Geospatial Data Science: Explore, Analyze and Model Spatial, Temporal & Spatiotemporal Data

Catalog description

This course on Geospatial Data Science focuses on leveraging Data Science Analytical Tools and Open Source Software to explore, process, integrate, analyze, visualize and model geospatial data targeting diverse applications. Students will learn the basic tools in R based code for Exploratory Data Analysis, Data Integration, Visualization of Geospatial Data and Data Modeling. QGIS will also be introduced in this course as an additional open-source tool for data visualization and manipulation. Students will work on geospatial datasets (air quality, water contamination, soil analysis, rocks properties, energy, transportation, public health, agriculture etc) developing entire data science pipelines from data collection to modeling(spatial, temporal or spatiotemporal). Students will be expected to learn the navigation of R Studio and develop data science pipelines using geospatial data. We include Vertex AI integration with Markov Cluster that enables students to leverage LLMs as code assistants. Students will be expected to learn the above and develop a 10 week modeling project focused on the use of spatial modeling methods with R using data relevant to their specific discipline or interest. Resulting scripts will be placed in a git repository for use by other students as open source resources along with documentation demonstrating the reproducible spatial modeling science and analyses for these problems. Examples of graduate projects from previous classes include subsurface modeling (geology), air quality monitoring, effects of air temperature on health and mortality rates(environment/health), earthquake mapping (geophysics/civil engineering), soil stability modeling (civil engineering), aquifer characterization (hydrology), pollution/contaminant mapping (environmental studies/medicine), water quality, crop growth(agriculture), predicting health outcomes integration with socioeconomic and environmental data. Offered as DSCI 332 and DSCI 432 .