67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
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"""Labels of Retrogressive-Thaw-Slumps (RTS).
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Assumes that the level 1 and level 2 DARTS features have been downloaded into $DATA_DIR / entropyc-rts / darts: https://arcticdata.io/catalog/view/doi:10.18739/A22B8VD7C
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Author: Tobias Hölzer
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Date: October 2025
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"""
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import os
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from pathlib import Path
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from typing import Literal
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import cyclopts
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import geopandas as gpd
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from rich.progress import track
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DATA_DIR = Path(os.environ.get("DATA_DIR", "../../data")) / "entropyc-rts"
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LEVEL2_PATH = DATA_DIR / "darts" / "DARTS_NitzeEtAl_v1-2_features_2018-2023_level2.parquet"
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LEVEL2_COV_PATH = DATA_DIR / "darts" / "DARTS_NitzeEtAl_v1-2_coverage_2018-2023_level2.parquet"
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def extract_darts_rts(grid: Literal["hex", "healpix"], level: int):
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"""Extract RTS labels from DARTS dataset.
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Args:
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grid (Literal["hex", "healpix"]): The grid type to use.
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level (int): The grid level to use.
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"""
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darts_l2 = gpd.read_parquet(LEVEL2_PATH)
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darts_cov_l2 = gpd.read_parquet(LEVEL2_COV_PATH)
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gridname = f"permafrost_{grid}{level}"
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grid = gpd.read_parquet(DATA_DIR / f"grids/{gridname}_grid.parquet")
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grid_l2 = grid.overlay(darts_l2.to_crs(grid.crs), how="intersection")
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grid_cov_l2 = grid.overlay(darts_cov_l2.to_crs(grid.crs), how="intersection")
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years = list(grid_cov_l2["year"].unique())
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for year in track(years, total=len(years), description="Processing years..."):
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subset = grid_l2[grid_l2["year"] == year]
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subset_cov = grid_cov_l2[grid_cov_l2["year"] == year]
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counts = subset.groupby("cell_id").size()
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grid[f"darts_{year}_rts_count"] = grid.cell_id.map(counts)
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areas = subset.groupby("cell_id").apply(lambda x: x.geometry.area.sum(), include_groups=False)
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grid[f"darts_{year}_rts_area"] = grid.cell_id.map(areas)
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areas_cov = subset_cov.groupby("cell_id").apply(lambda x: x.geometry.area.sum(), include_groups=False)
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grid[f"darts_{year}_covered_area"] = grid.cell_id.map(areas_cov)
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grid[f"darts_{year}_coverage"] = grid[f"darts_{year}_covered_area"] / grid.geometry.area
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grid[f"darts_{year}_rts_density"] = grid[f"darts_{year}_rts_area"] / grid[f"darts_{year}_covered_area"]
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output_path = DATA_DIR / f"darts/{gridname}_darts.parquet"
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grid.to_parquet(output_path)
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print(f"Saved RTS labels to {output_path}")
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def main(): # noqa: D103
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cyclopts.run(extract_darts_rts)
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if __name__ == "__main__":
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main()
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