Prof. Hao Sun Profile

Prof. Hao Sun

at China Univ of Mining and Technology-Beijing

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SPIE Journal Paper | 11 March 2021 Open Access

Evaluating eco-environment in urban agglomeration from a vegetation-impervious surface-soil-air framework: an example in Ningxia, China

Hao Sun, Ling Wu, Jiaqi Hu, Liru Ma, Huan Li, Dan Wu

JARS, Vol. 15, Issue 01, 014518, (March 2021) https://doi.org/10.1117/12.10.1117/1.JRS.15.014518

KEYWORDS: Vegetation, Remote sensing, MODIS, Soil science, Soil contamination, Data modeling, Air contamination, Sun, Statistical analysis, Reflectivity

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Urban agglomerations (UA) are the fastest growing regional types during recent years, especially in developing countries. Monitoring and evaluating the eco-environment quality of UA is significant for sustainability. The previous remote sensing models of urban eco-environment are generally based on the vegetation-impervious surface-soil framework, which neglects the air quality in urban areas. We constructed a vegetation-impervious surface-soil-air (VISA) framework and derived a remote sensing model of UA eco-environment (RSUAE) based on the VISA. The RSUAE can integrate the greenness, dryness and imperviousness, moisture, heat, and air turbidity. The new model was evaluated by comparing with land cover types and the existing remote sensing-based ecological index and eco-environmental quality index models. Results demonstrated that RSUAE is valid to depict the difference of eco-environment quality among varied land cover types. The RSUAE model has general consistency with the existing models, while RSUAE takes into account well the air quality. The RSUAE was utilized to evaluate the eco-environment of UA along the Yellow River in Ningxia, China (NXUA) with Mann–Kendall trend test. Results identified 78.69% of the area has no significant change trend, 18.73% of the area has a significant increasing trend, and 2.58% of the area suffers significant decreasing trend in eco-environment quality from 2001 to 2019. The Yanchi county has the best improvement in eco-environment quality, whereas sensitivity analysis indicates that it is more vulnerable than other counties. The analysis tool and method presented in this study provide a reference for other UAs. The evaluation results in NXUA are noteworthy for local management.

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