crs-l2-svalbard-polar-areas

Status: done
Score: 100
Duration: 1:02
Cost: 0.19¢
Model: deepseek/deepseek-v4-flash

Map (reference ← swipe → agent)

0:00
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.
0:00
System info
{
  "adapter": "openrouter",
  "model": "deepseek/deepseek-v4-flash",
  "base_url": "https://openrouter.ai/api/v1"
}
0:06
Let me start by understanding the task:

1. I need to work with Svalbard glaciers data
2. Calculate true geographic area using an appropriate projected coordinate system
3. The best CRS for measuring area at these latitudes (78°N) would be a polar projection - likely EPSG:3413 (NSIDC Sea Ice Polar Stereographic North) or EPSG:32633 (UTM zone 33N which covers Svalbard). But actually, for Svalbard which spans roughly 74°N to 81°N, a polar stereographic projection would be most appropriate. EPSG:3413 is the WGS 84 NSIDC Sea Ice Polar Stereographic North. Another option is EPSG:3995 (WGS 84 / Arctic Polar Stereographic). 

Let me first check what files are in the working directory.
0:06
Bash ls -la /work/
total 2608
drwxr-xr-x 1 agent agent      56 Jun 18 12:06 .
drwxr-xr-x 1 root  root       14 Jun 18 12:06 ..
-rw-r--r-- 1 agent agent 2670592 Jun 18 12:06 svalbard_glaciers_wgs84.gpkg
0:09
Let's first examine the data to understand its structure.
0:09
Bash cd /work && python3 -c "
cd /work && python3 -c "
import geopandas as gpd
gdf = gpd.read_file('svalbard_glaciers_wgs84.gpkg')
print('CRS:', gdf.crs)
print('Columns:', gdf.columns.tolist())
print('Shape:', gdf.shape)
print(gdf.head(3))
print(gdf.dtypes)
"
CRS: EPSG:4326
Columns: ['id', 'name', 'subtype', 'class', 'geometry']
Shape: (169, 5)
                                     id  ...                                           geometry
0  af2fac62-8f17-35dd-bb4b-cd7ac5f906b0  ...  MULTIPOLYGON (((22.78865 80.14451, 22.73235 80...
1  12ba70b6-6f49-35fa-a072-bfdc8321c987  ...  MULTIPOLYGON (((14.02517 77.97816, 14.02557 77...
2  5919887f-cdb2-3283-a884-b1146bdda8ee  ...  MULTIPOLYGON (((16.06338 78.22499, 16.06381 78...

[3 rows x 5 columns]
id               str
name             str
subtype          str
class            str
geometry    geometry
dtype: object
0:24
Svalbard is at high latitudes (~76-81°N). For area measurement at polar/Arctic latitudes, the best projected CRS would be a polar stereographic projection. The most appropriate one for Svalbard specifically would be:

- EPSG:3411 (NSIDC Sea Ice Polar Stereographic North) — but that's more for the whole Arctic
- EPSG:32633 (UTM zone 33N) — UTM zones at these high latitudes get very distorted
- EPSG:3995 (Arctic Polar Stereographic / WGS 84) — good for the Arctic region
- EPSG:5936 — WGS 84 NSIDC Sea Ice Polar Stereographic North (more recent)
- EPSG:3413 — WGS 84 NSIDC Sea Ice Polar Stereographic North

Actually, for Svalbard (which spans roughly 10°E to 35°E), a good choice is EPSG:32633 (UTM zone 33N) which covers most of Svalbard. But UTM zones at such high latitudes (above 84°N they don't apply) still work but with some distortion.

Actually, the best choice for area measurement at these high latitudes would be a **Lambert Azimuthal Equal-Area** projection centered on Svalbard, or a **Polar Stereographic** projection (which is conformal, not equal-area).

For equal-area properties, we need an equal-area projection. Options:
- EPSG:3571 — WGS 84 / North Pole LAEA Atlantic — Lambert Azimuthal Equal-Area centered on North Pole
- EPSG:3572 — WGS 84 / North Pole LAEA Bering Sea
- EPSG:3573 — WGS 84 / North Pole LAEA Alaska
- EPSG:3574 — WGS 84 / North Pole LAEA Canada
- EPSG:3575 — WGS 84 / North Pole LAEA Europe — this one covers Svalbard well
- EPSG:3576 — WGS 84 / North Pole LAEA Russia

Let me check EPSG:3575 — North Pole LAEA Europe. Its area of use includes Svalbard.

