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  "@type": "sc:Dataset",
  "name": "PolyTopoBench",
  "description": "PolyTopoBench is a benchmark for complex vector polygon generation from remote-sensing imagery, evaluating whether models recover complete polygon topology including interior rings. It has four single-class tasks on 512x512 aerial image patches: Inria building (OpenStreetMap footprints aligned to the Inria Aerial Image Labeling tiles and manually corrected) and Deventer-512 road, vegetation and unvegetated land cover. Annotations are provided as COCO-layout JSON, whose segmentation lists the exterior ring followed by hole rings, and as GeoParquet.",
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  "url": "https://huggingface.co/datasets/PingL/PolyTopoBench",
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    "https://arxiv.org/abs/2609.32856"
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  "license": [
    "https://spdx.org/licenses/ODbL-1.0.html",
    "https://spdx.org/licenses/CC-BY-4.0.html"
  ],
  "creator": [
    {
      "@type": "sc:Person",
      "name": "Zeping Liu"
    },
    {
      "@type": "sc:Person",
      "name": "Ni Lao"
    },
    {
      "@type": "sc:Person",
      "name": "Weiwei Sun"
    },
    {
      "@type": "sc:Person",
      "name": "Gil Wolff"
    },
    {
      "@type": "sc:Person",
      "name": "Yiqun Xie"
    },
    {
      "@type": "sc:Person",
      "name": "Liang Zhao"
    },
    {
      "@type": "sc:Person",
      "name": "Junfeng Jiao"
    },
    {
      "@type": "sc:Person",
      "name": "Gengchen Mai"
    }
  ],
  "citeAs": "@misc{liu2026polytopobenchbenchmarkcomplexvector, title={PolyTopoBench: A Benchmark for Complex Vector Polygon Generation from Remote Sensing Imagery}, author={Zeping Liu and Ni Lao and Weiwei Sun and Gil Wolff and Yiqun Xie and Liang Zhao and Junfeng Jiao and Gengchen Mai}, year={2026}, eprint={2609.32856}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2609.32856}}",
  "version": "1.0.0",
  "datePublished": "2026-09-26",
  "keywords": [
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    "GeoJSON",
    "GeoParquet",
    "Inria Aerial Image Labeling",
    "OpenStreetMap",
    "aerial imagery",
    "building footprints",
    "interior rings",
    "land cover",
    "polygon generation",
    "polygon topology",
    "polygonal vectorization",
    "remote sensing"
  ],
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      "@id": "deventer-splits-csv",
      "name": "deventer-splits-csv",
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      "contentUrl": "https://huggingface.co/datasets/PingL/PolyTopoBench/resolve/main/deventer/splits.csv",
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      "description": "Deventer 512x512 RGB patches, shared by all Deventer tasks.",
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      "name": "raw-inria-tiles",
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      "includes": "raw/inria/train/images/*.tif",
      "encodingFormat": "image/tiff"
    },
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      "@id": "raw-inria-masks",
      "name": "raw-inria-masks",
      "description": "Official Inria binary building masks (not the PolyTopoBench ground truth).",
      "containedIn": {
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      "includes": "raw/inria/train/gt/*.tif",
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          "description": "RGB image patch.",
          "dataType": "sc:ImageObject",
          "source": {
            "fileSet": {
              "@id": "inria-images"
            },
            "extract": {
              "fileProperty": "content"
            }
          }
        }
      ]
    },
    {
      "@type": "cr:RecordSet",
      "@id": "deventer-image-files",
      "name": "deventer-image-files",
      "description": "One record per deventer image patch file.",
      "field": [
        {
          "@type": "cr:Field",
          "@id": "deventer-image-files/path",
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          "description": "Path of the image in the repository.",
          "dataType": "sc:Text",
          "source": {
            "fileSet": {
              "@id": "deventer-images"
            },
            "extract": {
              "fileProperty": "fullpath"
            }
          }
        },
        {
          "@type": "cr:Field",
          "@id": "deventer-image-files/image",
          "name": "image",
          "description": "RGB image patch.",
          "dataType": "sc:ImageObject",
          "source": {
            "fileSet": {
              "@id": "deventer-images"
            },
            "extract": {
              "fileProperty": "content"
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          }
        }
      ]
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    {
      "@type": "cr:RecordSet",
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      },
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        {
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          "source": {
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              "@id": "inria-building-train-parquet"
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            "extract": {
              "column": "image_id"
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          }
        },
        {
          "@type": "cr:Field",
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          "name": "file_name",
          "description": "Image path relative to <dataset>/images/<split>/.",
          "dataType": "sc:Text",
          "source": {
            "fileObject": {
              "@id": "inria-building-train-parquet"
            },
            "extract": {
              "column": "file_name"
            }
          }
        },
        {
          "@type": "cr:Field",
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            "fileObject": {
              "@id": "inria-building-train-parquet"
            },
            "extract": {
              "column": "category"
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        },
        {
          "@type": "cr:Field",
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          "dataType": "sc:Float",
          "source": {
            "fileObject": {
              "@id": "inria-building-train-parquet"
            },
