Hospital Site Suitability Analysis Using QGIS: A GIS-Based Decision Support Workflow

Introduction

Selecting an appropriate location for healthcare infrastructure is an important task in urban and regional planning. Geographic Information Systems (GIS) provide powerful spatial analysis tools that help planners identify suitable locations based on multiple criteria.

This project demonstrates a Hospital Suitability Analysis workflow developed using QGIS. The objective of the study is to identify potential locations for future hospital development using spatial datasets and weighted overlay analysis.

The workflow combines terrain analysis, accessibility analysis, population distribution, and healthcare coverage assessment to create a GIS-based decision support system.

Objective of the Study

The main objective of this project is to identify suitable locations for hospital establishment based on:

• Accessibility to road networks

• Population distribution

• Terrain suitability

• Existing hospital coverage

• The analysis helps planners identify areas that are both accessible and underserved.

Study Area

The analysis was conducted for a selected study area in Thane, India. The workflow can also be applied to other districts, cities, or regions with suitable spatial datasets.

Datasets Used

The following datasets were used in this analysis:

• Road Network : Accessibility analysis

• Population Raster : Demand analysis

• DEM (Digital Elevation Model) : Terrain and slope analysis

• Existing Hospital Locations : Healthcare coverage analysis

Data Sources

The spatial datasets were collected from publicly available sources:

• OpenStreetMap (Roads and Hospitals)

• WorldPop (Population Data)

• USGS EarthExplorer (DEM Data)

Methodology

The hospital suitability workflow consists of multiple spatial analysis steps.

1. Data Preparation

All datasets were imported into QGIS and clipped to the study area boundary. This ensures that analysis is limited only to the selected region.

2. Slope Generation from DEM

Slope was generated from the DEM using QGIS terrain analysis tools.

Flatter terrain was considered more suitable because steep areas can increase construction difficulty and reduce accessibility.

3. Road Accessibility Analysis

Distance-from-road analysis was performed using the buffer tool in QGIS.

Areas located closer to roads were considered highly suitable due to improved transportation and emergency accessibility.After buffering done the difference tool to find the area outside the buffer zone, and then merged both the data to use the tool Rasterize.

4. Population Analysis

Population raster data was used to identify densely populated regions.

Areas with higher population density were assigned higher suitability values because they represent greater healthcare demand.

5. Existing Hospital Distance Analysis

Distance analysis was also performed for existing hospitals.

This step helps identify underserved areas where healthcare facilities are limited, also after finding the undeserved areas, used Rasterize tool to covert the vector to raster to work on raster calculator for Weighted overlay.

6. Weighted Overlay Analysis

A weighted overlay model was used to combine all suitability criteria.

Different weights were assigned based on the importance of each factor.

Example weighting scheme:

• Weight

• Roads : 40%

• Population : 30%

• Slope : 10%

• Existing Hospitals : 20%

The weighted overlay generated the final hospital suitability map.

WebGIS Publishing

The final suitability map was published as an interactive WebGIS application using the QGIS2Web plugin.

This allows users and decision makers to: interact with the map, zoom into regions and visualize the suitability zones in the web.

Conclusion:

The final suitability map classified the study area into:

Highly suitable zones, Moderately suitable zones, Less suitable zones, Unsuitable zones

The analysis showed that areas with: good road accessibility, moderate terrain, higher population, and lower existing hospital coverage were identified as the most suitable locations for future hospital development.