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Volume 16
Issue 5
10.3390/f16050831
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Monitoring and Assessing Ecological Environmental Quality in Qianping Reservoir, Central China: A Remote Sensing Ecological Index (RSEI) Approach

by
Enkai Xu
1,†,
Guohang Zhang
1,†,
Hua Wang
1,
Mei Yang
1,
Hao Tian
1,
Ming Zhao
2,
Nalin Dong
1,*,
Congshi Li
3,
Yongge Hu
4,*,
Guohang Tian
1,5,
Yakai Lei
1,5,
Qian Chen
6,* and
Dianwei Wei
7
1
College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
2
National Forestry and Grassland Industry Development Planning Institute, Beijing 100000, China
3
Qianping Reservoir Construction Administration Bureau, Zhengzhou 450000, China
4
College of Tourism, Xinyang Normal University, Xinyang 464000, China
5
Henan International Joint Laboratory of Landscape Architecture, Henan Agricultural University, Zhengzhou 450002, China
6
Department of Food, Agricultural, and Biological Engineering, The Ohio State University, Columbus, OH 43210, USA
7
Henan Provincial Water Conservancy Engineering Bureau, Zhengzhou 450000, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2025, 16(5), 831; https://doi.org/10.3390/f16050831 (registering DOI)
Submission received: 8 April 2025 / Revised: 5 May 2025 / Accepted: 14 May 2025 / Published: 16 May 2025
(This article belongs to the Special Issue Forests as Nature-Based Solutions: Ecosystem Services, Multiple Benefits, and Trade-Offs)
Versions Notes

Abstract

The ecological impacts of dam and reservoir construction necessitate systematic environmental quality evaluation (EEQ) to reconcile ecological protection with sustainable development. To address this need, we integrated the Remote Sensing Ecological Index (RSEI)—a comprehensive metric synthesizing greenness, humidity, heat, and dryness—with a Land Use Change Ecological Response (LUCER) model to quantify the long-term EEQ dynamics in reservoir-affected regions. This study utilized Landsat and Sentinel-2 remote sensing imagery with a 10 m resolution from the years 2000, 2005, 2010, 2015, and 2020 to compute the RSEI for the Qianping Reservoir area in Henan Province, investigating the spatiotemporal variations in EEQ. Key findings reveal: (1) Temporal trend: EEQ showed fluctuating improvement, with RSEI projected to rise gradually until 2030. (2) Spatial pattern: A lower ecological quality in central reservoir zones contrasts with higher quality in surrounding mountainous areas. (3) Mechanism: The Land Use Change Ecological Response (LUCER) model reveals that the conversion of cultivated land to forestland and grassland drives significant EEQ improvements, counterbalancing the negative impacts of hydrological fragmentation caused by reservoir construction and urbanization. This study advances RSEI applications in reservoir ecology by establishing a coupled monitoring–prediction framework, providing actionable insights for dam-related ecological restoration and governance.
Keywords: reservoir; Landsat/Sentinel-2 imagery; long-term monitoring; spatiotemporal variation; ecological restoration reservoir; Landsat/Sentinel-2 imagery; long-term monitoring; spatiotemporal variation; ecological restoration

Share and Cite

MDPI and ACS Style

Xu, E.; Zhang, G.; Wang, H.; Yang, M.; Tian, H.; Zhao, M.; Dong, N.; Li, C.; Hu, Y.; Tian, G.; et al. Monitoring and Assessing Ecological Environmental Quality in Qianping Reservoir, Central China: A Remote Sensing Ecological Index (RSEI) Approach. Forests 2025, 16, 831. https://doi.org/10.3390/f16050831

AMA Style

Xu E, Zhang G, Wang H, Yang M, Tian H, Zhao M, Dong N, Li C, Hu Y, Tian G, et al. Monitoring and Assessing Ecological Environmental Quality in Qianping Reservoir, Central China: A Remote Sensing Ecological Index (RSEI) Approach. Forests. 2025; 16(5):831. https://doi.org/10.3390/f16050831

Chicago/Turabian Style

Xu, Enkai, Guohang Zhang, Hua Wang, Mei Yang, Hao Tian, Ming Zhao, Nalin Dong, Congshi Li, Yongge Hu, Guohang Tian, and et al. 2025. "Monitoring and Assessing Ecological Environmental Quality in Qianping Reservoir, Central China: A Remote Sensing Ecological Index (RSEI) Approach" Forests 16, no. 5: 831. https://doi.org/10.3390/f16050831

APA Style

Xu, E., Zhang, G., Wang, H., Yang, M., Tian, H., Zhao, M., Dong, N., Li, C., Hu, Y., Tian, G., Lei, Y., Chen, Q., & Wei, D. (2025). Monitoring and Assessing Ecological Environmental Quality in Qianping Reservoir, Central China: A Remote Sensing Ecological Index (RSEI) Approach. Forests, 16(5), 831. https://doi.org/10.3390/f16050831

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