# mcda-suitability-analysis

> Claude/Codex skill by [@muend](https://omgskills.com/library/muend/index.md) · 35 stars · Updated 2026-10-17

Always invoke for spatial suitability, site selection, AHP, criteria weights, or weighted-overlay work, including audits of inconsistent pairwise judgments and requests for only a final map. Covers consistency, standardization, constraints, ranked surfaces, shortlists, and sensitivity. Route travel-time placement and location-allocation to network-accessibility-analysis.

Tags: agent-skills, ai, ai-agents, claude-code, codex, geoai, geospatial, gis, github-copilot, google-earth-engine, lidar, machine-learning, postgis, remote-sensing, spatial-analysis, spatial-data-science

## Install

```sh
git clone https://github.com/muend/geoai-skills /tmp/geoai-skills && ln -s /tmp/geoai-skills/skills/mcda-suitability-analysis ~/.claude/skills/mcda-suitability-analysis
```

## From README

MCDA & Suitability Analysis Purpose: produce suitability maps whose weights, scales, and assumptions are explicit, consistent, and stress-tested. A suitability map without a sensitivity analysis is an opinion with a legend. Workflow Structure: goal → criteria (factors) → constraints. Constraints are binary masks (legal exclusions, water bodies, slope \> threshold) applied at the END by multiplication; factors are continuous and weighted. Keep them apart — encoding a constraint as a heavily-weighted factor is a classic error that lets forbidden areas score "acceptable". Criteria layers: each factor as a raster on a COMMON grid (same CRS, extent, cell size, snap). Resample categorical layers with nearest, continuous with bilinear; document each. Standardization to a common suitability scale (0-1 or 0-255): Linear min-max for monotonic "more is better/worse". Fuzzy membership (sigmoid/linear with control points) when suitability saturates — justify control points from domain knowledge.

## Links

- HTML page: https://omgskills.com/library/muend/geoai-skills/skills/mcda-suitability-analysis/
- GitHub: https://github.com/muend/geoai-skills
- Author: [@muend](https://omgskills.com/library/muend/index.md)

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