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Article

Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function

by
Zongmin Wang
1,
Longfei Hou
1,
Haibo Yang
1,*,
Yong Zhao
2,
Fei Chen
3,
Qizhao Li
1 and
Zheng Duan
4
1
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
2
China Institute of Water Resources and Hydropower Research, Beijing 100038, China
3
General Institute of Water Conservancy and Hydropower Planning and Design, Ministry of Water Resources of China, Beijing 100120, China
4
Department of Physical Geography and Ecosystem Science, Lund University, S-22362 Lund, Sweden
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(19), 3580; https://doi.org/10.3390/rs16193580
Submission received: 19 August 2024 / Revised: 21 September 2024 / Accepted: 23 September 2024 / Published: 26 September 2024

Abstract

The traditional remote sensing ecological index (RSEI), based on principal component analysis (PCA) to integrate four evaluation indexes: greenness (NDVI), humidity (WET), dryness (NDBSI), and heat (LST), is insufficient to comprehensively consider the influence of each eco-environment evaluation index on eco-environment quality (EEQ). In this research, a new comprehensive remote sensing ecological index (CRSEI) based on the quaternion Copula function is proposed to comprehensively characterize EEQ responded by integrating four eco-environment evaluation indexes. Additionally, the spatiotemporal variation of EEQ in Henan Province is evaluated using monthly CRSEI data from 2001 to 2020. The results show that: (1) The applicability and monitoring accuracy of CRSEI are better than that of RSEI, which can be used to assess the EEQ. (2) The EEQ of Henan Province declined between 2001 and 2010 but significantly improved and rebounded from 2011 to 2020. During this period, CRSEI values were higher in West and South Henan and lowest in central Henan, with West Henan consistently showing the highest values across all seasons. (3) The EEQ in Henan Province exhibited a tendency of deterioration from the central cities outward, followed by improvement from the outer areas back towards the central cities. In 2010, regions with poor EEQ made up 68.3% of the total area, whereas by 2020, regions with excellent EEQ accounted for 74% of the total area. (4) The EEQ was significantly negatively correlated with human activities, while it was positively correlated with precipitation. The research provides a reference and guidance for the scientific assessment of the regional eco-environment.
Keywords: remote sensing ecological index; quaternion copula function; spatial–temporal changes; eco-environment quality remote sensing ecological index; quaternion copula function; spatial–temporal changes; eco-environment quality

Share and Cite

MDPI and ACS Style

Wang, Z.; Hou, L.; Yang, H.; Zhao, Y.; Chen, F.; Li, Q.; Duan, Z. Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function. Remote Sens. 2024, 16, 3580. https://doi.org/10.3390/rs16193580

AMA Style

Wang Z, Hou L, Yang H, Zhao Y, Chen F, Li Q, Duan Z. Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function. Remote Sensing. 2024; 16(19):3580. https://doi.org/10.3390/rs16193580

Chicago/Turabian Style

Wang, Zongmin, Longfei Hou, Haibo Yang, Yong Zhao, Fei Chen, Qizhao Li, and Zheng Duan. 2024. "Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function" Remote Sensing 16, no. 19: 3580. https://doi.org/10.3390/rs16193580

APA Style

Wang, Z., Hou, L., Yang, H., Zhao, Y., Chen, F., Li, Q., & Duan, Z. (2024). Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function. Remote Sensing, 16(19), 3580. https://doi.org/10.3390/rs16193580

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