Next Article in Journal
On the Potential of Bayesian Neural Networks for Estimating Chlorophyll-a Concentration from Satellite Data
Previous Article in Journal
Spectral Angle Mapper Application Using Sentinel-2 in Coastal Placer Deposits in Vigo Estuary, Northwest Spain
Previous Article in Special Issue
Satellite-Observed Arid Vegetation Greening and Terrestrial Water Storage Decline in the Hexi Corridor, Northwest China
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Remote Sensing
Volume 17
Issue 11
10.3390/rs17111825
remotesensing-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Dynamic Monitoring of Ecological Environmental Quality in Arid and Semi-Arid Regions: Disparities Among Central Asian Countries and Analysis of Key Driving Factors

by
Yue Liu
1,
Jinjie Wang
1,*,
Jianli Ding
1,2,
Zipeng Zhang
1,
Zhihong Liu
1,
Zihan Zhang
1,
Jinming Zhang
1 and
Liya Shi
1
1
College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
2
Xinjiang Institute of Technology, Aksu 843000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(11), 1825; https://doi.org/10.3390/rs17111825
Submission received: 25 March 2025 / Revised: 27 April 2025 / Accepted: 22 May 2025 / Published: 23 May 2025
(This article belongs to the Special Issue Ecosystem Protection in Arid and Semi-Arid Regions Supported by Multi-Source Remote Sensing Data)
Versions Notes

Abstract

The ecological environment of arid and semi-arid regions (ASARs) faces significant challenges, highlighting the need for a robust indicator system to assess ecological environmental quality (EEQ) and sustainability. This study investigates Central Asia (CA) using the Google Earth Engine (GEE) to develop a new remote sensing-based ecological index (ASAEI), assessing EEQ from 2000 to 2022 using the CatBoost–SHAP model. The results reveal a distinct spatial pattern in the ASAEI: the southwestern and southeastern regions face more severe ecological challenges, while the northern and central-southern areas exhibit better ecological conditions. The ASAEI exhibits a strong spatial autocorrelation, with high-value clusters in the northern and central-southern regions, where vegetation is dense, and low-value clusters in the southwestern and southeastern desert and Gobi regions. Over time, we observed that ecological degradation shifts from west to east. Overall, ecological restoration in CA exceeds the extent of degradation. Notably, Kazakhstan is primarily experiencing degradation, while other subregions predominantly show signs of restoration. Our analysis indicates that climate conditions and land use types are the primary factors influencing changes in the ASAEI. Furthermore, we project that 54.5% of the CA region will exhibit an improved EEQ, highlighting the need for restoration efforts in the western areas. The ASAEI offers a novel perspective and methodology for assessing EEQ in ASARs, with significant scientific implications.
Keywords: ecological environmental quality; arid and semi-arid regions; remote sensing; ecological index; machine learning; driving factors; climate impact ecological environmental quality; arid and semi-arid regions; remote sensing; ecological index; machine learning; driving factors; climate impact

Share and Cite

MDPI and ACS Style

Liu, Y.; Wang, J.; Ding, J.; Zhang, Z.; Liu, Z.; Zhang, Z.; Zhang, J.; Shi, L. Dynamic Monitoring of Ecological Environmental Quality in Arid and Semi-Arid Regions: Disparities Among Central Asian Countries and Analysis of Key Driving Factors. Remote Sens. 2025, 17, 1825. https://doi.org/10.3390/rs17111825

AMA Style

Liu Y, Wang J, Ding J, Zhang Z, Liu Z, Zhang Z, Zhang J, Shi L. Dynamic Monitoring of Ecological Environmental Quality in Arid and Semi-Arid Regions: Disparities Among Central Asian Countries and Analysis of Key Driving Factors. Remote Sensing. 2025; 17(11):1825. https://doi.org/10.3390/rs17111825

Chicago/Turabian Style

Liu, Yue, Jinjie Wang, Jianli Ding, Zipeng Zhang, Zhihong Liu, Zihan Zhang, Jinming Zhang, and Liya Shi. 2025. "Dynamic Monitoring of Ecological Environmental Quality in Arid and Semi-Arid Regions: Disparities Among Central Asian Countries and Analysis of Key Driving Factors" Remote Sensing 17, no. 11: 1825. https://doi.org/10.3390/rs17111825

APA Style

Liu, Y., Wang, J., Ding, J., Zhang, Z., Liu, Z., Zhang, Z., Zhang, J., & Shi, L. (2025). Dynamic Monitoring of Ecological Environmental Quality in Arid and Semi-Arid Regions: Disparities Among Central Asian Countries and Analysis of Key Driving Factors. Remote Sensing, 17(11), 1825. https://doi.org/10.3390/rs17111825

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop