Currently, the calculate_building_metrics function in our codebase calculates building area density within specified boundaries. However, we also need to calculate building count density to gain insights into the number of buildings per square kilometer.
Proposed Enhancement:
- Add Building Count Density Calculation: Measure the number of buildings per square kilometer within each administrative boundary.
- Integration: Modify the results dictionary to include the building count density metric.
Steps to Implement:
- Within the loop that processes each boundary group:
- Calculate
boundary_area_km2 as is currently done.
- Add a new metric,
building_count_density, calculated as building_count / boundary_area_km2.
- Update the results dictionary in the loop to:
results.append({
f"ADM{admin_level}_PT": boundary[f"ADM{admin_level}_PT"].iloc[0],
f"ADM{admin_level}_PCODE": pcode,
"building_count": building_count,
"building_density_km2": building_density,
"building_count_density_km2": building_count_density
})
Benefits:
Provides a complementary perspective to building area density.
Allows for more comprehensive urban analysis and planning insights.
Additional Notes:
Ensure all dependencies and input data files are updated accordingly.
Update documentation to reflect this new metric.
Currently, the calculate_building_metrics function in our codebase calculates building area density within specified boundaries. However, we also need to calculate building count density to gain insights into the number of buildings per square kilometer.
Proposed Enhancement:
Steps to Implement:
boundary_area_km2as is currently done.building_count_density, calculated asbuilding_count / boundary_area_km2.Benefits:
Provides a complementary perspective to building area density.
Allows for more comprehensive urban analysis and planning insights.
Additional Notes:
Ensure all dependencies and input data files are updated accordingly.
Update documentation to reflect this new metric.