Actually, I think the best approach is to use a custom Lambert Azimuthal Equal-Area projection centered on Svalbard. But for simplicity and reproducibility with a standard EPSG code, let's look at what's available.

EPSG:3575 (WGS 84 / North Pole LAEA Europe) has a center at 10°E, 52°N with a projection center at North Pole (90°N). This is an equal-area projection good for Europe/North Atlantic/Arctic.

Actually wait, let me think more carefully. For Svalbard (78-81°N, 10-35°E), I think the best standard EPSG codes would be:

1. **EPSG:3413 (WGS 84 / NSIDC Sea Ice Polar Stereographic North)** — This is a polar stereographic projection commonly used for Arctic sea ice. It's conformal but area distortion near Svalbard is manageable.

Actually, for measuring area we really want an equal-area projection. Let me think...

The best equal-area projection for Svalbard would be a **Lambert Azimuthal Equal Area** with center near Svalbard. EPSG:3575 (North Pole LAEA Europe) has its center at 90°N, 10°E. That would work well for Svalbard.

But let me just check what CRS is commonly used for Svalbard. Actually, let me look at the data more carefully and test a few options.

Let me test with EPSG:3575 (North Pole LAEA Europe) which is an equal-area projection.
0:24
Bash cd /work && python3 -c "
cd /work && python3 -c "
import geopandas as gpd
import pyproj
gdf = gpd.read_file('svalbard_glaciers_wgs84.gpkg')
bounds = gdf.total_bounds
print('Total bounds (WGS84):', bounds)
print('Min lat:', bounds[1], 'Max lat:', bounds[3])
print('Min lon:', bounds[0], 'Max lon:', bounds[2])
print()

# Check CRS options for the area
crs_list = [3413, 3575, 3995, 5936, 32633]
for epsg in crs_list:
    try:
        crs = pyproj.CRS.from_epsg(epsg)
        area_bounds = crs.area_of_use
        if area_bounds:
            print(f'EPSG:{epsg} - {crs.name}')
            print(f'  Area of use: west={area_bounds.west}, south={area_bounds.south}, east={area_bounds.east}, north={area_bounds.north}')
    except:
        print(f'EPSG:{epsg} - could not load')
"
Total bounds (WGS84): [10.7877123 77.4630249 33.4866675 80.3115547]
Min lat: 77.4630249 Max lat: 80.3115547
Min lon: 10.7877123 Max lon: 33.4866675

EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North
  Area of use: west=-180.0, south=60.0, east=180.0, north=90.0
EPSG:3575 - WGS 84 / North Pole LAEA Europe
  Area of use: west=-180.0, south=45.0, east=180.0, north=90.0
EPSG:3995 - WGS 84 / Arctic Polar Stereographic
  Area of use: west=-180.0, south=60.0, east=180.0, north=90.0
EPSG:5936 - WGS 84 / EPSG Alaska Polar Stereographic
  Area of use: west=-180.0, south=60.0, east=180.0, north=90.0
EPSG:32633 - WGS 84 / UTM zone 33N
  Area of use: west=12.0, south=0.0, east=18.0, north=84.0
0:49
Svalbard spans roughly 10°E to 34°E and 77°N to 81°N. For area measurement at high latitudes, a polar stereographic projection is most appropriate. Let's think about which one:

- EPSG:3995 (WGS 84 / Arctic Polar Stereographic) - This is the official Arctic polar stereographic, used by the Arctic Council and many Arctic datasets. It's a good choice.
- EPSG:3413 (NSIDC Sea Ice Polar Stereographic North) - Also commonly used for Arctic sea ice.
- EPSG:3575 (North Pole LAEA Europe) - An equal-area projection for the Arctic, which is excellent for measuring areas.

For area measurement, the Lambert Azimuthal Equal Area (LAEA) EPSG:3575 is good because it's equal-area by design. But polar stereographic also gives good results.

Actually, the most appropriate for Svalbard specifically would be:
- EPSG:3575 (WGS 84 / North Pole LAEA Europe) - Equal area projection covering the whole Arctic, excellent for area calculations.
- EPSG:3995 (WGS 84 / Arctic Polar Stereographic) - Standard polar stereographic.

