The Use of Landscape Metrics and Transfer Learning to Explore Urban Villages in China
AbstractUrban villages (UVs), the main settlements of rural migrant workers and low-income groups in metropolitan areas of China, have become of major concern to city managers and researchers due to the rapid urbanization in recent years. A clear understanding of their evolution and spatial relationships with the city is of great importance to policy formulation, implementation and assessment. In this paper, we propose a new framework based on landscape metrics and transfer learning for the long-term monitoring and analysis of UVs, and we apply it to Shenzhen and Wuhan, two metropolitan cities of China, with high-resolution satellite images acquired from 2003–2012 and 2009–2015, respectively. In the framework, landscape metrics are used for identifying the UVs and quantifying their evolution patterns on the basis of a city-UV-building hierarchical landscape model. Transfer learning is also introduced to use the samples and features across the spatial and temporal domains, which reduces the time and labor cost, as well as improves the mapping accuracies by 3–10%. The results show that the total area of UVs has decreased by less than
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Liu, H.; Huang, X.; Wen, D.; Li, J. The Use of Landscape Metrics and Transfer Learning to Explore Urban Villages in China. Remote Sens. 2017, 9, 365.
Liu H, Huang X, Wen D, Li J. The Use of Landscape Metrics and Transfer Learning to Explore Urban Villages in China. Remote Sensing. 2017; 9(4):365.Chicago/Turabian Style
Liu, Hui; Huang, Xin; Wen, Dawei; Li, Jiayi. 2017. "The Use of Landscape Metrics and Transfer Learning to Explore Urban Villages in China." Remote Sens. 9, no. 4: 365.
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