geo-l1-tokyo-busstop-buffer

Rerun

import geopandas as gpd

def main():
    # Load the input data
    input_file = 'tokyo_connectors.geojson'
    output_file = 'tokyo_stop_catchments.geoparquet'
    
    try:
        gdf = gpd.read_file(input_file)
        print(f"Loaded {len(gdf)} features from {input_file}")
    except Exception as e:
        print(f"Error loading input file: {e}")
        return

    # Check if connector_id exists
    if 'connector_id' not in gdf.columns:
        print("Error: 'connector_id' column not found in input file.")
        return

    # We need to buffer in meters, so we must project to a CRS that uses meters.
    # For Tokyo, EPSG:6677 (JGD2011 / Japan Plane Rectangular CS IX) is a good choice.
    # Or we can use a generic UTM zone. Tokyo is around UTM zone 54N (EPSG:32654).
    # Let's check the original CRS first.
    print(f"Original CRS: {gdf.crs}")

    # Project to a metric CRS
    # EPSG:6677 is highly accurate for Tokyo.
    target_crs = "EPSG:6677"
    gdf_projected = gdf.to_crs(target_crs)
    print(f"Projected to {target_crs}")

    # Perform the buffer
    # buffer(400) will create a 400m buffer
    gdf_projected['geometry'] = gdf_projected.buffer(400)

    # Ensure we only have one row per connector_id and it's Polygon or MultiPolygon
    # The buffer operation on a Point/Line/Polygon returns a Polygon or MultiPolygon.
    # If the input is a Point or Line, buffer() returns a Polygon/MultiPolygon.
    # If the input was already a Polygon, buffer(0) or buffer(400) returns a Polygon.
    
    # We want to keep only the necessary columns for the join: connector_id and geometry
    # However, the user might want other columns too? 
    # "Please keep connector_id on every row with the original value preserved"
    # Usually, it's safer to keep all columns that were in the original gdf.
    
    # Revert to original CRS if necessary, but buffering in meters is easier in projected CRS.
    # Usually, for spatial joins/analysis, the resulting layer is kept in a metric CRS 
    # or converted back to WGS84. Let's convert back to WGS84 (EPSG:4326) for general use,
    # or just keep it in the metric CRS if the user prefers.
    # Given the instruction "refreshing the 400 m walkable-catchment layer", 
    # keeping it in WGS84 is standard for web maps.
    
    gdf_final = gdf_projected.to_crs(epsg=4326)
    
    # Save to GeoParquet
    gdf_final.to_parquet(output_file)
    print(f"Saved {len(gdf_final)} features to {output_file}")

if __name__ == "__main__":
    main()

import geopandas as gpd

def main():
    # Load the input data
    input_file = 'tokyo_connectors.geojson'
    output_file = 'tokyo_stop_catchments.geoparquet'
    
    try:
        gdf = gpd.read_file(input_file)
        print(f"Loaded {len(gdf)} features from {input_file}")
    except Exception as e:
        print(f"Error loading input file: {e}")
        return

    # Check if connector_id exists
    if 'connector_id' not in gdf.columns:
        print("Error: 'connector_id' column not found in input file.")
        return

    # We need to buffer in meters, so we must project to a CRS that uses meters.
    # For Tokyo, EPSG:6677 (JGD2011 / Japan Plane Rectangular CS IX) is a good choice.
    target_crs = "EPSG:6677"
    gdf_projected = gdf.to_crs(target_crs)
    print(f"Projected to {target_crs}")

    # Perform the buffer (400 meters)
    gdf_projected['geometry'] = gdf_projected.buffer(400)

    # The user wants one Polygon or MultiPolygon row per input connector.
    # Buffer automatically returns a Polygon or MultiPolygon.
    # If multiple geometries resulted from a buffer on a multi-part geometry, 
    # they are already combined into a MultiPolygon. 
    # If we had multiple rows with the same connector_id, we might need to dissolve,
    # but the prompt implies 1:1 mapping ("every connector").
    
    # Convert back to WGS84 (EPSG:4326) for the output
    gdf_final = gdf_projected.to_crs(epsg=4326)
    
    # Save to GeoParquet
    gdf_final.to_parquet(output_file)
    print(f"Saved {len(gdf_final)} features to {output_file}")

if __name__ == "__main__":
    main()