Eco-Environmental Quality Assessment Using the Remote Sensing Ecological Index in Suzhou City, China

Gang Fang, Renato Dan A. Pablo () and Yin Zhang ()
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Gang Fang: School of Environment and Surveying Engineering, Suzhou University, Suzhou 234000, China
Renato Dan A. Pablo: Graduate School, Angeles University Foundation, Angeles 2009, Philippines
Yin Zhang: School of Environment and Surveying Engineering, Suzhou University, Suzhou 234000, China

Sustainability, 2023, vol. 15, issue 17, 1-16

Abstract: This study utilizes four environmental indicators derived from six-phase Landsat images (TM, OLI, and TIRS) to construct a remote sensing ecological index (RSEI) and to quantitatively and comprehensively assess the spatiotemporal changes in the eco-environmental quality (EEQ) of Suzhou City, China. The environmental indicators consist of the wetness index (WI), greenness index (GI), dryness index (DI), and heat index (HI). The obtained results showed: (1) positive effects of the WI and GI, as well as negative effects of the DI and HI, on the EEQ of Suzhou City in the 2002–2022 period. The GI was observed to have the greatest impact on the RSEI of Suzhou City. (2) The average RSEI values of Suzhou City exhibit a “W” shape pattern in the 2002–2022 period. The lowest and highest average RSEI values were 0.632 and 0.746, respectively, while the average annual RSEI value was 0.702. The EEQ of Suzhou City was observed to be at a relatively good level. (3) The EEQ of Suzhou City exhibits sharp declines in the periods of 2006–2010 and 2014–2018, for which the degraded RSEI area covers 440.60 and 404.16 km 2 , while the area ratios are 56.13% and 51.48%, respectively. The EEQ of Suzhou City has substantially increased during the periods of 2010–2014, 2018–2022, and 2002–2022, showing improved RSEI areas of 583.7, 390.13, and 347.02 km 2 and area ratios of 74.36%, 49.70%, and 44.21%, respectively. The results of this study provide a scientific basis for the protection, utilization, and development of the ecological environment (EE) of Suzhou City. They also provide valuable references and data support for the sustainable development, the high-quality development of the EE, and the construction of the ecological civilization of Suzhou City. The policymakers of environmental protection departments in Suzhou City can use this study’s inferences to devise local environmental protection policies.

Keywords: principal component analysis; RSEI; spatiotemporal variation; ecological environment; Suzhou City (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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