Add Darts

steps/s0_1_rts/rts.py

@@ -0,0 +1,66 @@
+"""Labels of Retrogressive-Thaw-Slumps (RTS).
+
+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
+
+Author: Tobias Hölzer
+Date: October 2025
+"""
+
+import os
+from pathlib import Path
+from typing import Literal
+
+import cyclopts
+import geopandas as gpd
+from rich.progress import track
+
+DATA_DIR = Path(os.environ.get("DATA_DIR", "../../data")) / "entropyc-rts"
+LEVEL2_PATH = DATA_DIR / "darts" / "DARTS_NitzeEtAl_v1-2_features_2018-2023_level2.parquet"
+LEVEL2_COV_PATH = DATA_DIR / "darts" / "DARTS_NitzeEtAl_v1-2_coverage_2018-2023_level2.parquet"
+
+
+def extract_darts_rts(grid: Literal["hex", "healpix"], level: int):
+    """Extract RTS labels from DARTS dataset.
+
+    Args:
+        grid (Literal["hex", "healpix"]): The grid type to use.
+        level (int): The grid level to use.
+
+    """
+    darts_l2 = gpd.read_parquet(LEVEL2_PATH)
+    darts_cov_l2 = gpd.read_parquet(LEVEL2_COV_PATH)
+
+    gridname = f"permafrost_{grid}{level}"
+    grid = gpd.read_parquet(DATA_DIR / f"grids/{gridname}_grid.parquet")
+
+    grid_l2 = grid.overlay(darts_l2.to_crs(grid.crs), how="intersection")
+    grid_cov_l2 = grid.overlay(darts_cov_l2.to_crs(grid.crs), how="intersection")
+
+    years = list(grid_cov_l2["year"].unique())
+    for year in track(years, total=len(years), description="Processing years..."):
+        subset = grid_l2[grid_l2["year"] == year]
+        subset_cov = grid_cov_l2[grid_cov_l2["year"] == year]
+
+        counts = subset.groupby("cell_id").size()
+        grid[f"darts_{year}_rts_count"] = grid.cell_id.map(counts)
+
+        areas = subset.groupby("cell_id").apply(lambda x: x.geometry.area.sum(), include_groups=False)
+        grid[f"darts_{year}_rts_area"] = grid.cell_id.map(areas)
+
+        areas_cov = subset_cov.groupby("cell_id").apply(lambda x: x.geometry.area.sum(), include_groups=False)
+        grid[f"darts_{year}_covered_area"] = grid.cell_id.map(areas_cov)
+        grid[f"darts_{year}_coverage"] = grid[f"darts_{year}_covered_area"] / grid.geometry.area
+
+        grid[f"darts_{year}_rts_density"] = grid[f"darts_{year}_rts_area"] / grid[f"darts_{year}_covered_area"]
+
+    output_path = DATA_DIR / f"darts/{gridname}_darts.parquet"
+    grid.to_parquet(output_path)
+    print(f"Saved RTS labels to {output_path}")
+
+
+def main():  # noqa: D103
+    cyclopts.run(extract_darts_rts)
+
+
+if __name__ == "__main__":
+    main()

steps/s0_1_rts/rts.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+
+uv run rts --grid hex --level 3
+uv run rts --grid hex --level 4
+uv run rts --grid hex --level 5
+uv run rts --grid healpix --level 6
+uv run rts --grid healpix --level 7
+uv run rts --grid healpix --level 8
+uv run rts --grid healpix --level 9

steps/s1_0_alphaearth/alphaearth.py

@@ -1,4 +1,8 @@
-"""Extract satellite embeddings from Google Earth Engine and map them to a grid."""
+"""Extract satellite embeddings from Google Earth Engine and map them to a grid.
+
+Author: Tobias Hölzer
+Date: October 2025
+"""
 
 import os
 import warnings