An Assessment of Urban Residential Environment Quality Based on Multi-Source Geospatial Data: A Case Study of Beijing, China

Author:

Zhang Shijia1,Xia Yang1,Li Zijuan1,Li Xue1,Wu Yufei1,Liu Peiyi1,Du Shouhang1

Affiliation:

1. College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

Abstract

Assessing the urban residential environment quality (REQ) is essential for advancing sustainable urban development and enhancing urban residents’ living standards. Traditional REQ assessments rely on statistical data, prone to delays and lacking holistic insight. This study takes residential blocks as the analysis units and is conducted within the area of the Sixth Ring Road in Beijing. It synthesizes multi-source geospatial data to devise a comprehensive framework for assessing urban REQ, incorporating facets of environmental health and comfort, housing comfort, transportation convenience, city security, and life convenience. Utilizing the principle of minimal relative informational entropy, this study integrates the Analytic Hierarchy Process (AHP) with the entropy method to determine the weight of each evaluative criterion. Subsequently, a linear weighting technique is employed to ascertain the scores for each evaluative criterion, thus facilitating a detailed examination of the REQ. Finally, the research probes into the complex interrelation between the assessed REQ and the city’s Gross Domestic Product (GDP) and carbon emissions across varying scales. Findings reveal that (1) the overall REQ within Beijing’s Sixth Ring Road is superior at the center and diminishes towards the periphery. (2) The dispersion of environmental health and comfort and city security metrics is relatively uniform, showing minor variations; however, a marked disparity is observed in the distribution of housing comfort metrics. (3) Regions characterized by higher GDP tend to demonstrate relatively higher levels of the REQ. Conversely, areas boasting higher-quality urban REQ are more inclined to exhibit increased levels of carbon emissions.

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

MDPI AG

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