Let me think more carefully. "True geographic area" means we need an equal-area projection. EPSG:3575 (North Pole LAEA Europe) is a Lambert Azimuthal Equal Area projection centered on the North Pole, so it's perfect. EPSG:3413 and 3995 are polar stereographic (not equal-area but conformal), so they'd give some distortion.

Let me use EPSG:3575 (North Pole LAEA Europe) since it's explicitly equal-area and designed for the Arctic region. This is the best choice for measuring true area at these latitudes.

Actually wait - the user says "most appropriate coordinate system for measuring area at these latitudes". For measuring area, an equal-area projection is essential. EPSG:3575 (North Pole LAEA Europe) is Lambert Azimuthal Equal Area, so it's perfect.

Let me write the script.
0:49
Write /work/solve.py
content · 42 lines · py
import geopandas as gpd
import pandas as pd

EPSG_AREA = 3575  # WGS 84 / North Pole LAEA Europe — equal-area projection for Arctic

# Read input
gdf = gpd.read_file('/work/svalbard_glaciers_wgs84.gpkg')

# Filter to glaciers only (keep all since they're all glaciers)
# Convert to equal-area projection for accurate area measurement
gdf_proj = gdf.to_crs(f'EPSG:{EPSG_AREA}')

# Calculate area in km²
gdf_proj['area_km2'] = gdf_proj.geometry.area / 1_000_000  # m² → km²

# Get bounding boxes in projected coordinates
bounds = gdf_proj.geometry.bounds  # returns minx, miny, maxx, maxy
gdf_proj['bbox_minx_polar'] = bounds['minx']
gdf_proj['bbox_miny_polar'] = bounds['miny']
gdf_proj['bbox_maxx_polar'] = bounds['maxx']
gdf_proj['bbox_maxy_polar'] = bounds['maxy']

# Build result DataFrame
result = gdf_proj[['name', 'area_km2', 'bbox_minx_polar', 'bbox_miny_polar',
                   'bbox_maxx_polar', 'bbox_maxy_polar']].copy()
result['crs_epsg'] = EPSG_AREA

# Sort descending by area_km2, take top 20
result = result.sort_values('area_km2', ascending=False).head(20).reset_index(drop=True)

# Round area to 2 decimal places, bboxes to 1 decimal place
result['area_km2'] = result['area_km2'].round(2)
result['bbox_minx_polar'] = result['bbox_minx_polar'].round(1)
result['bbox_miny_polar'] = result['bbox_miny_polar'].round(1)
result['bbox_maxx_polar'] = result['bbox_maxx_polar'].round(1)
result['bbox_maxy_polar'] = result['bbox_maxy_polar'].round(1)

# Write CSV
result.to_csv('/work/svalbard_glaciers_top20.csv', index=False)

print("Top 20 glaciers (area in km², projected in EPSG:3575):")
print(result.to_string(index=False))
Wrote /work/solve.py (1639 chars).
0:50
Let me run the script and see the results.
0:50
Bash cd /work && python3 solve.py
Top 20 glaciers (area in km², projected in EPSG:3575):
             name  area_km2  bbox_minx_polar  bbox_miny_polar  bbox_maxx_polar  bbox_maxy_polar  crs_epsg
         Sørfonna   4335.83         215171.4       -1169659.3         320016.0       -1103032.4      3575
        Vestfonna   2378.88         165886.8       -1129465.2         235709.6       -1065976.4      3575
      Åsgardfonna    911.98         116295.4       -1183688.3         151327.2       -1127169.2      3575
    Kvitøyjøkulen    623.62         402965.6       -1032099.0         436293.9        -995410.6      3575
     Valhallfonna    423.70         138082.9       -1153075.3         160466.0       -1119313.7      3575
   Nordmannsfonna    130.75         184822.2       -1301911.4         201711.8       -1283039.3      3575
        Sveabreen    126.29          72592.4       -1274725.0          95742.8       -1251880.0      3575
        Gruvfonna    113.63         146755.4       -1338346.4         166742.3       -1323709.7      3575
        Veteranen     96.50         146165.2       -1201490.5         156039.3       -1175968.6      3575
 Himingbjørgfonna     84.11         132484.1       -1194435.0         148653.4       -1181539.9      3575
       Hellefonna     82.14         169182.7       -1320345.2         180933.9       -1302631.7      3575
     Heuglinbreen     71.06         190614.3       -1283966.4         201423.5       -1270566.4      3575
Nordenskiöldbreen     66.92         152250.3       -1257600.1         162882.8       -1244584.0      3575
       Eidembreen     66.89          65121.8       -1294452.6          81423.0       -1283523.9      3575
           Isrosa     46.95         187701.1       -1307515.9         201027.4       -1299877.8      3575
      Edvardbreen     46.23         171864.2       -1345952.6         184041.8       -1332415.4      3575
      Esmarkbreen     42.86          80684.2       -1301763.5          89571.9       -1289799.1      3575
      Venernbreen     42.52          70095.1       -1299447.2          82844.3       -1291034.3      3575
       Dunérbreen     40.50         132462.5       -1137756.1         139052.9       -1123931.7      3575
    Fridtjovbreen     39.08          98906.1       -1358207.3         108050.7       -1346256.5      3575
0:54
The output looks good. Let me verify the file and do quick sanity checks:

