fix: NDVI harvest baseline_path never assigned after download

Generated with [Claude Code](https://claude.ai/code)
via [Happy](https://happy.engineering)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Happy <yesreply@happy.engineering>

app/indicators/ndvi.py

@@ -109,6 +109,7 @@ class NdviIndicator(BaseIndicator):
             baseline_dir = os.path.join(results_dir, "baseline")
             os.makedirs(baseline_dir, exist_ok=True)
             paths = baseline_job.download_results(baseline_dir)
+            baseline_path = self._find_tif(paths, baseline_dir)
         except Exception as exc:
             logger.warning("NDVI baseline batch download failed, degrading: %s", exc)
 

tests/test_indicator_ndvi.py

@@ -263,3 +263,67 @@ async def test_ndvi_harvest_falls_back_when_current_fails(test_aoi, test_time_ra
     )
 
     assert result.data_source == "placeholder"
+
+
+@pytest.mark.asyncio
+async def test_ndvi_harvest_uses_baseline_when_available(test_aoi, test_time_range):
+    """harvest() computes change vs baseline when baseline download succeeds."""
+    from app.indicators.ndvi import NdviIndicator
+
+    indicator = NdviIndicator()
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        # Current: higher NDVI
+        current_path = os.path.join(tmpdir, "current.tif")
+        _mock_ndvi_tif(current_path, n_months=12)
+
+        # Baseline: lower NDVI (shift down by 0.1)
+        baseline_path = os.path.join(tmpdir, "baseline.tif")
+        import rasterio
+        from rasterio.transform import from_bounds
+        rng = np.random.default_rng(99)
+        data = np.zeros((12, 10, 10), dtype=np.float32)
+        for m in range(12):
+            data[m] = 0.2 + 0.1 * np.sin(np.pi * (m - 3) / 6) + rng.normal(0, 0.02, (10, 10))
+        with rasterio.open(
+            baseline_path, "w", driver="GTiff", height=10, width=10, count=12,
+            dtype="float32", crs="EPSG:4326",
+            transform=from_bounds(32.45, 15.65, 32.65, 15.8, 10, 10),
+            nodata=-9999.0,
+        ) as dst:
+            for i in range(12):
+                dst.write(data[i], i + 1)
+
+        rgb_path = os.path.join(tmpdir, "rgb.tif")
+        _mock_true_color_tif(rgb_path)
+
+        def make_mock_job(src_path):
+            job = MagicMock()
+            job.job_id = "j-test"
+            def fake_download_results(target):
+                import shutil
+                os.makedirs(target, exist_ok=True)
+                dest = os.path.join(target, "result.tif")
+                shutil.copy(src_path, dest)
+                from pathlib import Path
+                return {Path(dest): {"type": "image/tiff"}}
+            job.download_results.side_effect = fake_download_results
+            job.status.return_value = "finished"
+            return job
+
+        current_job = make_mock_job(current_path)
+        baseline_job = make_mock_job(baseline_path)
+        true_color_job = make_mock_job(rgb_path)
+
+        result = await indicator.harvest(
+            test_aoi, test_time_range,
+            batch_jobs=[current_job, baseline_job, true_color_job],
+        )
+
+    assert result.data_source == "satellite"
+    # With distinct current vs baseline, confidence should NOT be LOW
+    # (it should be HIGH with 12 valid months)
+    assert result.confidence == ConfidenceLevel.HIGH
+    # Baseline band data should be present in chart
+    assert "baseline_mean" in result.chart_data
+    assert len(result.chart_data["baseline_mean"]) > 0