GeoTIFF-Based Deforestation Detection

A Jupyter notebook for detecting deforestation using GeoTIFF satellite images from Google Earth Engine and NDVI analysis with OpenCV.

Source: Google Earth Engine

Overview

This project harnesses the power of GeoTIFF satellite images to detect deforestation. Using Python and OpenCV, along with GDAL for image processing, this notebook delves into the analysis of land use changes over time. The focus is on calculating the Normalized Difference Vegetation Index (NDVI) to assess vegetation cover and detect deforestation areas.

Why This Project Matters

Deforestation is a critical environmental issue that impacts climate change, wildlife habitats, and biodiversity. By providing a method to analyze and monitor deforestation through satellite images, this project aids in environmental protection efforts. It aims to equip conservationists, researchers, and policymakers with the tools necessary for informed decision-making towards sustainable land management.

Features

• GeoTIFF Image Processing: Learn to handle GeoTIFF files using GDAL.
• NDVI Calculation: Utilize satellite imagery to compute NDVI and assess vegetation health.
• Temporal Analysis: Compare changes in vegetation over different years to pinpoint deforestation.

Environmental Impact

This project is more than just code—it's a tool aimed at protecting our natural world. By providing open access to environmental monitoring tools, we empower individuals and organizations around the globe to take actionable steps towards sustainability.

Requirements

• Python 3.7+
• OpenCV
• Matplotlib
• GDAL

Install these packages using pip:

pip install opencv-python matplotlib ipython gdal

For the Future

If you want to add more, Please don't hesitate to open a pull request.

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