The Decisive Influence of the Improved Remote Sensing Ecological Index on the Terrestrial Ecosystem in Typical Arid Areas of China

This study aims to assess the spatiotemporal changes in ecological environment quality (EEQ) in arid regions, using Xinjiang as a case study, from 2000 to 2023, with an improved remote sensing ecological index (IRSEI). Due to the complex ecology of arid regions, the traditional remote sensing ecological index (RSEI) has limitations in capturing ecological dynamics. To address this, we propose an enhanced IRSEI model that replaces normalization with standardization, improving robustness against outliers. Additionally, the kernel normalized difference vegetation index (kNDVI) and normalized difference salinity index (NDSI) are integrated to assess saline areas more effectively. The methodology includes time series analysis, spatial distribution analysis, and statistical evaluations using the difference method, coefficient of variation, and the Hurst index. Results show that the IRSEI more accurately reflects ecological dynamics than the RSEI. Temporal analysis reveals stable overall EEQ, with some areas improving. Spatially, the environment is generally better in the north and in mountainous regions than in the south and plains. Statistical evaluations suggest a positive trend in ecological changes, with improved areas surpassing degraded ones. This study contributes to the monitoring, protection, and management of arid region ecosystems, emphasizing the need for high-resolution data and further analysis.

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Publication Details

Journal
Land
Published
2024-12-12
DOI
https://doi.org/10.3390/land13122162
Citations
7
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
2.63
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article

The Decisive Influence of the Improved Remote Sensing Ecological Index on the Terrestrial Ecosystem in Typical Arid Areas of China

Hongqi Wu, Chao Xu, Mingjie Shi, Guo Long et al.
7 citations
Land
Remote Sensing and Land Use
2.63
article

The Decisive Influence of the Improved Remote Sensing Ecological Index on the Terrestrial Ecosystem in Typical Arid Areas of China

Hongqi Wu, Chao Xu, Mingjie Shi, Guo Long, Yanmin Fan
article en
7 citations

Abstract

This study aims to assess the spatiotemporal changes in ecological environment quality (EEQ) in arid regions, using Xinjiang as a case study, from 2000 to 2023, with an improved remote sensing ecological index (IRSEI). Due to the complex ecology of arid regions, the traditional remote sensing ecological index (RSEI) has limitations in capturing ecological dynamics. To address this, we propose an enhanced IRSEI model that replaces normalization with standardization, improving robustness against outliers. Additionally, the kernel normalized difference vegetation index (kNDVI) and normalized difference salinity index (NDSI) are integrated to assess saline areas more effectively. The methodology includes time series analysis, spatial distribution analysis, and statistical evaluations using the difference method, coefficient of variation, and the Hurst index. Results show that the IRSEI more accurately reflects ecological dynamics than the RSEI. Temporal analysis reveals stable overall EEQ, with some areas improving. Spatially, the environment is generally better in the north and in mountainous regions than in the south and plains. Statistical evaluations suggest a positive trend in ecological changes, with improved areas surpassing degraded ones. This study contributes to the monitoring, protection, and management of arid region ecosystems, emphasizing the need for high-resolution data and further analysis.

LandVol. 13(12)
Xinjiang Agricultural University (CN)
Life in Land
Openalex Percentile: Top 10%
Remote Sensing and Land Use
2.63
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