‹ back to GIS Glossary

Grid-Based Analysis

Definition

Grid‑based analysis uses tessellations—rasters, hex grids, H3 cells—to turn space into regularly sized units for computation and aggregation. Grids enable fast overlay, neighborhood statistics, and scalable tiling across large regions. By normalizing geometry, they simplify joins and allow multi‑resolution analyses that respect both local detail and regional patterns.

Application

Transportation models compute accessibility per cell, environmental teams map pollution gradients, retailers aggregate sales to privacy‑preserving grids, and researchers run cellular automata to simulate diffusion processes.

FAQ

Why pick hexagons over squares?

Hexes have more uniform neighbor distances and reduce orientation bias in some analyses. Squares align with rasters and are simpler to index; choose based on task and tooling.

How do you handle multi‑scale questions?

Build pyramids of grid resolutions and propagate metrics up or down with appropriate smoothing. Compare patterns across levels to test stability.

Do grids erase boundaries?

They abstract them, which can be a feature for privacy or fairness. When necessary, snap results back to administrative units via areal interpolation.

What about storage and performance?

Columnar formats and cell IDs (like H3 indexes) make big grid tables efficient. Add spatial keys and partitioning for distributed queries.