src/data/extractors/landuse.py

"""
Land use feature extractor.
Single Responsibility: Extract land cover and vegetation features.
"""
import geopandas as gpd
from typing import Dict, Any
from .base import BaseFeatureExtractor


class LandUseExtractor(BaseFeatureExtractor):
    """
    Extracts land use and vegetation features.

    Features:
    - Forest cover (%)
    - Agricultural land (%)
    - Urban area (%)
    - NDVI or vegetation index
    - Impervious surface (%)
    """

    def extract(self, basin_gdf: gpd.GeoDataFrame) -> Dict[str, Any]:
        """
        Extract land use features from basin.

        Args:
            basin_gdf: GeoDataFrame with basin geometry

        Returns:
            Dictionary with land use features
        """
        if not self.validate_inputs(basin_gdf):
            raise ValueError("Invalid basin GeoDataFrame")

        # Placeholder for land use extraction
        # Would involve:
        # - Rasterizing land use/land cover datasets (Corine, ESA WorldCover)
        # - Computing zonal statistics per class
        # - Extracting NDVI from satellite imagery (Sentinel-2, Landsat)
        return {
            "forest_cover_pct": None,
            "agricultural_land_pct": None,
            "urban_area_pct": None,
            "water_body_pct": None,
            "ndvi_mean": None,
            "ndvi_std": None,
            "impervious_surface_pct": None
        }

    def get_feature_names(self) -> list:
        """Get list of feature names."""
        return [
            "forest_cover_pct", "agricultural_land_pct",
            "urban_area_pct", "water_body_pct",
            "ndvi_mean", "ndvi_std", "impervious_surface_pct"
        ]