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author:

Xu, H.;, Duan, W.;, Deng, W.;, Lin, M. (Xu, H.;, Duan, W.;, Deng, W.;, Lin, M..) [1]

Indexed by:

Scopus

Abstract:

Recently, Jia et al. employed the index, modified remote sensing ecological index (MRSEI), to evaluate the ecological quality of the Qaidam Basin, China. The MRSEI made a modification to the previous remote sensing-based ecological index (RSEI), which is a frequently used remote sensing technique for evaluating regional ecological status. Based on the investigation of the ecological implications of the three principal components (PCs) derived from the principal component analysis (PCA) and the case study of the Qaidam Basin, this comment analyzed the rationality of the modification made to RSEI by MRSEI and compared MRSEI with RSEI. The analysis of the three PCs shows that the first principal component (PC1) has clear ecological implications, whereas the second principal component (PC2) and the third principal component (PC3) have not. Therefore, RSEI can only be constructed with PC1. However, MRSEI unreasonably added PC2 and PC3 into PC1 to construct the index. This resulted in the interference of each principal component. The addition also significantly reduced the weight of PC1 in the computation of MRSEI. The comparison results show that MRSEI does not improve RSEI, but causes the overestimation of the ecological quality of the Qaidam Basin. Therefore, the modification made by MRSEI is questionable and MRSEI is not recommended to be used for regional ecological quality evaluation. © 2022 by the authors.

Keyword:

MRSEI principal components analysis (PCA) RSEI

Community:

  • [ 1 ] [Xu H.]College of Environment and Safety Engineering, Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Xu H.]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou University, Fuzhou, 350116, China
  • [ 3 ] [Duan W.]College of Environment and Safety Engineering, Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 4 ] [Duan W.]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou University, Fuzhou, 350116, China
  • [ 5 ] [Deng W.]College of Environment and Safety Engineering, Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou, 350116, China
  • [ 6 ] [Deng W.]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou University, Fuzhou, 350116, China
  • [ 7 ] [Lin M.]Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China

Reprint 's Address:

  • [Xu, H.]College of Environment and Safety Engineering, China

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Related Keywords:

Source :

Remote Sensing

ISSN: 2072-4292

Year: 2022

Issue: 21

Volume: 14

5 . 0

JCR@2022

4 . 2 0 0

JCR@2023

ESI HC Threshold:51

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 23

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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