Description:
We currently extract total counts and lengths for OSM features within district boundaries. To enhance our analysis, we need to convert these into densities, providing insights per unit area.
Proposed Enhancement:
- Add Density Calculations for OSM Features: Convert point counts and road lengths into densities per square kilometer within each district.
- Integration: Modify the output to include density metrics for each feature.
Steps to Implement:
- Calculate the area of each district in square kilometers.
district_boundary_dataframe['area_km2'] = district_boundary_dataframe['geometry'].area / 1e6
- For each feature:
- Calculate point_density as point_count / district_area_km2.
- Calculate train_length or road_length_density as road_length / district_area_km2.
- Update the OSM features dictionary to store densities:
osm_features_districts[f"{feature_name}_density"] = [
feature_value / area_km2 for feature_value, area_km2 in zip(feature_values, district_boundary_dataframe['area_km2'])
]
- Ensure these new metrics are included in the final osm_features_dataframe.
Benefits:
- Provides normalised metrics that allow comparison between districts of different sizes.
- Facilitates more detailed urban and spatial analyses.
Additional Notes:
- Update all relevant documentation and ensure any dependent analytics reflect these new metrics.
- Consider visualizing these densities to better interpret spatial patterns.
Description:
We currently extract total counts and lengths for OSM features within district boundaries. To enhance our analysis, we need to convert these into densities, providing insights per unit area.
Proposed Enhancement:
Steps to Implement:
Benefits:
Additional Notes: