dd-l1-london-parks-count

Status: done
Score: 1.000
Duration: 0:30
Cost: 0.09¢
Model: deepseek/deepseek-v4-flash

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).
0:00
System info 
{
  "adapter": "openrouter",
  "model": "deepseek/deepseek-v4-flash",
  "base_url": "https://openrouter.ai/api/v1"
}
0:03 
Let me start by exploring the working directory to find the data file.
0:03
Bash ls /work/ 
london_parks.fgb
0:06 
Let me explore the data to understand its structure.
0:06
Bash cd /work && python3 -c " 
cd /work && python3 -c "
import geopandas as gpd
import pyogrio

# Read the data
gdf = gpd.read_file('london_parks.fgb')
print('Columns:', gdf.columns.tolist())
print('CRS:', gdf.crs)
print('Length:', len(gdf))
print(gdf.head(3))
print(gdf.dtypes)
"
Columns: ['id', 'name', 'class', 'geometry']
CRS: EPSG:27700
Length: 317
                                     id  ...                                           geometry
0  2b746b97-b0ed-35cc-8eb2-28a64821d7d8  ...  MULTIPOLYGON (((532381.849 178719.026, 532391....
1  669c73cb-2314-3f8b-9b24-14b7db998247  ...  MULTIPOLYGON (((532435.728 178838.472, 532437....
2  bcdbe219-4769-3d9a-bec6-ba44b2f4301f  ...  MULTIPOLYGON (((532657.956 178707.481, 532664....

[3 rows x 4 columns]
id               str
name             str
class            str
geometry    geometry
dtype: object
0:13 
The data is in EPSG:27700 (British National Grid, which uses meters). I need to:

1. Calculate area of each park in the original CRS (since it's in meters, square meters area can be computed)
2. Filter those with area >= 1 hectare (1 hectare = 10,000 square meters)
3. Calculate the combined area in hectares
4. Compute the bounding box in WGS84 (EPSG:4326)

Let me write a script to do this.
0:13
Write /work/solve.py
content · 35 lines · py 
import geopandas as gpd
import json

# Read the data
gdf = gpd.read_file('/work/london_parks.fgb')
print(f"Loaded {len(gdf)} parks, CRS: {gdf.crs}")

# Compute area in square metres (CRS is EPSG:27700, units are metres)
gdf['area_sq_m'] = gdf.geometry.area

# Filter to parks >= 1 hectare (10000 sq m)
large_parks = gdf[gdf['area_sq_m'] >= 10000].copy()
print(f"Parks >= 1 ha: {len(large_parks)}")

# Total area in hectares
total_area_ha = large_parks['area_sq_m'].sum() / 10000
print(f"Total area: {total_area_ha:.2f} ha")

# Convert to WGS84 for bounding box
large_parks_wgs84 = large_parks.to_crs('EPSG:4326')
bbox = large_parks_wgs84.total_bounds  # [xmin, ymin, xmax, ymax]
print(f"BBox WGS84: {bbox.tolist()}")

# Write output
output = {
    "count": int(len(large_parks)),
    "total_area_ha": round(total_area_ha, 6),
    "bbox_wgs84": [round(b, 6) for b in bbox.tolist()]
}

with open('/work/london_parks_summary.json', 'w') as f:
    json.dump(output, f, indent=2)

print("\nWritten to london_parks_summary.json")
print(json.dumps(output, indent=2))
Wrote /work/solve.py (1059 chars).
0:17 
Wait, the user said "Output parks_summary.json" but I named it london_parks_summary.json. Let me re-read: "Output parks_summary.json with keys count, total_area_ha, and bbox_wgs84". They say parks_summary.json. Let me adjust.
0:17
Edit /work/solve.py 
Edited /work/solve.py.
0:21 
Wait, the user said "Output parks_summary.json". Let me check what I wrote - I originally had `london_parks_summary.json` and corrected to `parks_summary.json`. Good.

Now let's run it.
0:21
Bash cd /work && python solve.py 
Loaded 317 parks, CRS: EPSG:27700
Parks >= 1 ha: 42
Total area: 519.16 ha
BBox WGS84: [-0.19932378751294652, 51.49147199538401, -0.08248178747996572, 51.54706589542573]

Written to parks_summary.json
{
  "count": 42,
  "total_area_ha": 519.162081,
  "bbox_wgs84": [
    -0.199324,
    51.491472,
    -0.082482,
    51.547066
  ]
}
0:24 
Let me verify the output file was created correctly.
0:24
Read /work/parks_summary.json 
     1	{
     2	  "count": 42,
     3	  "total_area_ha": 519.162081,
     4	  "bbox_wgs84": [
     5	    -0.199324,
     6	    51.491472,
     7	    -0.082482,
     8	    51.547066
     9	  ]
    10	}
0:28 
The file is written correctly. Let me summarise the results.
0:28