Description
Error and uncertainty are a fact of life, however they often go unaccounted for in geospatial models that rely on Digital Elevation Models (DEMs). Our work focuses on mitigating that problem as it relates to SRTM and ASTER GDEM. This is a discussion about how Python works within a broader system that enables researchers to work around this uncertainty without being geostatistics experts. The talk will cover how we use Python for advanced raster processing (including a vertical datum correction), calculating error statistics, and interacting with our spatial database as well as what we're doing with the end product, including a live demo.