feat: operationalize Flemish land and nature themes

2026-07-17 22:38:25 +02:00
parent 0718d0ebba
commit c787fb2184
27 changed files with 2010 additions and 12 deletions
@@ -68,6 +68,10 @@ class ThematicRasterAnalysisService:
    @staticmethod
    def _unsupported_metrics(product: ThematicRasterProduct) -> list[str]:
        if product.metric_kind == "binary_area":
+            if product.theme == "forest":
+                return ["tree_count", "canopy_cover", "timber_volume", "legal_forest_boundary"]
+            if product.theme == "agriculture":
+                return ["declared_parcel_area", "crop_declaration", "ownership", "cadastral_area"]
            return ["object_count", "parcel_area", "current_land_use"]
        if product.metric_kind == "population_density":
            return ["current_population", "household_count", "address_level_population"]
@@ -152,7 +156,12 @@ class ThematicRasterAnalysisService:
            positive_count = int(np.count_nonzero(values >= 0.5))
            positive_area_ha = positive_count * cell_area_m2 / 10_000.0
            positive_share = positive_count / max(1, valid_cell_count) * 100.0
-            label = "Ruimtebeslag" if product.theme == "space_occupation" else "Open ruimte"
+            label = {
+                "space_occupation": "Ruimtebeslag",
+                "open_space": "Open ruimte",
+                "forest": "Bos",
+                "agriculture": "Akker en landbouwgrasland",
+            }[product.theme]
            metrics = [
                metric(f"{product.theme}_area_ha", f"{label} in selectie", positive_area_ha, "ha", "positive_source_cells_times_cell_area"),
                metric(f"{product.theme}_share_pct", f"Aandeel {label.lower()}", positive_share, "%", "positive_source_cells_divided_by_valid_selected_cells"),
@@ -216,6 +225,8 @@ class ThematicRasterAnalysisService:
        palettes = {
            "space_occupation": np.asarray([[251, 231, 211], [190, 62, 51]], dtype="float64"),
            "open_space": np.asarray([[221, 238, 219], [38, 122, 70]], dtype="float64"),
+            "forest": np.asarray([[223, 237, 226], [43, 117, 72]], dtype="float64"),
+            "agriculture": np.asarray([[245, 237, 204], [166, 122, 35]], dtype="float64"),
            "population": np.asarray([[238, 231, 246], [103, 58, 151]], dtype="float64"),
            "accessibility": np.asarray([[233, 241, 244], [15, 118, 110]], dtype="float64"),
            "services": np.asarray([[255, 244, 191], [182, 109, 22]], dtype="float64"),