            "extract": {
              "column": "area"
            }
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        },
        {
          "@type": "cr:Field",
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          "description": "Number of interior rings.",
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            "fileObject": {
              "@id": "inria-building-train-parquet"
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              "column": "hole_count"
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          }
        },
        {
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          "@id": "inria-building-train/geometry",
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          "description": "WKB-encoded Polygon in 512x512 pixel coordinates (origin top-left, y down, no CRS); ring 0 is the exterior and further rings are holes.",
          "dataType": "sc:Text",
          "source": {
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              "@id": "inria-building-train-parquet"
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              "column": "geometry"
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      ]
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      "@type": "cr:RecordSet",
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      "key": {
        "@id": "inria-building-val/annotation_id"
      },
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        {
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          "source": {
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            "extract": {
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          }
        },
        {
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        },
        {
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            },
            "extract": {
              "column": "area"
            }
          }
        },
        {
          "@type": "cr:Field",
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          "description": "Number of interior rings.",
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            "fileObject": {
              "@id": "inria-building-val-parquet"
            },
            "extract": {
              "column": "hole_count"
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          }
        },
        {
          "@type": "cr:Field",
          "@id": "inria-building-val/geometry",
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          "dataType": "sc:Text",
          "source": {
            "fileObject": {
              "@id": "inria-building-val-parquet"
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            "extract": {
              "column": "geometry"
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          }
        }
      ]
    },
    {
      "@type": "cr:RecordSet",
      "@id": "deventer-road-train",
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      "key": {
        "@id": "deventer-road-train/annotation_id"
      },
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          "source": {
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        {
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            },
            "extract": {
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        },
        {
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        {
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        },
        {
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            "fileObject": {
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          }
        },
        {
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          "dataType": "sc:Text",
          "source": {
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      ]
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      "@type": "cr:RecordSet",
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      "key": {
        "@id": "deventer-road-val/annotation_id"
      },
      "field": [
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        {
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          "dataType": "sc:Integer",
          "source": {
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            "extract": {
              "column": "image_id"
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          }
        },
        {
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          "dataType": "sc:Text",
          "source": {
            "fileObject": {
              "@id": "deventer-road-val-parquet"
            },
            "extract": {
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          }
        },
        {
          "@type": "cr:Field",
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          }
        },
        {
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          "source": {
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            },
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              "column": "area"
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          }
        },
        {
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          "dataType": "sc:Integer",
          "source": {
            "fileObject": {
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          }
        },
        {
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          "dataType": "sc:Text",
          "source": {
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        }
      ]
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    {
      "@type": "cr:RecordSet",
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      "key": {
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      "field": [
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        {
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        {
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        {
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        {
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          "@id": "deventer-unvegetated-train/area",
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          "description": "Polygon area in square pixels (exterior minus holes).",
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        },
        {
          "@type": "cr:Field",
