基于DEM和高分辨率遥感影像的“膨胀-融合”式地表沟壑提取

李文凯; 张唯; 秦家豪; 王红平

doi:10.3799/dqkx.2020.004

Volume 45 Issue 6

Jun. 2020

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Article Navigation > Earth Science > 2020 > 45(6): 1948-1955

Li Wenkai, Zhang Wei, Qin Jiahao, Wang Hongping, 2020. 'Expansion-Fusion' Extraction of Surface Gully Area Based on DEM and High-Resolution Remote Sensing Images. Earth Science, 45(6): 1948-1955. doi: 10.3799/dqkx.2020.004

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Li Wenkai, Zhang Wei, Qin Jiahao, Wang Hongping, 2020. "Expansion-Fusion" Extraction of Surface Gully Area Based on DEM and High-Resolution Remote Sensing Images. Earth Science, 45(6): 1948-1955. doi: 10.3799/dqkx.2020.004

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"Expansion-Fusion" Extraction of Surface Gully Area Based on DEM and High-Resolution Remote Sensing Images

doi: 10.3799/dqkx.2020.004

Li Wenkai^{1
,
,},
Zhang Wei¹,
Qin Jiahao²,
Wang Hongping^{1
,
,}

1.
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China
2.
China Construction Second Engineering Bureau Ltd. East China Company, Shanghai 200135, China

Received Date: 2019-09-30
Publish Date: 2020-06-15

Abstract

Abstract

Refined extraction of surface gullies is an important part of topography research. Aiming at the existence of fracture zones and a pseudo-gully zones in the existing gully extraction results,in this paper,it proposes an "expansion-fusion" extraction method based on DEM and high-resolution remote sensing image. The method combines the D8 algorithm,the SOA (slope of aspect) algorithm and the object-oriented classification method to extract the results. Firstly,the distance mapping algorithm is introduced to directional expansion of the initial gully,and then the raster re-classification and algebraic operation are used to merge the gully and eliminate the pseudo-gully. In this study,this method is adopted to extract gully area with GDEM v2 data and GF-2 data covering the area of Juheigou to Mawancun in Shennongjia Forest of Hubei Province. The random point verification method is used to evaluate the accuracy of the gully extraction in the experimental area. The results show that the overall accuracy of the method is 92%,which can effectively bridge the fracture area in the combined data,and eliminate the pseudo-gully area to improve the extraction accuracy of the gully.
- surface gully extraction,
- hydrological analysis,
- SOA (slope of aspect),
- object-oriented classification,
- high-resolution remote sensing image

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References(35)

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"Expansion-Fusion" Extraction of Surface Gully Area Based on DEM and High-Resolution Remote Sensing Images

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