Comprehensive Geospatial Analysis Tool

This repository provides a complete Python-based toolkit for performing two types of geospatial analysis:

1. Tourism Hotspot Analysis
2. Service Gap Analysis

It works with spatial vector datasets such as .shp, .geojson, .gpkg, .json, .kml, and .gml. The toolkit uses clustering algorithms (KMeans and DBSCAN), spatial buffers, and raster heatmaps to extract geographic patterns and service coverage insights.

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Features

Tourism Hotspot Analysis

• Clusters tourism-related POIs using KMeans.
• Creates hotspot polygons via buffer and convex hull.
• Generates a raster heatmap using KDE.
• Outputs:
  • clustered_points.geojson
  • tourism_hotspots.geojson
  • tourism_heatmap.tiff

Service Gap Analysis

• Clusters service POIs (e.g., hospitals, schools) using DBSCAN.
• Buffers clusters to model service areas.
• Detects underserved regions within administrative boundaries.
• Outputs:
  • poi_clusters.geojson
  • service_areas.geojson
  • well_served_areas.geojson
  • underserved_areas.geojson

Input Handling

• Scans data/ directory for spatial files.
• Keyword-based auto detection for POIs and boundary layers.

Modular Design

• Separated logic for each analysis type.
• Common utilities for file operations and CLI orchestration.

Installation

1. Clone the repository

git clone https://github.com/akash-suresh-kumar/Geospatial-Analysis.git
cd geospatial-analysis

2. Set up virtual environment

python -m venv iudx
source ./iudx/Scripts/activate  # On Windows

3. Install dependencies

pip install -r requirements.txt

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Output Structure

All output files are saved to the Output/ directory under analysis-specific subfolders.

Tourism Hotspot Outputs

• clustered_points.geojson
• tourism_hotspots.geojson
• tourism_heatmap.tiff
• Location: Outputs/tourism_analysis/

Service Gap Analysis Outputs

• poi_clusters.geojson
• service_areas.geojson
• well_served_areas.geojson
• underserved_areas.geojson
• Location: Outputs/service_gap_analysis/