Extracting impervious surfaces from multi-source remote sensing data based on Grabcut

doi:10.6046/gtzyyg.2018.03.24

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Abstract

Impervious surface is a major indicator of rapid urbanization, which leads to urban waterlogging. In this study, the authors took the advantages of multi-spectral satellite imagery and LiDAR data based on Grabcut to extract impervious surfaces. Taking the Guangzhou City as a study case, the authors reveal that the method can reach higher overall accuracy and robustness than the traditional single-source method.

Keywords impervious surfaces multi-source remote sensing data Grabcut satellite imagery LiDAR point cloud

TP79

Issue Date: 10 September 2018

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	Jiasi YI
	Xiangyun HU

Cite this article:

Jiasi YI,Xiangyun HU. Extracting impervious surfaces from multi-source remote sensing data based on Grabcut[J]. Remote Sensing for Land & Resources, 2018, 30(3): 174-180.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.03.24 OR https://www.gtzyyg.com/EN/Y2018/V30/I3/174

Fig.1 Flowchart of extracted method

Fig.2 Multi-source features

Fig.3 Classification results

Fig.4 Details of classification results

Tab.1 Classification accuracy of different source data

Tab.2 Classification accuracy of the proposed method and the traditional remote sensing methods

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