Determining the Most Suitable Vegetation Index for Mapping of Desertification Intensity in Arid Lands of Sistan Using Sentinel Images

Document Type : Original Article

Authors

1 Assistant Professor, Higher education complex of Saravan, Saravan, Iran.

2 1. Assistant Professor, Higher education complex of Saravan, Saravan, Iran.

Abstract

Vegetation is one of the most important key components in arid regions for reducing of the effects of erosion and determining the severity of desertification. Decrease in vegetation leads to increase in surface albedo. Accessing and preparing desertification intensity map at the fastest possible time and at the lowest cost is one of the concerns of governments. In the present study, in order to identify the best vegetation index for preparing the desertification intensity map, MSIL-1C data of Sentinel 2 satellite in the arid region of Sistan has been used. For this purpose, the relationship between surface albedo and each of the different vegetation indices of the NDVI, RVI, DVI, PVI, SAVI and TSAVI were conducted. After determining the linear regression equation between the albedo and each of the mentioned indices, the relevant desertification intensity equation was calculated and the desertification intensity map of the studied area at 5 classes was prepared based on albedo and each of the mentioned indices. The results showed the strongest relationship in the study area was between albedo and NDVI, with a correlation coefficient of 0.63, and the lowest correlation of 0.37 was between the albedo and PVI indices. Based on the present study among the indices studied, the NDVI is the best for the preparation of maps of desertification intensity in the arid region of Sistan. Based on this index, 20.3% of the region was classified as severe and 32.9% of the region grouped into the moderate desertification class.

Keywords

Main Subjects

References

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Desert Management
Volume 10, Issue 1 - Serial Number 21
6 Articles
June 2022
Pages 1-14

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History

  • Receive Date: 10 February 2022
  • Revise Date: 18 April 2022
  • Accept Date: 23 April 2022

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