          "@id": "deventer-unvegetated-train/hole_count",
          "name": "hole_count",
          "description": "Number of interior rings.",
          "dataType": "sc:Integer",
          "source": {
            "fileObject": {
              "@id": "deventer-unvegetated-train-parquet"
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            "extract": {
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          }
        },
        {
          "@type": "cr:Field",
          "@id": "deventer-unvegetated-train/geometry",
          "name": "geometry",
          "description": "WKB-encoded Polygon in 512x512 pixel coordinates (origin top-left, y down, no CRS); ring 0 is the exterior and further rings are holes.",
          "dataType": "sc:Text",
          "source": {
            "fileObject": {
              "@id": "deventer-unvegetated-train-parquet"
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            "extract": {
              "column": "geometry"
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    },
    {
      "@type": "cr:RecordSet",
      "@id": "deventer-unvegetated-val",
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      "description": "deventer/unvegetated val: one record per polygon (3300 polygons, 2074 interior rings, 432 images).",
      "key": {
        "@id": "deventer-unvegetated-val/annotation_id"
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      "field": [
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          "@type": "cr:Field",
          "@id": "deventer-unvegetated-val/annotation_id",
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          "description": "Annotation id, unique within the task split; matches the COCO JSON.",
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          "@type": "cr:Field",
          "@id": "deventer-unvegetated-val/file_name",
          "name": "file_name",
          "description": "Image path relative to <dataset>/images/<split>/.",
          "dataType": "sc:Text",
          "source": {
            "fileObject": {
              "@id": "deventer-unvegetated-val-parquet"
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          "name": "category",
          "description": "Task category name.",
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            "fileObject": {
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            "extract": {
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          "@type": "cr:Field",
          "@id": "deventer-unvegetated-val/area",
          "name": "area",
          "description": "Polygon area in square pixels (exterior minus holes).",
          "dataType": "sc:Float",
          "source": {
            "fileObject": {
              "@id": "deventer-unvegetated-val-parquet"
            },
            "extract": {
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          }
        },
        {
          "@type": "cr:Field",
          "@id": "deventer-unvegetated-val/hole_count",
          "name": "hole_count",
          "description": "Number of interior rings.",
          "dataType": "sc:Integer",
          "source": {
            "fileObject": {
              "@id": "deventer-unvegetated-val-parquet"
            },
            "extract": {
              "column": "hole_count"
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          }
        },
        {
          "@type": "cr:Field",
          "@id": "deventer-unvegetated-val/geometry",
          "name": "geometry",
          "description": "WKB-encoded Polygon in 512x512 pixel coordinates (origin top-left, y down, no CRS); ring 0 is the exterior and further rings are holes.",
          "dataType": "sc:Text",
          "source": {
            "fileObject": {
              "@id": "deventer-unvegetated-val-parquet"
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            "extract": {
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  ],
  "rai:dataLimitations": "Inria building: This dataset is intended for evaluating building-footprint polygon generation from high-resolution aerial imagery. It is limited to the geographic and visual distribution of the Inria Aerial Image Labeling data and may not generalize to other regions, sensors, seasons, resolutions, or building styles. The vector annotations are derived from aligned OpenStreetMap footprints and raster masks, so they may inherit incompleteness, temporal mismatch, alignment errors, or residual topology errors. The dataset is not intended for legal, cadastral, surveying-grade, operational mapping, emergency response, surveillance, or other high-stakes uses without independent validation. Deventer land cover: This dataset is intended for evaluating polygonal vectorization of selected Deventer land-cover classes from 512 x 512 aerial image patches. Its applicability is limited to the source city, sensor conditions, spatial resolution, and land-cover categories represented in Deventer-512. The benchmark uses road, vegetation, and unvegetated classes and should not be assumed to generalize to other regions, seasons, sensors, resolutions, or land-cover taxonomies without validation. It is not intended for legal, cadastral, operational mapping, emergency response, surveillance, or other high-stakes uses without independent quality control.",
  "rai:dataBiases": "Inria building: The dataset reflects selection bias from the Inria city coverage and OpenStreetMap availability. Urban areas, building styles, mapping completeness, and imagery conditions represented in the source cities are likely overrepresented, while rural areas, informal settlements, regions with sparse OpenStreetMap coverage, different sensors, seasons, and lower-resolution imagery may be underrepresented. Annotation bias may arise from OpenStreetMap incompleteness, temporal mismatch with imagery, raster-mask errors, and manual correction decisions. Models trained or evaluated on this dataset may perform better on well-mapped urban buildings similar to the source cities and worse on underrepresented geographies, building types, or annotation conditions. Deventer land cover: The dataset has selection bias toward the Deventer geographic area, its aerial imagery conditions, urban layout, and land-cover patterns. Other regions, rural settings, different climates, sensors, seasons, resolutions, and land-cover distributions may be underrepresented. Annotation bias may arise from the upstream vector annotations, class definitions, split construction, and any residual geometry errors. Models evaluated on this dataset may perform better on Deventer-like scenes and worse on underrepresented geographies or land-cover patterns.",
