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KARST feature extractor for geological characteristics.
Single Responsibility: Extract karst-specific features.
"""
import geopandas as gpd
from typing import Dict, Any, Optional
from pathlib import Path
from .base import BaseFeatureExtractor
class KarstExtractor(BaseFeatureExtractor):
"""
Extracts karst-related geological features.
Features:
- Karst presence/index
- Bedrock permeability
- Sinkhole density
- Infiltration capacity (from IDPR data)
- Aquifer characteristics
"""
def __init__(
self,
idpr_data: Optional[Any] = None,
karst_layer: Optional[Path] = None,
**kwargs
):
"""
Initialize karst extractor.
Args:
idpr_data: IDPR dataframe (infiltration vs runoff)
karst_layer: Path to karst geological layer (shapefile/raster)
**kwargs: Additional parameters
"""
super().__init__(**kwargs)
self.idpr_data = idpr_data
self.karst_layer = karst_layer
def extract(self, basin_gdf: gpd.GeoDataFrame) -> Dict[str, Any]:
"""
Extract karst features from basin.
Args:
basin_gdf: GeoDataFrame with basin geometry
Returns:
Dictionary with karst features
"""
if not self.validate_inputs(basin_gdf):
raise ValueError("Invalid basin GeoDataFrame")
features = {}
# IDPR-based infiltration capacity
if self.idpr_data is not None:
features.update(self._extract_idpr_features(basin_gdf))
# Karst geological features (placeholder)
if self.karst_layer:
features.update(self._extract_karst_geology(basin_gdf))
return features
def _extract_idpr_features(self, basin_gdf: gpd.GeoDataFrame) -> Dict[str, float]:
"""
Extract IDPR (infiltration vs runoff tendency) features.
IDPR developed by BRGM measures tendency toward infiltration or runoff.
Higher values = more infiltration (karst behavior)
"""
# This would involve spatial join with IDPR data
# Placeholder implementation
return {
"idpr_mean": None, # Mean IDPR value in basin
"idpr_max": None, # Max IDPR (most karst-prone areas)
"infiltration_capacity": None # Derived metric
}
def _extract_karst_geology(self, basin_gdf: gpd.GeoDataFrame) -> Dict[str, float]:
"""
Extract karst geological characteristics.
This would involve:
- Intersecting with geological maps
- Identifying karst lithology (limestone, dolomite)
- Calculating karst area fraction
"""
return {
"karst_presence": None, # Boolean or fraction
"karst_area_fraction": None, # % of basin with karst
"bedrock_permeability": None,# Estimated permeability
"sinkhole_density": None # Sinkholes per km²
}
def get_feature_names(self) -> list:
"""Get list of feature names."""
return [
"idpr_mean", "idpr_max", "infiltration_capacity",
"karst_presence", "karst_area_fraction",
"bedrock_permeability", "sinkhole_density"
]
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