Satellite Image Analysis for Deforestation

Python notebook for analyzing deforestation in Cancun, Mexico using OpenCV and satellite imagery from Google Earth Engine, designed for impactful environmental monitoring.

Photo by Renaldo Matamoro on Upsplash

Overview

This project employs advanced computer vision techniques to analyze deforestation in Cancun, Mexico using satellite images sourced from Google Earth Engine. By applying color segmentation with OpenCV, the project identifies changes in forestation over several years, providing insights into environmental impacts.

Project Purpose

Deforestation poses significant challenges to environmental stability, affecting biodiversity, climate, and local communities. This project not only showcases a technical solution to monitor these changes but also serves as a call to action. It provides stakeholders, researchers, and policymakers with tools to visualize and quantify environmental changes, empowering informed decision-making and fostering a sustainable future.

How It Works

The project uses Python and OpenCV to process satellite images and apply color segmentation to identify forested areas. Steps include:

1. Loading and displaying multi-temporal satellite images.
2. Applying color segmentation to isolate greenery.
3. Analyzing changes in forest cover over different years to detect deforestation. The Jupyter notebook included in this repository guides you through each step with clear explanations and visual outputs.

Requirements

• Python 3.7+
• OpenCV
• Matplotlib
• Numpy

Install these packages using pip:

pip install opencv-python matplotlib ipython numpy

For the Future

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

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