Sensitivity of Spectral Indices on Burned Area Detection using Landsat Time Series in Savannas of Southern Burkina Faso

Jinxiu Liu, Eduardo Maeda, Wang Du, Janne Heiskanen

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Accurate and efficient burned area mapping and monitoring are fundamental for environmental applications. Studies using Landsat time series for burned area mapping are increasing and popular. However, the performance of burned area mapping with different spectral indices and Landsat time series has not been evaluated and compared. This study compares eleven spectral indices for burned area detection in the savanna area of southern Burkina Faso using Landsat data ranging from October 2000 to April 2016. The same reference data are adopted to assess the performance of different spectral indices. The results indicate that Burned Area Index (BAI) is the most accurate index in burned area detection using our method based on harmonic model fitting and breakpoint identification. Among those tested, fire-related indices are more accurate than vegetation indices, and Char Soil Index (CSI) performed worst. Furthermore, we evaluate whether combining several different spectral indices can improve the accuracy of burned area detection. According to the results, only minor improvements in accuracy can be attained in the studied environment, and the performance depended on the number of selected spectral indices.

Original languageEnglish
Article number2492
JournalRemote Sensing
Volume13
Issue number13
Number of pages12
ISSN2072-4292
DOIs
Publication statusPublished - Jul 2021
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 1171 Geosciences
  • Burned area
  • Spectral indices
  • Landsat time series
  • Savanna
  • burned area
  • spectral indices
  • Landsat time series
  • savanna
  • FIRE SEVERITY
  • VEGETATION
  • ECOSYSTEMS
  • IMAGERY
  • COVER
  • RED

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