sunlight-analysis

To calculate solar position and generate a sun-path diagram, you need to specify your target location and time. The analysis outputs azimuth and elevation angles, which are then visualized to support site analysis and massing decisions for architectural daylight planning.

Yes, you can analyze terrain shadow from a DEM file for site analysis. By processing digital elevation models, the tool calculates terrain shadows to inform massing and daylight design, helping you assess outdoor comfort and building performance across different times.

You can assess annual sun hours and shadow hours at a specific point by running the solar position calculations across a full year. This outputs cumulative daylight and nighttime periods, directly supporting energy modeling and outdoor comfort planning for your site.

Yes, you need specific Python libraries to run solar position and shadow analysis. The implementation relies on pysolar, matplotlib, numpy, pytz, shapely, and rasterio to execute the underlying calculations and generate visual diagrams.

The best way to visualize building shadows and sun paths across multiple locations is by using matplotlib to render the computed solar data. This approach generates sun-path diagrams and shadow projections, allowing you to compare daylight design impacts across various sites.

You use rasterio and shapely for terrain shadow analysis because rasterio handles DEM file input and geospatial data, while shapely processes the resulting geometric boundaries. Together they compute terrain shadow geometry for architectural site analysis.