4 posts
Build a printable model of central Durham from OpenStreetMap footprints and LiDAR heights. Give every building a roof height, or shape the roofs from the surface model, remove detail too thin to print, and prove the city and its two-colour parts are watertight.
Estimate rooftop solar potential in Python for 2,148 buildings in Manchester: take a 1 m Environment Agency LiDAR DSM and Overture Maps footprints, compute roof slope and aspect, trace horizon angles for shading from neighbours and trees, build a sun map from a PVGIS typical year with pvlib, check it against pvlib's Perez model and PVGIS, then estimate kWp and kWh per year per roof and rank the best roofs.
Run a viewshed analysis in Python on a real DEM: compute what one wind turbine can see with gdal.ViewshedGenerate, rebuild the same line-of-sight algorithm in numpy, correct for earth curvature and refraction, build a cumulative zone of theoretical visibility (ZTV) from 26 turbines, draw line-of-sight profiles, and measure how much trees and buildings in a LiDAR DSM shrink a bare-earth viewshed.
Stream free USGS 3DEP lidar of Washington, D.C., read and inspect a LAZ file with laspy, remove noise, grid the points into a 1 m DTM, DSM and canopy height model, and use the result to measure the Washington Monument to within 44 cm.