/Deforestation_Analysis_with_Landsat8

Deforestation analysis with Landsat8

Primary LanguageJupyter Notebook

Medium LinkedIn OpenCV Python Computer Vision

License: MIT

Deforestation Analysis with Landsat 8

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Context

The Indigenous Land (IL) Mãe Maria, located in the Amazon Region, specifically in the southern part of the state of Pará, is home to three indigenous groups: Gavião Akrãtikatêjê, Gavião Kykatejê, and Gavião Parkatêjê, totaling 709 inhabitants in an area of 62,488 hectares. These communities face conflicts stemming from various activities, such as governmental entities' actions, dam and hydroelectric power plant construction, the establishment of waterways, highways, railways, port complexes/terminals, and airports, in addition to public policies and environmental legislation.

mae_maria

Project Objective

Our objective is to examine the consequences on vegetation cover in Indigenous Land Mãe Maria, using the Normalized Difference Vegetation Index (NDVI) to assess variations in vegetation between the years 2013 and 2023. To achieve this goal, we will construct a sequential process that involves collecting information from the distinct spectral bands of the Landsat 8 satellite.

Project Structure

.
├── Readme.md
├── Deforestation_Analysis_with_Landsat8.ipynb

Used Libraries

This project requires the following libraries:

  • OpenCV
  • Earthengine
  • Numpy
  • Matplotlib

Conclusion

The analysis of the Normalized Difference Vegetation Index (NDVI) on satellite images of Indigenous Land Mãe Maria revealed an increase of approximately 3.7905% in vegetation cover between 2013 and 2023. This is a positive sign of environmental recovery and preservation, despite the conflicts and pressures faced by indigenous communities in the region. v1

However, the ongoing need for environmental conservation and protection is emphasized to ensure a sustainable future for local communities and the ecosystem. The scientific approach employed underscores the importance of balancing human development and environmental preservation.

Contact

LinkedIn

Medium

e-mail: contato.jonysarcanjo@gmail.com

Useful Links

License

This project is licensed under the MIT License.