Method of water information extraction by improved SWI based on GF-1 satellite image

doi:10.6046/gtzyyg.2017.01.05

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Abstract

High-precision information extraction of mountainous rivers is a key technology for development and utilization of water resources in arid areas of China. Nevertheless, the utilization of remote sensing images cannot distinguish water form mountain shadows. In this paper, the authors used GF-1 satellite images with resolution of 2 m and 8 m as the data source, selected Baka Luck reservoirs as the study area, and put forward an improved method(modified shadow water index, MSWI) for water information extraction. At the same time, the authors used the single-band threshold method, the NDWI method, the single band method combined with the SWI decision tree classification(SWI) and the single band method combined with the MSWI decision tree classification (MSWI) respectively to extract water information in the study area. The results show that, compared with the SWI and the MSWI method, the first two methods have relatively poor performance. The SWI and MSWI classification effect is good and the total classification accuracy of MSWI is increased by 1.22% relative to the SWI method. It can provide technical support for the domestic high series satellite image information extraction in water resources in arid regions.

Keywords UAV imagery data Pix4D Mapper photogrammetric point clouds nDSM objected-based SVM building extraction

TP751.1

Issue Date: 23 January 2017

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	WANG Xudong
	DUAN Fuzhou
	QU Xinyuan
	LI Dan
	YU Panfeng

Cite this article:

WANG Xudong,DUAN Fuzhou,QU Xinyuan, et al. Method of water information extraction by improved SWI based on GF-1 satellite image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 29-35.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2017.01.05 OR https://www.gtzyyg.com/EN/Y2017/V29/I1/29

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