Zipeng Zhang

Dr. Zipeng Zhang

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 June 2023 in Geoderma
Verified
Journal Article
Open access
Zipeng ZhangZipeng Zhang
Zipeng Zhang
JDJianli Ding
Jianli Ding
CZChuanmei Zhu
Chuanmei Zhu
JWJinjie Wang
Jinjie Wang
Xiangyu GeXiangyu Ge
Xiangyu Ge
JWJingzhe Wang
Jingzhe Wang

24 July 2022 in Land Degradation & Development
Verified
Journal Article
Closed access
Zipeng ZhangZipeng Zhang
Zipeng Zhang
JDJianLi Ding
JianLi Ding
CZChuanMei Zhu
ChuanMei Zhu
HSHaobo Shi
Haobo Shi
XCXiangYue Chen
XiangYue Chen
JWJingZhe Wang
JingZhe Wang

16 June 2023 in Land Degradation & Development
Verified
Journal Article
Closed access
CZChuanmei Zhu
Chuanmei Zhu
JDJianli Ding
Jianli Ding
Zipeng ZhangZipeng Zhang
Zipeng Zhang
JWJinjie Wang
Jinjie Wang
XCXiangyue Chen
Xiangyue Chen
JWJingzhe Wang
Jingzhe Wang

19 January 2024 in Land
Verified
Journal Article
Open access
PDF file
JLJunjie Li
Junjie Li
XPXiangbin Peng
Xiangbin Peng
RTRuomei Tang
Ruomei Tang
JGJing Geng
Jing Geng
Zipeng ZhangZipeng Zhang
Zipeng Zhang
TBTingting Bai
Tingting Bai
Since the beginning of the new century, there has been a notable enhancement in China’s ecological environment quality (EEQ), a development occurring in tandem with climate change and the extensive ecological restoration projects (ERPs) undertaken in the country. However, comprehensive insights into the spatial and temporal characteristics of China’s EEQ, and its responses to both climate change and human activities over the past two decades, have remained largely elusive. In this study, we harnessed a combination of multi-source remote-sensing data and reanalysis data. We employed Theil–Sen median trend analysis, multivariate regression residual analysis, and the Hurst index to examine the impacts and changing patterns of climatic factors and human activities on China’s EEQ during the past two decades. Furthermore, we endeavored to forecast the future trajectory of EEQ. Our findings underscore a significant improvement in EEQ across most regions of China between 2002 and 2019, with the most pronounced enhancements observed in the Loess Plateau, Northeast China, and South China. This transformation can be attributed to the combined influence of climatic factors and human activities, which jointly accounted for alterations in EEQ across 78.25% of China’s geographical expanse. Human activities (HA) contributed 3.93% to these changes, while climatic factors (CC) contributed 17.79%. Additionally, our projections indicate that EEQ is poised to continue improving in 56.70% of China’s territory in the foreseeable future. However, the Loess Plateau, Tarim Basin, and Inner Mongolia Plateau are anticipated to experience a declining trend. Consequently, within the context of global climate change, the judicious management of human activities emerges as a critical imperative for maintaining EEQ in China. This study, bridging existing gaps in the literature, furnishes a scientific foundation for comprehending the evolving dynamics of EEQ in China and informs the optimization of management policies in this domain.

28 July 2025 in Geography and Sustainability
Verified
Journal Article
Open access
Zipeng ZhangZipeng Zhang
Zipeng Zhang
JDJianli Ding
Jianli Ding
LLLiangyi Li
Liangyi Li
JCJinhua Cao
Jinhua Cao
KWKeqiang Wang
Keqiang Wang
JWJingzhe Wang
Jingzhe Wang

23 May 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
Yue LiuYue Liu
Yue Liu
Jinjie WangJinjie Wang
Jinjie Wang
Jianli DingJianli Ding
Jianli Ding
Zipeng ZhangZipeng Zhang
Zipeng Zhang
ZLZhihong Liu
Zhihong Liu
LSLiya Shi
Liya Shi
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.
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