Spatial Data Management and Analysis

This unit develops skills for ingesting, organizing, querying, and analyzing spatial data across raster, vector, and tabular systems. Students learn database and data‑import workflows, surface and network analysis, overlay/map algebra, geocoding, basic scripting, and tool selection (QGIS, ArcGIS Online, 3D/AR) to prepare datasets for applied GIS projects.

Learning Objectives

• Analyze how different data structures (raster, vector, tabular, object-oriented/NoSQL) affect data retrieval and query performance by performing attribute, spatial, and raster searches and documenting results
• Apply database management and data‑ingestion workflows to import, geocode, reproject, and prepare spatial datasets with appropriate metadata using DBMS and file-based systems
• Demonstrate proficiency in spatial analysis techniques by performing surface (DEM) analyses, watershed delineation, impedance/network modeling, overlay operations, map algebra, and summary statistics to answer geographic questions
• Evaluate and implement efficient GIS workflows by scripting repetitive tasks, selecting between desktop and cloud tools (QGIS, ArcGIS Online, 3D/AR), and choosing data sources based on project requirements for scale, accuracy, and accessibility