Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function
(2024) In Remote Sensing 16(19).- 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... (More)
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.
(Less)
- author
- Wang, Zongmin ; Hou, Longfei ; Yang, Haibo ; Zhao, Yong ; Chen, Fei ; Li, Qizhao and Duan, Zheng LU
- organization
- publishing date
- 2024-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- eco-environment quality, quaternion copula function, remote sensing ecological index, spatial–temporal changes
- in
- Remote Sensing
- volume
- 16
- issue
- 19
- article number
- 3580
- publisher
- MDPI AG
- external identifiers
-
- scopus:85206298115
- ISSN
- 2072-4292
- DOI
- 10.3390/rs16193580
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2024 by the authors.
- id
- eccd9df7-ec5f-40b9-983a-03084f0f6b22
- date added to LUP
- 2024-12-18 12:34:26
- date last changed
- 2025-05-13 11:41:35
@article{eccd9df7-ec5f-40b9-983a-03084f0f6b22,
abstract = {{<p>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.</p>}},
author = {{Wang, Zongmin and Hou, Longfei and Yang, Haibo and Zhao, Yong and Chen, Fei and Li, Qizhao and Duan, Zheng}},
issn = {{2072-4292}},
keywords = {{eco-environment quality; quaternion copula function; remote sensing ecological index; spatial–temporal changes}},
language = {{eng}},
number = {{19}},
publisher = {{MDPI AG}},
series = {{Remote Sensing}},
title = {{Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function}},
url = {{http://dx.doi.org/10.3390/rs16193580}},
doi = {{10.3390/rs16193580}},
volume = {{16}},
year = {{2024}},
}