Asset Details
Do you wish to reserve the book?
Analysis of spatiotemporal evolution and driving factors of ecological environment quality in the Ili-Balkhash Lake Basin in Central Asia
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Analysis of spatiotemporal evolution and driving factors of ecological environment quality in the Ili-Balkhash Lake Basin in Central Asia
Do you wish to request the book?
Analysis of spatiotemporal evolution and driving factors of ecological environment quality in the Ili-Balkhash Lake Basin in Central Asia
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Analysis of spatiotemporal evolution and driving factors of ecological environment quality in the Ili-Balkhash Lake Basin in Central Asia
2025
Overview
The Central Asian area is faced with unprecedented challenges due to the fragility of its ecological environment and under the double pressure of global warming and intensified human activities. As a typical transboundary watershed in Central Asia, the ecological system quality of the Ili-Balkhash Lake Basin (IBLB) is of vital importance to the sustainable development of the whole region. In this study, we constructed the Remote Sensing Ecological Index (RSEI) for the IBLB (2000–2020) using the MODIS dataset on the Google Earth Engine platform and applied Sen’s slope and Mann–Kendall (Sen-MK) trend analysis methods to assess RSEI trends. Additionally, geographic detectors and geographically weighted regression models were used to identify and analyze the global and local factors influencing RSEI. The outcome of the study suggests that: (1) The ecological quality of the basin has generally improved, and the proportion of high quality and good areas has risen, but spatial heterogeneity is obvious, and the area around the lake shows a trend of degradation; (2) LST and NDVI were the main natural drivers, and LUI and AWUE were the key human drivers, with significant interactions among the factors; (3) The GWR model further reveals that LST is the main limiting factor of RSEI, and the two are negatively correlated, while there is significant spatial variability in the effects of NDVI, LUI and AWUE on RSEI, with both positive and negative effects. This study lends a scientific basis for revealing the ecological evolution of watersheds in arid zones. The methodological system it constructed can provide a reference for the ecological monitoring and governance practice of transboundary watersheds around the world.
Publisher
Nature Publishing Group UK,Nature Portfolio
