https://github.com/13wejay/lulc-processor-jupyter
Jupyter Notebook Python Script for Analyzing LULC Changes
https://github.com/13wejay/lulc-processor-jupyter
earth-engine lulc-changes lulc-classification python-script remote-sensing
Last synced: 7 months ago
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Jupyter Notebook Python Script for Analyzing LULC Changes
- Host: GitHub
- URL: https://github.com/13wejay/lulc-processor-jupyter
- Owner: 13wejay
- License: mit
- Created: 2025-02-25T14:00:19.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-03-17T06:55:44.000Z (7 months ago)
- Last Synced: 2025-03-17T07:40:30.707Z (7 months ago)
- Topics: earth-engine, lulc-changes, lulc-classification, python-script, remote-sensing
- Language: Jupyter Notebook
- Homepage:
- Size: 9.77 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LULC Processor with Python (Jupyter Notebook)
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](#overview)
2. [Features](#features)
3. [Installation](#installation)
4. [Usage](#usage)
5. [Data Requirements](#data-requirements)
6. [Output](#output)
7. [Contributing](#contributing)
8. [License](#license)
9. [Acknowledgments](#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:**
```bash
git clone https://github.com/your-username/LULC-Processor-Python-Script.git
2. **Navigate to the project folder:**
```bash
cd LULC-Processor-Python-Script
3. **Create and activate a virtual environment (optional but recommended):**
```bash
python -m venv venv
source venv/bin/activate # On macOS/Linux
venv\Scripts\activate # On Windows
4. **Install the required dependencies:**
```bash
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.
---