Urban villages extraction from high-resolution remote sensing imagery based on landscape semantic metrics

doi:10.11947/j.AGCS.2021.20190463

Abstract

Abstract: Urban villages (UVs), a special type of informal settlement in China. In this study, we proposed a method for UV extraction from high-resolution remote sensing imagery using landscape semantic metrics that can describe the complicated scene of UVs. In addition, an “uncertainty-feedback” strategy was proposed for large-scale practicable UV mapping. The experiment was performed in the urban areas of Guangzhou, with overall accuracy larger than 90%. The results reveal that the landscape semantic metrics have better ability to describe the essential characteristics of UVs compared to the traditional spectral and textural features. Besides, the “uncertainty-feedback” strategy can make full use of the classification reliability output by the machine learning, and produce more accurate UV mapping results with limited manual intervention. Thus, the proposed method can be effectively applied to large-scale UV extraction and mapping.

Key words: urban villages, high-resolution remote sensing imagery, landscape metrics, scene representation, land-use mapping

CLC Number:

P227

ZHANG Tao, DING Lele, SHI Furong. Urban villages extraction from high-resolution remote sensing imagery based on landscape semantic metrics[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(1): 97-104.

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