Historical Eco-Environmental Quality Mapping in China with Multi-Source Data Fusion

Author:

Wu Shaoteng1,Cao Lei1,Xu Dong234ORCID,Zhao Caiyu5

Affiliation:

1. School of Architecture, Tianjin University, Tianjin 300072, China

2. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

3. Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

4. Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China

5. Electronic Information Engineering College, Changchun University, Changchun 130022, China

Abstract

Since the initiation of economic reforms and opening up, China has witnessed an unprecedented rate of development across all sectors. However, the country has also experienced severe ecological damage, surpassing that of many other nations. The rapid economic growth has come at the expense of the environment, revealing a significant lack of coordination between urbanization and eco-environmental protection in China. Consequently, there is an urgent need for a comprehensive and continuous historical dataset of China’s eco-environmental quality (EEQ) based on remote sensing, allowing for the analysis of spatial and temporal changes. Such data would provide objective, scientific, and reliable support for China’s eco-environmental protection and pollution prevention policies, while addressing potential ecological risks resulting from urbanization. To achieve this, the entropy value method is employed to integrate multi-source remote sensing data and construct an evaluation system for China’s EEQ. Historical data from 2000 to 2017 is plotted to illustrate China’s EEQ over time. The findings of this study are as follows: (1) The entropy method effectively facilitates the construction of China’s eco-environmental quality assessment system. (2) From 2000 to 2017, approximately 39.7% of China’s regions witnessed a decrease in EEQ, while 60.3% exhibited improvement, indicating an overall enhancement in EEQ over the past eighteen years. (3) The Yangtze and Yellow River basins experienced improved EEQ due to China’s ecological restoration projects. (4) The future EEQ in China demonstrates a subtle positive trend across diverse contexts. This study departs from conventional approaches to EEQ evaluation by leveraging the advantages of multivariate remote sensing big data, including objectivity, timeliness, and accessibility. It provides a novel perspective for future eco-environmental quality evaluation.

Funder

Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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