Costa Rica’s dry tropical forest preservation: Integration of satellite technologies and terrestrial sensor nodes to early forest fire detection

Paper number

GLOC-2023,T,IP,x75194

Author

Mr. Francisco Eduardo Salazar Lopez, University of Costa Rica, Costa Rica

Coauthor

Mr. Axel Batista Murillo, University of Costa Rica, Costa Rica

Coauthor

Mr. Bryan Martínez, Universidad de Costa Rica, Costa Rica

Coauthor

Ms. Priscilla H. Góchez, Universidad de Costa Rica, Costa Rica

Coauthor

Ms. Fabiola Quirós, Universidad de Costa Rica, Costa Rica

Coauthor

Ms. Camila Barrios, Universidad de Costa Rica, Costa Rica

Coauthor

Ms. Natalia Martinez, Universidad de Costa Rica, Costa Rica

Coauthor

Mr. Braulio Soto, Universidad de Costa Rica, Costa Rica

Coauthor

Mr. Anthony Gómez Ureña, Universidad de Costa Rica, Costa Rica

Coauthor

Mr. Isaac Rojas Vasquez, University of Costa Rica, Costa Rica

Year

2023

Abstract

By protecting approximately 25.5\% of its terrestrial and insular area, Costa Rica demonstrates a strong commitment to protecting the environment. However, one of the most affected areas during the dry season is the tropical dry forest, which is prone to forest fires caused by natural and anthropogenic phenomena, enhanced by climate change. The tropical dry forest of Latin America and the Caribbean, once uninterrupted from Mexico to Panama, is now under threat given that its size has shrunk to 10\% of its original extension. This article presents a proposal developed by Universidad de Costa Rica in conjunction with public and private organizations, communities, and Guanacaste Conservation Area (ACG, by its acronym in Spanish) for the development and implementation of an early forest fire detection system.
This system will be based on the analysis of satellite images to identify areas at risk of fires, and a network of remote sensor nodes that will be deployed, with the ability to measure temperature, humidity, and smoke data. These sensor nodes will be responsive to various variables that could potentially cause ignition or indicate the presence of a fire. These devices will be able to transmit real-time data and will be equipped with cameras to gather visual information about the fire. In addition, an autonomous UAV capable of scanning the terrain and the forest will be implemented to corroborate the information provided by the nodes. Finally, an awareness plan is proposed, including technology training for surrounding communities, to integrate them into the project and support the conservation of the tropical dry forest. This project aims to reduce the negative impact of fires on the conservation areas and improve the response times of forest fire brigades.

Abstract document

GLOC-2023,T,IP,x75194.brief.pdf

Manuscript document

(absent)