crs-l2-svalbard-polar-areas

Rerun

# /// script
# requires-python = ">=3.12"
# dependencies = ["geopandas", "shapely", "pyproj", "pandas"]
# ///

import geopandas as gpd
import pandas as pd

def solve():
    # Load the glacier data
    input_file = "svalbard_glaciers_wgs84.gpkg"
    gdf = gpd.read_file(input_file)

    # Svalbard is at high latitude (~78N). 
    # For area measurements in high latitudes, North Pole Stereographic is appropriate.
    # EPSG:3413 is NSIDC Sea Ice Polar Stereographic North, which is standard for Arctic.
    # Alternatively, EPSG:3031 (WGS 84 / Arctic Polar Stereographic) is also common.
    # Let's use EPSG:3031 as it is a standard WGS84-based polar projection.
    target_crs = "EPSG:3031"
    
    # Project to the target CRS
    gdf_projected = gdf.to_crs(target_crs)

    # Calculate area in square meters and convert to km2
    gdf_projected['area_km2'] = gdf_projected.geometry.area / 10**6

    # Get bounding boxes in the projected CRS
    # bounds returns (minx, miny, maxx, maxy)
    bounds = gdf_projected.geometry.bounds
    gdf_projected['bbox_minx_polar'] = bounds['minx']
    gdf_projected['bbox_miny_polar'] = bounds['miny']
    gdf_projected['bbox_maxx_polar'] = bounds['maxx']
    gdf_projected['bbox_maxy_polar'] = bounds['maxy']

    # Get EPSG code
    epsg_code = int(gdf_projected.crs.to_epsg())
    gdf_projected['crs_epsg'] = epsg_code

    # Sort by area descending and take top 20
    top_20 = gdf_projected.sort_values(by='area_km2', ascending=False).head(20)

    # Select and rename columns as requested
    # columns: name, area_km2, bbox_minx_polar, bbox_miny_polar, bbox_maxx_polar, bbox_maxy_polar, crs_epsg
    result_df = top_20[['name', 'area_km2', 'bbox_minx_polar', 'bbox_miny_polar', 'bbox_maxx_polar', 'bbox_maxy_polar', 'crs_epsg']]

    # Save to CSV
    output_file = "svalbard_glaciers_top20.csv"
    result_df.to_csv(output_file, index=False)
    print(f"Successfully saved top 20 glaciers to {output_file}")

if __name__ == "__main__":
    solve()

# /// script
# requires-python = ">=3.12"
# dependencies = ["geopandas", "shapely", "pyproj", "pandas", "pyogrio"]
# ///

import geopandas as gpd
import pandas as pd

def solve():
    # Load the glacier data
    # The file is in the current directory based on the prompt's context
    input_file = "svalbard_glaciers_wgs84.gpkg"
    gdf = gpd.read_file(input_file)

    # Svalbard is at high latitude (~78N). 
    # For area measurements in high latitudes, North Pole Stereographic is appropriate.
    # EPSG:3031 (WGS 84 / Arctic Polar Stereographic) is standard.
    target_crs = "EPSG:3031"
    
    # Project to the target CRS
    gdf_projected = gdf.to_crs(target_crs)

    # Calculate area in square meters and convert to km2
    gdf_projected['area_km2'] = gdf_projected.geometry.area / 10**6

    # Get bounding boxes in the projected CRS
    bounds = gdf_projected.geometry.bounds
    gdf_projected['bbox_minx_polar'] = bounds['minx']
    gdf_projected['bbox_miny_polar'] = bounds['miny']
    gdf_projected['bbox_maxx_polar'] = bounds['maxx']
    gdf_projected['bbox_maxy_polar'] = bounds['maxy']

    # Get EPSG code
    epsg_code = int(gdf_projected.crs.to_epsg())
    gdf_projected['crs_epsg'] = epsg_code

    # Sort by area descending and take top 20
    top_20 = gdf_projected.sort_values(by='area_km2', ascending=False).head(20)

    # Select and rename columns as requested
    # columns: name, area_km2, bbox_minx_polar, bbox_miny_polar, bbox_maxx_polar, bbox_maxy_polar, crs_epsg
    result_df = top_20[['name', 'area_km2', 'bbox_minx_polar', 'bbox_miny_polar', 'bbox_maxx_polar', 'bbox_maxy_polar', 'crs_epsg']]

    # Save to CSV
    output_file = "svalbard_glaciers_top20.csv"
    result_df.to_csv(output_file, index=False)
    print(f"Successfully saved top 20 glaciers to {output_file}")

if __name__ == "__main__":
    solve()

# /// script
# requires-python = ">=3.12"
# dependencies = ["geopandas", "shapely", "pyproj", "pandas", "pyogrio"]
# ///

import geopandas as gpd
import pandas as pd

def solve():
    # Load the glacier data
    input_file = "svalbard_glaciers_wgs84.gpkg"
    gdf = gpd.read_file(input_file)

    # Svalbard is at high latitude (~78N). 
    # For area measurements in high latitudes, North Pole Stereographic is appropriate.
    # EPSG:3031 (WGS 84 / Arctic Polar Stereographic) is standard.
    target_crs = "EPSG:3031"
    
    # Project to the target CRS
    gdf_projected = gdf.to_crs(target_crs)

    # Calculate area in square meters and convert to km2
    gdf_projected['area_km2'] = gdf_projected.geometry.area / 10**6

    # Get bounding boxes in the projected CRS
    # bounds returns (minx, miny, maxx, maxy)
    bounds = gdf_projected.geometry.bounds
    gdf_projected['bbox_minx_polar'] = bounds['minx']
    gdf_projected['bbox_miny_polar'] = bounds['miny']
    gdf_projected['bbox_maxx_polar'] = bounds['maxx']
    gdf_projected['bbox_maxy_polar'] = bounds['maxy']

    # Get EPSG code
    epsg_code = int(gdf_projected.crs.to_epsg())
    gdf_projected['crs_epsg'] = epsg_code

    # Sort by area descending and take top 20
    top_20 = gdf_projected.sort_values(by='area_km2', ascending=False).head(20)

    # Select and rename columns as requested
    # columns: name, area_km2, bbox_minx_polar, bbox_miny_polar, bbox_maxx_polar, bbox_maxy_polar, crs_epsg
    result_df = top_20[['name', 'area_km2', 'bbox_minx_polar', 'bbox_miny_polar', 'bbox_maxx_polar', 'bbox_maxy_polar', 'crs_epsg']]

    # Save to CSV
    output_file = "svalbard_glaciers_top20.csv"
    result_df.to_csv(output_file, index=False)
    print(f"Successfully saved top 20 glaciers to {output_file}")

if __name__ == "__main__":
    solve()