Analysis of Spatial Changes in Urban Areas Due to Revitalization Investments Based on China and Poland

In order to address the social, economic, and environmental challenges arising from urban development, some urban revitalization plans have been proposed. With the implementation of these plans, the spatial pattern of the region has also undergone corresponding changes. Some of the revitalization projects have driven economic growth while accompanied by ecological degradation, while others have achieved coordinated development and protection. This study selected eight urban revitalization cases, based on remote sensing (RS) and geographic information system (GIS), and used the Random Forest (RF) machine learning method to dynamically monitor the spatial changes in the region before and after revitalization through Land Use and Land Cover (LULC) analysis. The research results show that among the eight cases, only the revitalization cases located in Beijing and Swarzędz reflected an increase in water and vegetation areas, while the built-up area decreased. The other six cases located in Nanjing, Kraków, Wągrowiec, Swarzędz, Parczew, and Mosina all reflect the result of built-up areas encroaching water and vegetation areas.

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Publication Details

Journal
Sustainability
Published
2025-11-12
DOI
https://doi.org/10.3390/su172210126
Citations
2
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
2.21
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article

Analysis of Spatial Changes in Urban Areas Due to Revitalization Investments Based on China and Poland

Yingxin Wang, Adam Choryński
2 citations
Sustainability
Land Use and Ecosystem Services
2.21
article

Analysis of Spatial Changes in Urban Areas Due to Revitalization Investments Based on China and Poland

Yingxin Wang, Adam Choryński
article en
2 citations

Abstract

In order to address the social, economic, and environmental challenges arising from urban development, some urban revitalization plans have been proposed. With the implementation of these plans, the spatial pattern of the region has also undergone corresponding changes. Some of the revitalization projects have driven economic growth while accompanied by ecological degradation, while others have achieved coordinated development and protection. This study selected eight urban revitalization cases, based on remote sensing (RS) and geographic information system (GIS), and used the Random Forest (RF) machine learning method to dynamically monitor the spatial changes in the region before and after revitalization through Land Use and Land Cover (LULC) analysis. The research results show that among the eight cases, only the revitalization cases located in Beijing and Swarzędz reflected an increase in water and vegetation areas, while the built-up area decreased. The other six cases located in Nanjing, Kraków, Wągrowiec, Swarzędz, Parczew, and Mosina all reflect the result of built-up areas encroaching water and vegetation areas.

SustainabilityVol. 17(22)
University of Life Sciences in Poznań (PL)
Openalex Percentile: Top 11%
Land Use and Ecosystem Services
2.21
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