Identification of Industrial Land Parcels and Its Implications for Environmental Risk Management in the Beijing–Tianjin–Hebei Urban Agglomeration

Zishu Wang, Jie Zhao, Sijie Lin and Yi Liu
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Zishu Wang: School of Environment, Tsinghua University, Beijing 100084, China
Jie Zhao: Department of Ecology and Environment Research, Beijing Tsinghua Holdings Human Settlements Environment Institute, Beijing 100083, China
Sijie Lin: School of Environment, Tsinghua University, Beijing 100084, China
Yi Liu: School of Environment, Tsinghua University, Beijing 100084, China

Sustainability, 2019, vol. 12, issue 1, 1-14

Abstract: Due to rapid, sprawling urban and industrial development, urbanization in China has led to serious environmental pollution with subsequent risks to human well-being. Landscapes comprised of intermingled residential and industrial areas are common across China, which is a large challenge for effective urban planning and environmental protection. Being able to identify industrial land across the urban landscape is critical for understanding patterns of urban design and subsequent consequences for the environment. Here, we describe a method to quickly identify industrial parcels using points of interest (POIs) and large-scale spatial data. We used the Beijing–Tianjin–Hebei urban agglomeration as a case study and identified 8325 square kilometers of industrial land, accounting for 30.7% of the total built land. Based on ground-truth randomly-sampled sites, the accuracy, precision, and recall of identified industrial areas were 87.1%, 66.4%, and 68.1%, respectively. Furthermore, we found that over 350 km 2 of the industrial parcels were high human settlement risks and mainly were distributed in Tianjin and Tangshan city. Over 28.8% of the identified industrial land parcels might be at the risk of potential soil contamination. The results can be helpful in future urban planning and for identifying urban areas that are targets for implementing environmental risk management and remediation.

Keywords: industrial land identification; POIs; large-scale spatial data; environmental risk management; Beijing–Tianjin–Hebei urban agglomeration (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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