Identification and Analysis of Production–Living–Ecological Space Based on Multi-Source Geospatial Data: A Case Study of Xuzhou City

Weilin Wang, Yindi Zhao (), Caihong Ma and Simeng Dong
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Weilin Wang: School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Yindi Zhao: School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Caihong Ma: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Simeng Dong: School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China

Sustainability, 2025, vol. 17, issue 3, 1-24

Abstract: Effective production, living, and ecological space allocation is essential for improving and optimizing urban space development. In this study, we proposed a production–living–ecological space (PLES) identification method based on Point of Interest (POI) data and China Land Cover Dataset (CLCD) to identify PLESs in Xuzhou City for the years 2012, 2018, and 2022, with an average recognition accuracy of 89.81%. Moreover, the land-use transfer matrix, center of gravity migration, and Geo-detector were used to reveal the spatiotemporal pattern evolution of PLESs. The results showed that: (1) The distribution of PLESs presented significant differentiation between Urban Built-Up Area (UBUA) and Non-Urban Built-Up Area (NUBUA). UBUA was mainly composed of living spaces, while NUBUA was primarily characterized by production–ecological spaces. (2) The intensive utilization of urban land led to an increase in the area of multifunctional spaces, while the complexity of urban space increased. (3) During 2012 to 2022, the center of gravity of PLESs remained relatively stable. The moving distances were all less than 1 km (except for ecological space from 2012 to 2018). (4) The evolution of PLESs was closely linked with socio-economic factors, and the interactions between the factors also had a significant driving effect on PLESs.

Keywords: production–living–ecological space (PLES); point of interest (POI); China land cover dataset (CLCD); spatiotemporal pattern evolution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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