Modeling of Risk Zones for Forest Fires in High Andean Zones of Peru

Melania Haydee Ysla Huaman, Clisman Jhojan Ponce Ramos, Nicole Dayanna Zacarias Arauco, Jose Vladimir Cornejo Tueros

Producción científica: Libro o Capítulo del libro Contribución a la conferenciarevisión exhaustiva

Resumen

Forest fires are a serious environmental hazard within the forest ecosystem, which can be studied under satellite sensors and Geographic Information Systems (GIS). The objective of the study is to identify and model the degree of risk to forest fires and the risk zones in high Andean areas of Peru, specifically in the Province of Concepción. To achieve this objective, meteorological data, Aster GDEM vector and satellite information were used to develop thematic layers of vegetation cover in terms of combustibility, climate classification, proximity to population centers, slope and accessibility. The forest fire risk degree map was prepared by integrating the different parameters, such as vegetation cover, temperature, rainfall, slope, proximity to roads and population centers in the ArcGIS 10.8 environment. The forest fire risk degree map was classified into five categories as very low, low, medium, high and very high risk zones, according to their susceptibility to fire. It was obtained as a result that in a total area of 224,595.67 hectares, the degree of very low risk represents 0.06%, low risk represents 8.50%, medium risk represents 54.21%, high risk represents 33.42%, very high risk represents 3.81%, then the medium risk is the most representative in this high Andean zone. Finally, the study shows that satellite sensors and GIS are very good tools for modeling forest fire risk zones so that the knowledge obtained can be replicated in other departments with similar characteristics such as relief, thus contributing to the conservation of forest resources.

Idioma originalInglés estadounidense
Título de la publicación alojada2023 the 7th International Conference on Energy and Environmental Science - ICEES 2023
EditoresJianping Yang
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas65-78
-14
ISBN (versión impresa)9783031320675
DOI
EstadoIndizado - 2023
Evento2023 the 7th International Conference on Energy and Environmental Science - ICEES 2023 - Virtual, Online
Duración: 6 ene. 20238 ene. 2023

Serie de la publicación

NombreEnvironmental Science and Engineering
ISSN (versión impresa)1863-5520
ISSN (versión digital)1863-5539

Conferencia

Conferencia2023 the 7th International Conference on Energy and Environmental Science - ICEES 2023
CiudadVirtual, Online
Período6/01/238/01/23

Nota bibliográfica

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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