👉 Geographic Information Systems (GIS) rely heavily on mathematical techniques to analyze, visualize, and manage spatial data. At its core, GIS uses principles from geometry, trigonometry, and algebra to represent and manipulate geographic features like points, lines, and polygons. For instance, spatial analysis often involves calculating distances and areas using the Haversine formula for great-circle distances on a sphere, or employing the Euclidean distance formula for flat planes. GIS also utilizes coordinate systems (like latitude/longitude or UTM) and projections to accurately map the Earth's surface onto flat maps, preserving spatial relationships as much as possible. More advanced GIS operations, such as network analysis for routing or spatial statistics for pattern detection, require sophisticated mathematical models like graph theory and probability distributions. Overall, GIS math bridges the gap between abstract spatial data and practical applications in fields like urban planning, environmental science, and logistics.
