Relationship between Vegetation Index and Forest Surface Fuel Load in UAV Multispectral Remote Sensing

Yufei Zhou, Zhenshi Wang, Yingxia Zhong, Qiang Li, Shujing Wei, Sisheng Luo, Zepeng Wu, Ruikun Dai and Xiaochuan Li

Asian Agricultural Research, 2022, vol. 14, issue 10

Abstract: [Objectives] To explore the relationship between vegetation index and forest surface fuel load. [Methods] UAV multispectral remote sensing was used to obtain large-scale forest images and obtain structural data of forest surface fuel load. This experimental area was located in Gaoming District, Foshan City, Guangdong Province. The average surface fuel load of the experimental area was as high as 39.33 t/ha, and the forest surface fuel load of Pinus elliottii was the highest. [Results] The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) had moderately strong correlation with the forest surface fuel load. The regression model of NDVI (X) and forest surface fuel load (Y) was established: Y = -5.935 4X + 8.466 3, and the regression model of EVI (X) and forest surface fuel load (Y) was established: Y = -5.848 5X + 6.727 1. The study also found that the linear relationship between NDVI and surface fuel load was more significant. [Conclusions] Both NDVI and EVI have moderately strong correlations with forest surface fuel load. NDVI is moderately or strongly correlated with the surface fuel load of Pinus massoniana forest, shrub grassland, broad-leaf forest and bamboo forest, while EVI is only strongly correlated with surface fuel load of broad-leaf forest and bamboo forest. It is expected that the relationship between other vegetation indices and forest surface fuel load can be obtained by the method in this study, so as to find a more universal vegetation index for calculating surface fuel load.

Keywords: Agribusiness (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:ags:asagre:338264

DOI: 10.22004/ag.econ.338264

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