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Assessment of Remote Sensing Ecological Quality by Introducing Water and Air Quality Indicators: A Case Study of Wuhan, China

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  • Yue Pan

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Jian Gong

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Jingye Li

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

Abstract

In the context of ecological protection and urban expansion, the quality of the ecological environment and ecological security are gravely at risk. A simple, effective, and comprehensive assessment method for regional environmental quality monitoring is urgently required at this time. This study proposes a comprehensive approach for evaluating regional ecological quality. Based on Landsat TM+OLI/TIRS images, indicators representing the ecological quality of land and water were constructed. Land ecological quality consists of land surface moisture (WET), normalized difference vegetation index (NDVI), normalized building bare soil index (NDBSI), and land surface temperature (LST), which represent humidity, greenness, dryness, and temperature, respectively. At the same time, the remote sensing indices of chlorophyll_a (chl_a) and suspended solids (SS) were constructed to characterize the water quality. Air quality was characterized based on aerosol optical depth (AOD) in MCD19A2. By introducing water and air quality indicators and utilizing principal component analysis, a remote sensing ecological index that improves water area assessment (WIRSEI) was established and applied to Wuhan from 2000 to 2020. The driving force of WIRSEI change was analyzed using the geographically weighted regression (GWR) model. The results revealed that (1) air quality AOD and humidity WET greatly impacted the ecological quality (WIRSEI). WIRSEIs in seven central urban areas were significantly lower than that in six remote urban regions, and the ecological quality of lakes was higher than that of rivers. (2) From 2000 to 2020, Wuhan’s overall WIRSEI showed a “rising–falling–rising–stable” trend. In most regions, the degree of ecological quality change was relatively small; most grades were “no change”, “slightly better”, and “slightly worse”, representing 88–93% of the total area. (3) The change in WIRSEI from 2000 to 2020 was closely related to urban expansion, population change, and economic development. The effects of land use and socioeconomic changes on WIRSEI were significantly different in spatial distribution. Compared to the driving factors, land use dynamics (LUCD) significantly impacted WIRSEI changes, while the effects of gross domestic product (GDP) and population (POP) were very small. This study uses WIRSEI to evaluate the regional ecological quality, providing a vital reference and basis for enhancing regional ecological quality assessment methods, promoting ecological environmental protection and restoration, regional coordination, and sustainable development. The research results show that the proposed approach is simple and effective, strongly supporting regional ecological quality and protection monitoring.

Suggested Citation

  • Yue Pan & Jian Gong & Jingye Li, 2022. "Assessment of Remote Sensing Ecological Quality by Introducing Water and Air Quality Indicators: A Case Study of Wuhan, China," Land, MDPI, vol. 11(12), pages 1-22, December.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:12:p:2272-:d:1001049
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    References listed on IDEAS

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    1. Alistair W. R. Seddon & Marc Macias-Fauria & Peter R. Long & David Benz & Kathy J. Willis, 2016. "Sensitivity of global terrestrial ecosystems to climate variability," Nature, Nature, vol. 531(7593), pages 229-232, March.
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