dd-l1-london-parks-count

Status: done
Score: 1.000
Duration: 0:18
Cost: 0.12¢
Model: google/gemma-4-26b-a4b-it

Map (reference ← swipe → agent)

0:00
I've got inner-London parks (london_parks) and I'm sizing the corpus before commissioning a green-space accessibility study. How many of those parks come in at one hectare or more, what's their combined area in hectares, and what bounding box would I draw around that subset on a WGS84 map? Output parks_summary.json with keys count, total_area_ha, and bbox_wgs84 (as a [xmin, ymin, xmax, ymax] array).
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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 
london_parks.fgb
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Write /work/solve.py
content · 51 lines · py 
import geopandas as gpd
import json

def main():
    # Load the parks
    parks = gpd.read_file('london_parks.fgb')
    
    # Ensure we are working with areas in a metric CRS for hectare calculation
    # If it's WGS84, we need to reproject to a local metric CRS (e.g., EPSG:27700 - British National Grid)
    if parks.crs.is_geographic:
        parks_metric = parks.to_crs(epsg=27700)
    else:
        parks_metric = parks

    # Calculate area in hectares (1 ha = 10,000 m^2)
    parks_metric['area_ha'] = parks_metric.geometry.area / 10000.0

    # Filter parks >= 1 hectare
    large_parks = parks_metric[parks_metric['area_ha'] >= 1.0].copy()

    # Count
    count = len(large_parks)

    # Total area in hectares
    total_area_ha = float(large_parks['area_ha'].sum())

    # Bounding box in WGS84
    if count > 0:
        # Reproject back to WGS84 for the bbox
        large_parks_wgs84 = large_parks.to_crs(epsg=4326)
        bbox = large_parks_wgs84.total_bounds  # [xmin, ymin, xmax, ymax]
        bbox_list = bbox.tolist()
    else:
        bbox_list = []

    # Prepare output
    output = {
        "count": count,
        "total_area_ha": total_area_ha,
        "bbox_wgs84": bbox_list
    }

    with open('parks_summary.json', 'w') as f:
        json.dump(output, f, indent=4)

    print("Summary generated successfully.")
    print(output)

if __name__ == "__main__":
    main()

Wrote /work/solve.py (1400 chars).
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Bash python solve.py 
Summary generated successfully.
{'count': 42, 'total_area_ha': 519.1620805430861, 'bbox_wgs84': [-0.19932378751294652, 51.49147199538401, -0.08248178747996572, 51.54706589542573]}
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Bash cat parks_summary.json 
{
    "count": 42,
    "total_area_ha": 519.1620805430861,
    "bbox_wgs84": [
        -0.19932378751294652,
        51.49147199538401,
        -0.08248178747996572,
        51.54706589542573
    ]
}
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