crs-l2-svalbard-polar-areas
Map (reference ← swipe → agent)
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svalbard_glaciers — I need an honest size ranking of these high-latitude glaciers using true geographic area, not the distorted values you'd get from raw lat/lon coordinates. Pick the most appropriate coordinate system for measuring area at these latitudes and give me the top 20 by area as CSV: columns name, area_km2, bbox_minx_polar, bbox_miny_polar, bbox_maxx_polar, bbox_maxy_polar, crs_epsg — bboxes in the same projected metres as the area, and crs_epsg the integer EPSG code of the CRS you used. Sort by area_km2 descending. File: svalbard_glaciers_top20.csv.
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System info
{
"adapter": "openrouter",
"model": "google/gemma-4-26b-a4b-it",
"base_url": "https://openrouter.ai/api/v1"
}
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Bash
ls -F
svalbard_glaciers_wgs84.gpkg
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Bash
ogrinfo -al -so svalbard_glaciers_wgs84.gpkg
INFO: Open of `svalbard_glaciers_wgs84.gpkg'
using driver `GPKG' successful.
Layer name: glaciers
Geometry: Multi Polygon
Feature Count: 169
Extent: (10.787712, 77.463025) - (33.486668, 80.311555)
Layer SRS WKT:
GEOGCRS["WGS 84",
ENSEMBLE["World Geodetic System 1984 ensemble",
MEMBER["World Geodetic System 1984 (Transit)"],
MEMBER["World Geodetic System 1984 (G730)"],
MEMBER["World Geodetic System 1984 (G873)"],
MEMBER["World Geodetic System 1984 (G1150)"],
MEMBER["World Geodetic System 1984 (G1674)"],
MEMBER["World Geodetic System 1984 (G1762)"],
MEMBER["World Geodetic System 1984 (G2139)"],
MEMBER["World Geodetic System 1984 (G2296)"],
ELLIPSOID["WGS 84",6378137,298.257223563,
LENGTHUNIT["metre",1]],
ENSEMBLEACCURACY[2.0]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
CS[ellipsoidal,2],
AXIS["geodetic latitude (Lat)",north,
ORDER[1],
ANGLEUNIT["degree",0.0174532925199433]],
AXIS["geodetic longitude (Lon)",east,
ORDER[2],
ANGLEUNIT["degree",0.0174532925199433]],
USAGE[
SCOPE["Horizontal component of 3D system."],
AREA["World."],
BBOX[-90,-180,90,180]],
ID["EPSG",4326]]
Data axis to CRS axis mapping: 2,1
FID Column = fid
Geometry Column = geom
id: String (0.0)
name: String (0.0)
subtype: String (0.0)
class: String (0.0)
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Write
/work/solve.py
content · 44 lines · py
import geopandas as gpd
# Load the glaciers layer
gdf = gpd.read_file('svalbard_glaciers_wgs84.gpkg', layer='glaciers')
# Check the CRS - it should be EPSG:4326
print(f"Original CRS: {gdf.crs}")
# For Svalbard (approx 78N), we need an appropriate projection for area measurement.
# NSIDC Sea Ice Polar Stereographic (EPSG:3413) is a good candidate for polar regions.
# Alternatively, North Pole Stereographic (EPSG:3995) or similar.
# Let's use EPSG:3413 (NSIDC Sea Ice Polar Stereographic North).
target_crs = "EPSG:3413"
gdf_projected = gdf.to_crs(target_crs)
# Calculate area in square meters, then convert to km2
gdf_projected['area_km2'] = gdf_projected.geometry.area / 10**6
# Sort by area descending and take top 20
top20 = gdf_projected.sort_values(by='area_km2', ascending=False).head(20).copy()
# Get bounding box in projected coordinates
# bbox_minx_polar, bbox_miny_polar, bbox_maxx_polar, bbox_maxy_polar
top20['bbox_minx_polar'] = top20.geometry.bounds.minx
top20['bbox_miny_polar'] = top20.geometry.bounds.miny
top20['bbox_maxx_polar'] = top20.geometry.bounds.maxx
top20['bbox_maxy_polar'] = top20.geometry.bounds.maxy
# Prepare columns for output
# name, area_km2, bbox_minx_polar, bbox_miny_polar, bbox_maxx_polar, bbox_maxy_polar, crs_epsg
# We need to extract the EPSG code as an integer
epsg_code = gdf_projected.crs.to_epsg()
top20['crs_epsg'] = int(epsg_code)
output_cols = ['name', 'area_km2', 'bbox_minx_polar', 'bbox_miny_polar', 'bbox_maxx_polar', 'bbox_maxy_polar', 'crs_epsg']
result = top20[output_cols]
# Save to CSV
result.to_csv('svalbard_glaciers_top20.csv', index=False)
print("Success! Top 20 glaciers saved to svalbard_glaciers_top20.csv")
print(result.head())
Wrote /work/solve.py (1708 chars).
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Bash
python solve.py
Original CRS: EPSG:4326
Success! Top 20 glaciers saved to svalbard_glaciers_top20.csv
name area_km2 ... bbox_maxy_polar crs_epsg
140 Sørfonna 4146.995028 ... -365990.290930 3413
156 Vestfonna 2272.183117 ... -420978.166085 3413
168 Åsgardfonna 872.249186 ... -525034.100104 3413
78 Kvitøyjøkulen 595.277158 ... -211860.173706 3413
149 Valhallfonna 405.018065 ... -505582.963556 3413
[5 rows x 7 columns]
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Bash
head -n 5 svalbard_glaciers_top20.csv
name,area_km2,bbox_minx_polar,bbox_miny_polar,bbox_maxx_polar,bbox_maxy_polar,crs_epsg Sørfonna,4146.995028319491,1018600.817882212,-472800.3912665622,1093407.1674378568,-365990.2909299612,3413 Vestfonna,2272.1831167032924,955923.9805055511,-493366.30464676005,1014589.5375176889,-420978.1660846758,3413 Åsgardfonna,872.2491860794605,970672.3159938941,-558393.7394266115,1024973.2110542867,-525034.1001042881,3413 Kvitøyjøkulen,595.2771582678471,1028269.5074980733,-251073.05692732212,1052280.1255731431,-211860.17370643766,3413
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Bash
ls -l svalbard_glaciers_top20.csv
-rw-r--r-- 1 agent agent 2303 Jun 16 11:50 svalbard_glaciers_top20.csv
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