  "rai:personalSensitiveInformation": "Inria building: The dataset contains geographic information in the form of aerial imagery and building footprint annotations. It does not intentionally include personal attributes such as gender, age, language, health or medical data, political or religious beliefs, experience or seniority, or individual-level socio-economic status. No personally identifying information is annotated. However, because aerial imagery and building footprints describe physical locations and built environments, downstream use should consider location privacy and potential sensitivity of geospatial information. Deventer land cover: The dataset contains geographic information in the form of aerial imagery and land-cover polygon annotations. It does not intentionally include personal attributes such as gender, age, language, health or medical data, political or religious beliefs, experience or seniority, or individual-level socio-economic status. No personally identifying information is annotated. However, because the data describes physical locations and land-cover structure, downstream use should consider the sensitivity of geospatial information.",
  "rai:dataUseCases": "Inria building: The dataset represents building footprints and their polygon topology in high-resolution aerial imagery, including exterior boundaries and interior rings. It is intended for evaluating remote-sensing building polygon generation and topology-aware vectorization methods. Validation is limited to the benchmark setting described in the accompanying paper: building-footprint extraction from Inria-style aerial imagery using the provided polygon annotations and evaluation metrics. Validation does not necessarily hold for legal mapping, cadastral boundaries, operational GIS updates, other object classes, other sensors, other resolutions, or geographic regions outside the source distribution. Deventer land cover: The dataset represents land-cover polygons in aerial imagery, with emphasis on road, vegetation, and unvegetated regions and their polygon topology. It is intended for evaluating remote-sensing polygonal vectorization and topology-aware polygon generation methods. Validation is limited to the PolyTopoBench benchmark setting and the selected Deventer-512 classes. Validation does not necessarily hold for other regions, sensors, resolutions, land-cover taxonomies, operational GIS updates, cadastral mapping, or high-stakes decision making.",
  "rai:dataSocialImpact": "Inria building: This dataset may support positive applications such as better evaluation of building-footprint extraction, map updating, urban analysis, and disaster-response research. Potential risks include misuse for surveillance, privacy-invasive geospatial analysis, or unsupported high-stakes mapping decisions. Because coverage is geographically limited, models may perform unevenly across regions and communities with different building styles or mapping completeness. Users should validate models on target regions and avoid operational or high-stakes use without independent quality control. Deventer land cover: This dataset may support positive applications such as evaluating land-cover vectorization, map updating, urban analysis, and environmental monitoring. Potential risks include misuse for surveillance, privacy-invasive geospatial analysis, or unsupported operational mapping decisions. Because the data is geographically limited to Deventer, models may perform unevenly across other regions or communities with different land-cover patterns. Users should validate models on target regions and avoid high-stakes use without independent quality control.",
  "rai:hasSyntheticData": false,
  "prov:wasDerivedFrom": [
    {
      "@id": "https://project.inria.fr/aerialimagelabeling/",
      "prov:label": "Inria Aerial Image Labeling Dataset",
      "sc:license": "Public domain imagery and building footprints (per the dataset page)"
    },
    {
      "@id": "https://www.openstreetmap.org",
      "prov:label": "OpenStreetMap",
      "sc:license": "ODbL-1.0"
    },
    {
      "@id": "https://huggingface.co/datasets/HeinzJiao/Deventer-512",
      "prov:label": "Deventer-512",
      "sc:license": "CC-BY-4.0"
    }
  ],
  "prov:wasGeneratedBy": [
    {
      "@type": "prov:Activity",
      "prov:type": {
        "@id": "https://www.wikidata.org/wiki/Q4929239"
      },
      "prov:label": "Download",
      "sc:description": "The source imagery and raster building masks come from the Inria Aerial Image Labeling dataset. Building footprint vectors are derived from OpenStreetMap."
    },
    {
      "@type": "prov:Activity",
      "prov:type": {
        "@id": "https://www.wikidata.org/wiki/Q5227332"
      },
      "prov:label": "Correct Annotation",
      "sc:description": "OpenStreetMap footprints were aligned to the imagery, residual mismatches were manually reviewed, and interior rings were restored using the raster masks. Automated geometry cleaning was applied, including self-intersection repair and checks for interior-ring containment. The final annotations are released as image-coordinate GeoJSON polygons."
    },
    {
      "@type": "prov:Activity",
      "prov:type": {
        "@id": "https://www.wikidata.org/wiki/Q4929239"
      },
      "prov:label": "Download",
      "sc:description": "Download data from Hugging Face"
    },
    {
      "@type": "prov:Activity",
      "prov:type": {
        "@id": "https://www.wikidata.org/wiki/Q5227332"
      },
      "prov:label": "Expert Examination",
      "sc:description": "Our human expert examine the annotations and correct some wrong labels"
    },
    {
      "@type": "prov:Activity",
      "prov:label": "Patch extraction and packaging",
      "sc:description": "Inria tiles were split by city (29 train / 7 val tiles per city) and cut into a 10x10 grid of 512x512 patches; polygons were clipped to each patch and clipped parts with a bounding-box side of 5 px or less were removed; training patches without buildings were dropped. Deventer-512 val and test splits were merged into val and image ids were renumbered. Each task split was exported as COCO-layout JSON and GeoParquet."
    }
  ]
}