Skip to content

13wejay/LULC-Processor-Jupyter

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 

Repository files navigation

LULC Processor with Python (Jupyter Notebook)

Python Jupyter Notebook License

A Python script for processing Land Use and Land Cover (LULC) data using Jupyter Notebook. This tool is designed to analyze, visualize, and process LULC datasets efficiently.


Table of Contents

  1. Overview
  2. Features
  3. Installation
  4. Usage
  5. Data Requirements
  6. Output
  7. Contributing
  8. License
  9. Acknowledgments

Overview

This project provides a Python-based solution for processing Land Use and Land Cover (LULC) data. It is implemented as a Jupyter Notebook, making it easy to visualize and interact with the data. The script includes functionalities for data preprocessing, analysis, and visualization.


Features

  • Automated LULC Processing: Extracts LULC information from multiple raster files.
  • Batch Processing: Processes all LULC TIFF files in a folder automatically.
  • Data Preprocessing: Reads and cleans LULC data using shapefiles for region selection.
  • Visualization: Generates time-series plots and maps to display LULC changes.
  • Statistical Analysis: Calculates land cover changes, impervious surface values, and runoff coefficients.
  • Excel Output: Saves LULC analysis results in a structured Excel file.
  • Image Output: Produces summary plots showing year-by-year LULC trends.

Installation

To use this script, follow these steps:

  1. Clone the repository:
    git clone https://github.com/your-username/LULC-Processor-Python-Script.git
    
  2. Navigate to the project folder:
    cd LULC-Processor-Python-Script
    
  3. Create and activate a virtual environment (optional but recommended):
    python -m venv venv
    source venv/bin/activate  # On macOS/Linux
    venv\Scripts\activate     # On Windows
    
  4. Install the required dependencies:
    pip install -r requirements.txt
    

Usage

  1. Open Jupyter Notebook or Visual Studio Code Editor.
  2. Open LULC_Processor.ipynb in Jupyter.
  3. Run the cells step by step to:
    • Load and preprocess LULC data.
    • Perform analysis and extract statistics.
    • Visualize results.
    • Export Excel and image outputs.

Data Requirements

  1. LULC Raster Files: TIFF format (2001-2023) stored in a folder.
  2. Shapefile: Defines the study area for spatial selection.
  3. Projection: Ensure raster files have a common coordinate system.

Output

  1. Excel File (LULC_Analysis.xlsx)
  2. LULC Change Plot (LULC_Change.png): A multi-year comparison plot showing land use transitions.
  3. Maps: Color-coded maps highlighting LULC changes over time.

Contributing

Contributions are welcome! To contribute:

  1. Fork the repository.
  2. Create a new branch (feature-branch).
  3. Commit your changes and push.
  4. Open a Pull Request.

License

This project is licensed under the MIT License.


Acknowledgments

Special thanks to open-source geospatial libraries such as GeoPandas, Rasterio, NumPy, Matplotlib, for making this possible.


About

Jupyter Notebook Python Script for Analyzing LULC Changes

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published