DSA SCI 8530 - Geospatial AI & Image Analysis
Graduate course, University of Missouri, Institute for Data Science and Informatics (IDSI), 2025
This course introduces remote sensing and geospatial analytics for data science applications. Students will learn to harness satellite imagery, aerial data, and cloud-based platforms like Google Earth Engine to analyze environmental patterns, land use changes, and atmospheric conditions. The course emphasizes practical applications of remote sensing for addressing real-world challenges in environmental monitoring, climate research, and public health. Through hands-on exercises, students will develop skills in image processing, temporal analysis, and spatial data visualization. Topics include satellite sensor characteristics, data acquisition, processing techniques, and information extraction methods. Students will work with multi-temporal datasets to examine air quality patterns, vegetation dynamics, and land cover changes. The course covers both technical implementation and ethical considerations of remote sensing data use. By the end of the course, students will be able to critically analyze, visualize, and interpret raster spatial data to support data-driven decision making in their research areas.