dd-l1-london-parks-count

Status: done
Score: 1.000
Duration: 0:40
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"
}
0:07
Let me first explore the working directory to find the input file(s).
0:07
Bash ls -la /work/
total 192
drwxr-xr-x 1 agent agent     32 Jun 18 00:29 .
drwxr-xr-x 1 root  root      14 Jun 18 00:29 ..
-rw-r--r-- 1 agent agent 193504 Jun 18 00:29 london_parks.fgb
0:11
The input file is `london_parks.fgb` - a FlatGeobuf file. Let me inspect it to understand its structure.
0:11
Bash cd /work && python3 -c "
cd /work && python3 -c "
import geopandas as gpd
gdf = gpd.read_file('london_parks.fgb')
print('CRS:', gdf.crs)
print('Columns:', gdf.columns.tolist())
print('Shape:', gdf.shape)
print()
print(gdf.head(3))
print()
print(gdf.dtypes)
"
CRS: EPSG:27700
Columns: ['id', 'name', 'class', 'geometry']
Shape: (317, 4)

                                     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
0:18
The data is in EPSG:27700 (British National Grid, metric). So area calculations will be in square metres. Let me filter to parks >= 1 hectare (10,000 m²), compute the summary stats, and output the JSON.

Plan:
1. Calculate area in m² (from geometry in EPSG:27700)
2. Filter >= 10000 m² (1 hectare)
3. Count them
4. Sum area in hectares (m² / 10000)
5. Compute bounding box in WGS84 (EPSG:4326)
6. Write JSON
0:18
Bash cd /work && python3 -c "
cd /work && python3 -c "
import geopandas as gpd
import json

gdf = gpd.read_file('london_parks.fgb')
print('CRS:', gdf.crs)

# Area in m²
gdf['area_m2'] = gdf.geometry.area
print('Area stats (m²):')
print(gdf['area_m2'].describe())

# Filter >= 1 ha = 10000 m²
parks_large = gdf[gdf['area_m2'] >= 10000].copy()
print(f'\nParks >= 1 ha: {len(parks_large)}')

# Total area in hectares
total_area_ha = parks_large['area_m2'].sum() / 10000
print(f'Total area (ha): {total_area_ha:.2f}')

# Bounding box in WGS84
parks_wgs84 = parks_large.to_crs('EPSG:4326')
bbox = parks_wgs84.total_bounds  # [xmin, ymin, xmax, ymax]
print(f'bbox: {bbox.tolist()}')
"
CRS: EPSG:27700
Area stats (m²):
count    3.170000e+02
mean     1.859891e+04
std      1.207272e+05
min      6.435495e+01
25%      9.757476e+02
50%      2.274718e+03
75%      5.231445e+03
max      1.389197e+06
Name: area_m2, dtype: float64

Parks >= 1 ha: 42
Total area (ha): 519.16
bbox: [-0.19932378751294652, 51.49147199538401, -0.08248178747996572, 51.54706589542573]
0:24
Let me write the summary JSON file with these values.
0:24
Write /work/parks_summary.json
content · 5 lines · json
{
  "count": 42,
  "total_area_ha": 519.16,
  "bbox_wgs84": [-0.19932378751294652, 51.49147199538401, -0.08248178747996572, 51.54706589542573]
}
Wrote /work/parks_summary.json (144 chars).
0:28
Let me verify the output file and the sanity of the coordinates.
0:28
Bash cd /work && python3 -c "
cd /work && python3 -c "
import json
with open('parks_summary.json') as f:
    d = json.load(f)
print(d)
# sanity check
xmin, ymin, xmax, ymax = d['bbox_wgs84']
assert -180 <= xmin <= 180, 'xmin out of range'
assert -180 <= xmax <= 180, 'xmax out of range'
assert -90 <= ymin <= 90, 'ymin out of range'
assert -90 <= ymax <= 90, 'ymax out of range'
assert xmin < xmax and ymin < ymax, 'bbox flipped'
print('Bbox sanity check passed')
print(f'File size: {len(json.dumps(d))} chars')
" && ls -la /work/parks_summary.json
{'count': 42, 'total_area_ha': 519.16, 'bbox_wgs84': [-0.19932378751294652, 51.49147199538401, -0.08248178747996572, 51.54706589542573]}
Bbox sanity check passed
File size: 136 chars
-rw-r--r-- 1 agent agent 144 Jun 18 00:29 /work/parks_summary.json
0:38
Everything checks out. Let me summarize what was done.
0:38