1. The CRS EPSG:3575 (North Pole LAEA Europe) is an equal-area projection suitable for the Arctic/Svalbard region. It preserves area measurements accurately, which is what we need.

2. The coordinates in metres make sense - the bounding box values are in the range of tens/hundreds of thousands, which is typical for projected CRS in the Arctic.

3. Let me verify the file exists and check its contents.
0:54
Bash ls -la /work/svalbard_glaciers_top20.csv && echo "---" && head -25 /work/svalbar...
-rw-r--r-- 1 agent agent 1352 Jun 18 12:07 /work/svalbard_glaciers_top20.csv
---
name,area_km2,bbox_minx_polar,bbox_miny_polar,bbox_maxx_polar,bbox_maxy_polar,crs_epsg
Sørfonna,4335.83,215171.4,-1169659.3,320016.0,-1103032.4,3575
Vestfonna,2378.88,165886.8,-1129465.2,235709.6,-1065976.4,3575
Åsgardfonna,911.98,116295.4,-1183688.3,151327.2,-1127169.2,3575
Kvitøyjøkulen,623.62,402965.6,-1032099.0,436293.9,-995410.6,3575
Valhallfonna,423.7,138082.9,-1153075.3,160466.0,-1119313.7,3575
Nordmannsfonna,130.75,184822.2,-1301911.4,201711.8,-1283039.3,3575
Sveabreen,126.29,72592.4,-1274725.0,95742.8,-1251880.0,3575
Gruvfonna,113.63,146755.4,-1338346.4,166742.3,-1323709.7,3575
Veteranen,96.5,146165.2,-1201490.5,156039.3,-1175968.6,3575
Himingbjørgfonna,84.11,132484.1,-1194435.0,148653.4,-1181539.9,3575
Hellefonna,82.14,169182.7,-1320345.2,180933.9,-1302631.7,3575
Heuglinbreen,71.06,190614.3,-1283966.4,201423.5,-1270566.4,3575
Nordenskiöldbreen,66.92,152250.3,-1257600.1,162882.8,-1244584.0,3575
Eidembreen,66.89,65121.8,-1294452.6,81423.0,-1283523.9,3575
Isrosa,46.95,187701.1,-1307515.9,201027.4,-1299877.8,3575
Edvardbreen,46.23,171864.2,-1345952.6,184041.8,-1332415.4,3575
Esmarkbreen,42.86,80684.2,-1301763.5,89571.9,-1289799.1,3575
Venernbreen,42.52,70095.1,-1299447.2,82844.3,-1291034.3,3575
Dunérbreen,40.5,132462.5,-1137756.1,139052.9,-1123931.7,3575
Fridtjovbreen,39.08,98906.1,-1358207.3,108050.7,-1346256.5,3575
1:01
The CSV looks good. Let me verify the results make sense:

1. Svalbard glaciers at latitudes ~77°N – 80°N — EPSG:3575 (North Pole LAEA Europe) is an equal-area projection suitable for the Arctic, which is exactly what we need for accurate area measurement.

2. The projected coordinates are in metres (typical for a LAEA projection) with values in the hundreds of thousands to low millions — that makes sense for Arctic projections.

3. The areas look reasonable — Sørfonna at ~4,336 km² and Vestfonna at ~2,379 km² are known large ice caps on Svalbard.

4. The CSV has the correct columns: name, area_km2, bbox_minx_polar, bbox_miny_polar, bbox_maxx_polar, bbox_maxy_polar, crs_epsg.

5. Sorted by area_km2 descending. ✓

6. CRS is EPSG:3575. ✓

Everything looks correct!
1:01