Analysis of Severity of Forest Fires Through Spectral Indices in Altiplanic Zones of Peru

M. H. Ysla Huaman, E. Romero Garcia, M. O. Bacilio Hilario, J. V. Cornejo Tueros

Research output: Chapter in Book/ReportChapterpeer-review

Abstract

Forest fires are one of the main problems that affect biodiversity and forest heterogeneity, which are caused by human or natural activities and even driven by climate change. The objective of this study was to analyze the severity of forest fires with the NBR index (Normalized Burn Ratio) in highland areas of Peru, and evaluate the vegetative recovery of forest species in the affected area with the NDVI index (Normalized Difference Vegetation Index). As a result, it was obtained that the type of vegetation in the affected area is the Andean Pajonal, the level of severity in the study area ranges from low to moderately high, with low severity being the predominant one, which occupies 57,562% of the study area. The NDVI evaluation of 2 weeks before, 2 weeks after and 3 months after the event show that there is a vegetative regeneration of the vegetation cover, two weeks after the event in the study area no healthy vegetation is found, but 3 months later the 4.321% is classified as healthy vegetation and only 0.002% of the study area has dead vegetation. Finally, the study shows that evaluation of environmental problems can be carried out through the use of remote sensing and that the information collected can help the corresponding political authorities take or design suitable strategies for this problem.

Original languageAmerican English
Title of host publicationSpringer Proceedings in Earth and Environmental Sciences
PublisherSpringer Nature
Pages83-94
Number of pages12
DOIs
StateIndexed - 2024

Publication series

NameSpringer Proceedings in Earth and Environmental Sciences
VolumePart F2160
ISSN (Print)2524-342X
ISSN (Electronic)2524-3438

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

  • Forest Fires
  • GIS and Remote Sensing
  • NBR
  • NDVI
  • Satellite Image

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