fio-l2-capetown-landuse-dissolve
Map (reference ← swipe → agent)
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I'm prepping a transit-corridor study for the Cape Town metro, and I need a class-level summary of `landuse` so the team's spatial-SQL notebooks can join it against the bus-route table. Can you give me one row per landuse class with the geometry unified into a single MultiPolygon, the total area in m², and the count of source parcels that fed in? Please write the result to `landuse_dissolved.geoparquet` with `class`, `area_m2`, and `parcel_count` columns.
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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
ls -F
capetown_landuse.fgb
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Write
/work/inspect_data.py
content · 13 lines · py
import geopandas as gpd
# Load the landuse data
gdf = gpd.read_file('capetown_landuse.fgb')
# Inspect the first few rows and columns to identify the landuse column and geometry
print("Columns:", gdf.columns)
print(gdf.head())
print("CRS:", gdf.crs)
# Check for common landuse column names if 'landuse' isn't the exact name
# The user said 'landuse' class, so I will look for a column named 'landuse' or similar.
Wrote /work/inspect_data.py (415 chars).
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Bash
python /work/inspect_data.py
python /work/inspect_data.py
Columns: Index(['id', 'class', 'subtype', 'geometry'], dtype='str')
id ... geometry
0 f328c054-b040-3a7d-a015-53747d608fef ... MULTIPOLYGON (((872000.605 6252622.417, 871205...
1 f1943847-f785-390c-abb0-edc923f97997 ... MULTIPOLYGON (((253543.223 6283900.241, 254921...
2 c37e40aa-f202-3b15-b68d-89dafeeaa478 ... MULTIPOLYGON (((255047.308 6280773.284, 255024...
3 b9d39db7-5dcc-379e-bfeb-c994628df5a7 ... MULTIPOLYGON (((254978.723 6280842.179, 254992...
4 0033302c-c1d6-3624-b71e-0e300db64963 ... MULTIPOLYGON (((264759.63 6280552.85, 264825.5...
[5 rows x 4 columns]
CRS: EPSG:32734
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thought<tool_call|>