Location & Accessibility
Who can reach what — and where the next site should go.
Location analysis asks practical questions: which people does this clinic serve, who lives too far from a pharmacy, how much trade will a new store take, where should five depots go. Each answer depends on a model of catchment, distance and choice that is easy to run and easy to misread. These guides cover catchments and accessibility measures, gravity and Huff models, weighted site suitability, and p-median and coverage optimisation — measured on a real street network and a real population, with the edge effects and solver limits attached.
Start here
The cornerstone guide — the whole workflow end to end. Everything after it goes deeper into one part of it.
Step 1 Location Analysis Explained: Catchments, Accessibility and Site Selection location analysis gis explained Begin the path →The full path, in order
20 guides: the concepts underneath the work, then each task, then the errors that task produces. Work down, or jump to the step you need.
- Catchment Areas Explained: Buffers, Isochrones and Voronoi Compared catchment area gis 🧭 Concept
- How to Build Voronoi Service Areas Around Facilities in Python voronoi polygons python geopandas ⚙️ How-To
- How to Count the Population Within Reach of Each Facility population within distance of facility python ⚙️ How-To
- Accessibility Measures Explained: Nearest, Cumulative and Gravity spatial accessibility measures 🧭 Concept
- How to Measure Distance to the Nearest Facility for Every Home distance to nearest facility python ⚙️ How-To
- How to Measure Access to Services with the Two-Step Floating Catchment Method 2sfca python ⚙️ How-To
- Gravity and Huff Models Explained: Predicting Where People Go huff model explained 🧭 Concept
- How to Estimate Market Share with a Huff Model in Python huff model python ⚙️ How-To
- Site Suitability Explained: Constraints, Factors and Weights site suitability analysis gis 🧭 Concept
- How to Run a Weighted Site Suitability Analysis in Python suitability analysis python raster ⚙️ How-To
- Location-Allocation Explained: p-Median, Coverage and What Each Optimises location allocation p-median explained 🧭 Concept
- How to Choose Facility Locations with a p-Median Model in Python p-median python pulp ⚙️ How-To
- How to Maximise Coverage with a Limited Number of Sites maximal covering location problem python ⚙️ How-To
- How to Find the Areas Nobody Can Reach Within a Travel Time service area coverage gaps python ⚙️ How-To
- Fixing Voronoi Polygons That Extend Forever or Miss the Study Area voronoi polygons infinite python 🔧 Fix
- Fixing a Location-Allocation Model That Never Solves pulp p-median slow 🔧 Fix
- Fixing Accessibility Scores That Are Wrong Near the Study Area Edge accessibility edge effect 🔧 Fix
- Fixing a Gravity Model That Sends Everyone to the Biggest Store huff model distance decay parameter 🔧 Fix
- Fixing a Suitability Map That Comes Out All One Value or All NoData suitability raster overlay nodata 🔧 Fix
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