Land use change detection based on multi-source data

doi:10.6046/gtzyyg.2018.04.22

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Abstract

Annual land use change survey is very important for keeping the land use data of China up-to-date. Currently, Land use change information acquisition is mainly based on artificial visual interpretation, which is low in efficiency. A new method of land use change detection based on multi-source data is presented in this paper. Classification samples for current phase image are acquired form previous phase land use vector data through a processing of sample refining. So automatic classification for current phase image can be implemented, which makes automatic change detected by comparing classification result with previous phase land use. The multivariate alteration detection (MAD) transformation method for the two phase image is used to eliminate pseudo change. The changed polygon objects with accuracy boundary are extracted based on change detect. Experiment shows that the proposed method is more effective with working time less than half that of the traditional method, and can better find real land use change without omission.

Keywords change detection land use multi-source data

P237.3TP751

Issue Date: 07 December 2018

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	Zhan ZHAO
	Wang XIA
	Li YAN

Cite this article:

Zhan ZHAO,Wang XIA,Li YAN. Land use change detection based on multi-source data[J]. Remote Sensing for Land & Resources, 2018, 30(4): 148-155.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.04.22 OR https://www.gtzyyg.com/EN/Y2018/V30/I4/148

Fig.1 Experiment data in Dorbet Mongolian Autonomous County

Fig.2 Experiment data in Changsha County

Fig.3 Technical flow of change detection and extraction

Fig.4 Flow chart of samples refining

Fig.5 Processing results of experiment data in Dorbet Mongolian Autonomous County

Fig.6 Processing results of experiment data in Changsha County

Fig.7 Comparison of results of the proposed method and traditional method

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