Environmental Spatial Data Analysis

3 credits · Graduate

Environmental Spatial Data Analysis (ESDA) provides an introduction on how to leverage and analyze geospatial data using Python. The topics that are covered include geospatial numerical arrays, geostatistics, digital cartography, classification, regression, spectral analysis, clustering, terrain analysis, bayesian statistics, and dimensionality reduction. Prerequisite: EGR 238L or graduate standing.