Weighted Overlay

Weighted overlay is a spatial analysis method that merges several raster layers, each representing a different criterion, into a single output raster by multiplying each layer by its assigned weight and summing the results. Before combination, all input layers are reclassified to a common evaluation scale (typically 1-9 or 1-10), standardizing disparate units so they can be meaningfully compared.

The weighted overlay process involves three key steps. First, each input raster is reclassified so that its values are mapped to a common suitability scale, where higher values indicate greater suitability and lower values indicate less suitability. Second, each reclassified layer is assigned a percentage weight reflecting its relative importance, with all weights summing to 100 percent. Third, the weighted layers are summed cell by cell to produce an output raster where each cell value represents the overall suitability score for that location.

Site selectionSite SelectionSite selection is the analytical process of evaluating and choosing optimal physical locations for new stores, facili... analysts use weighted overlay to identify optimal locations for retail stores, warehouses, or public facilities by combining layers such as proximity to transportation, population density, and land cost. Environmental planners assess habitat suitability by overlaying vegetation, water availability, and terrain factors. Urban planners evaluate development potential by weighting infrastructure access, zoningZoningZoning is a land use planning tool that divides geographic areas into zones with specific permitted uses, building st... compatibility, and environmental constraints. Agricultural scientists combine soil quality, climate data, and water access layers to identify optimal growing areas.

The quality of weighted overlay results depends on thoughtful weight assignment and appropriate reclassificationReclassificationReclassification reassigns cell values in a raster dataset to new categories based on defined rules, simplifying comp.... Sensitivity analysis, which tests how changes in weights affect the output, is strongly recommended. Weighted overlay assumes compensatory decision-making: a low score on one criterion can be offset by high scores on others, which may not be appropriate for all decisions.