --- /dev/null +++ b/data/source_assets/deforestation/000300/questions/false_positive_rejection.json @@ -0,0 +1,86 @@ +{ + "case_id": "sample_000300__false_positive_rejection", + "sample_id": "sample_000300", + "family": "false_positive_rejection", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Apply the declared ordered remote-sensing proxy rules to classify the change pattern in this AOI. Return exactly one operational cause class from: deforestation, plantation_harvest, water_flood_edge, burn_bare_soil, agriculture, no_change. These are benchmark proxy classes, not independently field-verified causal labels. Report the optical NDVI/NBR drops, Sentinel-1 VH delta dB and post-event VV mean dB, Hansen loss area, baseline tree-cover mean percentage, and ordered rules fired.", + "expected_answer_shape": { + "cause": "deforestation | plantation_harvest | water_flood_edge | burn_bare_soil | agriculture | no_change", + "evidence": { + "ndvi_drop": "float", + "nbr_drop": "float", + "sar_vh_delta_db": "float", + "sar_vv_post_mean_db": "float", + "hansen_loss_area_ha": "float", + "treecover2000_mean_pct": "float", + "rules_fired": "list[str]" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000300/questions/forest_loss_detection.json b/data/source_assets/deforestation/000300/questions/forest_loss_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..8ea162d7fb897604725156ea13c1529437c136c6 --- /dev/null +++ b/data/source_assets/deforestation/000300/questions/forest_loss_detection.json @@ -0,0 +1,82 @@ +{ + "case_id": "sample_000300__forest_loss_detection", + "sample_id": "sample_000300", + "family": "forest_loss_detection", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Looking at the multi-temporal Sentinel-2 RGB panel for this AOI, decide whether real forest loss occurred between 2020-04-02 and 2020-09-29. Answer 'deforestation' or 'no_deforestation' and report the supporting NDVI drop, SAR VH change (dB), and Hansen loss area (ha).", + "expected_answer_shape": { + "label": "deforestation | no_deforestation", + "evidence": { + "ndvi_drop": "float", + "sar_vh_delta_db": "float", + "hansen_loss_area_ha": "float" + } + }, + "available_data": { + "visible_modality": "s2_rgb", + "panel_paths": [ + "visible/s2_rgb/pre_3.png", + "visible/s2_rgb/pre_2.png", + "visible/s2_rgb/pre_1.png", + "visible/s2_rgb/post_1.png", + "visible/s2_rgb/post_2.png", + "visible/s2_rgb/post_3.png" + ], + "cache": { + "s2_6band": [ + "cache/s2/pre_3.tif", + "cache/s2/pre_2.tif", + "cache/s2/pre_1.tif", + "cache/s2/post_1.tif", + "cache/s2/post_2.tif", + "cache/s2/post_3.tif" + ], + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "masks": [ + "masks/loss_year_2020.tif", + "masks/lossyear.tif", + "masks/treecover2000.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "CompareSources", + "ClassifyChange", + "TaskComplete" + ], + "tool_budget_min": 7, + "tool_budget_max": 7, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000300/questions/multi_year_loss_attribution.json b/data/source_assets/deforestation/000300/questions/multi_year_loss_attribution.json new file mode 100644 index 0000000000000000000000000000000000000000..c821f22533eb60df275b57ee5c43357430c3eaa6 --- /dev/null +++ b/data/source_assets/deforestation/000300/questions/multi_year_loss_attribution.json @@ -0,0 +1,30 @@ +{ + "case_id": "sample_000300__multi_year_loss_attribution", + "sample_id": "sample_000300", + "family": "multi_year_loss_attribution", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Using only Hansen lossyear codes 1 through 23 (calendar years 2001 through 2023) inside this AOI, compute each year's grid-aware loss area in hectares and return the year with the largest area plus that six-decimal area. Break an equal six-decimal area tie in favor of the earliest year. If no valid pixel has a code from 1 through 23, return year 'no_loss' and loss_ha 0.0. Code 0 is valid no-loss and nodata 255 is excluded.", + "expected_answer_shape": { + "year": "integer 2001..2023 | 'no_loss'", + "loss_ha": "non-negative float" + }, + "available_data": { + "cache": { + "masks": [ + "masks/lossyear.tif" + ] + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "DetectChange", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": "deforestation_contract_completion_v1_20261014" +} diff --git a/data/source_assets/deforestation/000300/questions/severity_proxy_numeric.json b/data/source_assets/deforestation/000300/questions/severity_proxy_numeric.json new file mode 100644 index 0000000000000000000000000000000000000000..f0e868e83319d38e905bd2294d7ff09a119dd6c2 --- /dev/null +++ b/data/source_assets/deforestation/000300/questions/severity_proxy_numeric.json @@ -0,0 +1,56 @@ +{ + "case_id": "sample_000300__severity_proxy_numeric", + "sample_id": "sample_000300", + "family": "severity_proxy_numeric", + "event_year": 2020, + "region_group": "Africa", + "region_name": "Congo Basin / DRC / Republic of Congo / Cameroon", + "question_text": "Using all available Sentinel-1 acquisitions and their declared pre/post temporal roles, compute the whole-AOI mean VH backscatter change as post_mean_db minus pre_mean_db. Return that finite delta in decibels and bucket severity as severe for delta < -3, moderate for -3 <= delta < -1, mild for -1 <= delta < 0, or none for delta >= 0. Thus -3 is moderate, -1 is mild, and 0 is none.", + "expected_answer_shape": { + "vh_delta_db": "finite float", + "severity": "severe | moderate | mild | none" + }, + "available_data": { + "cache": { + "s1_grd": [ + "cache/s1_grd/s1_00.tif", + "cache/s1_grd/s1_03.tif", + "cache/s1_grd/s1_06.tif", + "cache/s1_grd/s1_09.tif", + "cache/s1_grd/s1_11.tif" + ], + "s1_window_metadata": { + "s1_00": { + "acquisition_date": "2020-04-20", + "temporal_role": "pre" + }, + "s1_03": { + "acquisition_date": "2020-05-26", + "temporal_role": "pre" + }, + "s1_06": { + "acquisition_date": "2020-07-13", + "temporal_role": "post" + }, + "s1_09": { + "acquisition_date": "2020-08-18", + "temporal_role": "post" + }, + "s1_11": { + "acquisition_date": "2020-09-11", + "temporal_role": "post" + } + } + } + }, + "available_tools": [ + "ReadData", + "PrepareScene", + "ComputeStats", + "ScoreHazard", + "TaskComplete" + ], + "tool_budget_min": 5, + "tool_budget_max": 5, + "contract_completion_version": 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