https://github.com/kev-1729/deforestation_detection

Este proyecto detecta la deforestación mediante análisis de imágenes satelitales, aplicando Visión por Computadora y Machine Learning. Utiliza Python, TensorFlow, OpenCV y técnicas de procesamiento de imágenes para la identificación de áreas afectadas.
https://github.com/kev-1729/deforestation_detection

machine-learning opencv tensorflow

Last synced: about 2 months ago
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Este proyecto detecta la deforestación mediante análisis de imágenes satelitales, aplicando Visión por Computadora y Machine Learning. Utiliza Python, TensorFlow, OpenCV y técnicas de procesamiento de imágenes para la identificación de áreas afectadas.

• Host: GitHub
• URL: https://github.com/kev-1729/deforestation_detection
• Owner: Kev-1729
• License: mit
• Created: 2024-08-25T00:16:27.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2025-03-05T02:01:18.000Z (over 1 year ago)
• Last Synced: 2025-03-05T03:18:08.825Z (over 1 year ago)
• Topics: machine-learning, opencv, tensorflow
• Language: Python
• Homepage:
• Size: 18.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Calculation of Deforested Areas Using Satellite Image Segmentation  

This project implements a system to detect deforested areas in satellite images using image processing and segmentation techniques. The main goal is to automate image analysis to calculate the amount of land affected by deforestation.  

## Project Benefits  

- **Automated Monitoring**: Automates the detection of deforested areas in large satellite image datasets.  

- **Efficient Analysis**: Enables efficient analysis of affected regions, saving time compared to manual methods.  

- **Informative Visualization**: Provides clear and detailed visualizations of deforested areas, facilitating study and decision-making in conservation and resource management projects.  

- **Practical Application**: Useful for environmental organizations, governments, and research projects that need to monitor the impact of deforestation over time.

  

## Project Explanation  

This project is based on advanced image segmentation techniques specifically designed to detect and measure deforested areas. Using satellite images, the system identifies regions affected by deforestation and calculates the impacted area in square kilometers. The main steps include:  

- **Image Preprocessing**: Satellite images are adjusted and normalized to optimize the accuracy of the segmentation model.  

- **Segmentation**: Using an image processing-based segmentation approach, deforested areas are identified within the satellite image.  

- **Area Calculation**: Once affected areas are segmented, the total area is calculated using methods based on the satellite image scale.  

- The system can process multiple images automatically, enabling continuous monitoring of large forested areas and their changes over time.  

## Results  

The system generates the following outputs:  

- **Processed Images**: Satellite images with deforested areas visually highlighted for easier interpretation.  

- **Affected Area Calculation**: Provides an accurate calculation of the total deforested area in square kilometers, crucial for environmental studies and policy implementation.