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volume 15 issue 18 pages 13881

Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau

Publication typeJournal Article
Publication date2023-09-18
scimago Q1
wos Q2
SJR0.688
CiteScore7.7
Impact factor3.3
ISSN20711050
Renewable Energy, Sustainability and the Environment
Building and Construction
Geography, Planning and Development
Management, Monitoring, Policy and Law
Abstract

Ecosystems in arid and semi-arid areas are delicate and prone to different erosive effects. Monitoring and evaluating the environmental ecological condition in such areas contribute to the governance and restoration of the ecosystem. Remote sensing ecological indices (RSEIs) are widely used as a method for environmental monitoring and have been extensively applied in various regions. This study selects the arid and semi-arid Loess Plateau as the research area, in response to existing research on ecological monitoring that predominantly uses vegetation indices as monitoring indicators for greenness factors. A fluorescence remote sensing ecological index (SRSEI) is constructed by using monthly synthesized sun-induced chlorophyll fluorescence data during the vegetation growth period as a new component for greenness and combining it with MODIS product data. The study generates the RSEI and SRSEI for the research area spanning from 2001 to 2021. The study compares and analyzes the differences between the two indices and explores the evolution patterns of the ecosystem quality in the Loess Plateau over a 21-year period. The results indicate consistent and positively correlated linear fitting trend changes in the RSEI and SRSEI for the research area between 2001 and 2021. The newly constructed ecological index exhibits a higher correlation with rainfall data, and it shows a more significant decrease in magnitude during drought occurrences, indicating a faster and stronger response of the new index to drought in the research area. The largest proportions are found in the research area’s regions with both substantial and minor improvements, pointing to an upward tendency in the Loess Plateau’s ecosystem development. The newly constructed environmental index can effectively evaluate the quality of the ecosystem in the research area.

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GOST |
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GOST Copy
Shi M. et al. Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau // Sustainability. 2023. Vol. 15. No. 18. p. 13881.
GOST all authors (up to 50) Copy
Shi M., Lin F., Jing Xia, Li B., Shi Y., Hu Y. Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau // Sustainability. 2023. Vol. 15. No. 18. p. 13881.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.3390/su151813881
UR - https://doi.org/10.3390/su151813881
TI - Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau
T2 - Sustainability
AU - Shi, Ming
AU - Lin, Fei
AU - Jing Xia
AU - Li, Bingyu
AU - Shi, Yang
AU - Hu, Yimin
PY - 2023
DA - 2023/09/18
PB - MDPI
SP - 13881
IS - 18
VL - 15
SN - 2071-1050
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2023_Shi,
author = {Ming Shi and Fei Lin and Jing Xia and Bingyu Li and Yang Shi and Yimin Hu},
title = {Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau},
journal = {Sustainability},
year = {2023},
volume = {15},
publisher = {MDPI},
month = {sep},
url = {https://doi.org/10.3390/su151813881},
number = {18},
pages = {13881},
doi = {10.3390/su151813881}
}
MLA
Cite this
MLA Copy
Shi, Ming, et al. “Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau.” Sustainability, vol. 15, no. 18, Sep. 2023, p. 13881. https://doi.org/10.3390/su151813881.