Land Use Change and Community Analysis Tools

Table of Contents

1. Introduction
2. Features
3. Repository Structure
4. Installation
5. Usage
   • Setup
   • Forests Analysis
   • Communities Analysis
6. Dependencies
7. Data Sources
8. Examples
   • Forests Analysis Example
   • Communities Analysis Example
9. Contributing
10. License
11. Acknowledgments

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Introduction

This repository contains tools for analyzing land use changes and community impacts using geographic information system (GIS) data. The primary focus is on forest analysis and community analysis, providing insights into land cover transitions, carbon stock variations, greenhouse gas emissions/removals, and socio-economic factors affecting communities.

The tools are designed to be user-friendly and well-documented, enabling researchers, policymakers, and stakeholders to perform complex spatial analyses with ease.

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Features

• Forests Analysis (forests_analysis.py):

  • Analyzes land use changes between two time periods.
  • Calculates carbon stock changes, greenhouse gas emissions, and removals.
  • Processes disturbances such as fire, insect damage, and harvest activities.
  • Generates detailed reports and summaries.

• Communities Analysis (communities_analysis.py):

  • Assesses the impact of land use changes on communities.
  • Evaluates socio-economic indicators.
  • Integrates demographic data with spatial analyses.
  • Provides visualizations and statistical summaries.

• Helper Functions (funcs.py):

  • Contains reusable functions for data conversion, raster processing, and statistical calculations.

• Lookup Dictionaries (lookups.py):

  • Provides mappings for NLCD categories, disturbance types, and carbon stock loss factors.

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Repository Structure

• forests_analysis.py: Main script for forest land use change analysis.
• communities_analysis.py: Main script for community impact analysis.
• funcs.py: Module containing helper functions used by the main scripts.
• lookups.py: Module containing lookup dictionaries for category mappings.
• data/: Directory containing input data files (rasters, shapefiles, CSVs).
• outputs/: Directory where output results and reports are saved.
• examples/: Directory with example data and usage examples.
• requirements.txt: File listing all Python dependencies.
• LICENSE: License information for the repository.

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Installation

Prerequisites

• Python 3.7 or higher
• ArcGIS Pro with Spatial Analyst Extension (for GIS processing)
• Git (optional, for cloning the repository)

Clone the Repository

git clone https://github.com/yourusername/your-repo-name.git
cd your-repo-name