Creating 3D Maps using Python
summary
Creates textured 3D terrain models from open data using Python and common geospatial tools: downloads Landsat and local aerial tiles from AWS, reads rasters with rasterio, reprojects with GDAL, stitches into meshes exported as OBJ. Demonstrated results include 10 cm city imagery and 30–90 m global DEMs, processing terabytes in about three days on machines with ~192 GB RAM, producing both wireframe and textured outputs that load and render successfully.
AI-written summary · about
chapters (7)
- 0:00Start
- 10:56How Is It Done Reading Raster Data
- 15:57Elevation Data
- 18:04Create a 3d Model Creating 3d Models
- 18:21Wavefront Obj Format
- 19:36Create a 3d Object from Elevation Data
- 24:27How Long Does It Take To Calculate All the Polygons
related talks
23mDigital Earth Models
59mMake a great-looking 3D landscape visualization!
01h 30m3D geospatial data visualization using Python and Cesiumjs
29mGeospatial Analysis using Python
24mMaps of Imaginary Lands
30mMaps, Maps, Maps!
30mReal-time Map Imagery Manipulation with Python, Slippy Maps, Flask, and Pillow: Building Interactive
26mCartography with Python