多源遥感数据图谱协同岩石单元分类方法

张翠芬; 郝利娜; 王少军; 杨玉龙

doi:10.3799/dqkx.2019.168

Volume 45 Issue 5

May 2020

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Article Navigation > Earth Science > 2020 > 45(5): 1844-1854

Zhang Cuifen, Hao Lina, Wang Shaojun, Yang Yulong, 2020. Geological Units Classification with Texture-Spectral Synergy of Multi-Sourced Remote Sensing Images. Earth Science, 45(5): 1844-1854. doi: 10.3799/dqkx.2019.168

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Zhang Cuifen, Hao Lina, Wang Shaojun, Yang Yulong, 2020. Geological Units Classification with Texture-Spectral Synergy of Multi-Sourced Remote Sensing Images. Earth Science, 45(5): 1844-1854. doi: 10.3799/dqkx.2019.168

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Geological Units Classification with Texture-Spectral Synergy of Multi-Sourced Remote Sensing Images

doi: 10.3799/dqkx.2019.168

Zhang Cuifen^{1, 2
,},
Hao Lina^{3
,
,},
Wang Shaojun⁴,
Yang Yulong⁴

1.
The Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
2.
School of Information Technology, Shandong Women's University, Jinan 250002, China
3.
College of Earth Science, Chengdu University of Technology, Chengdu 610052, China
4.
The Faculty of Public Administration, China University of Geosciences, Wuhan 430074, China

Received Date: 2019-07-09
Publish Date: 2020-05-15

Abstract

Abstract

The structural pattern, differential weathering, and outcrop situation of different geological units can be described by the texture information of remote sensing imagery as graphical features. The geological units compositions of differential minerals are shown as spectral cues.With regard to geological units classification, the classification accuracy of most studies is limited since they have mainly utilized the spectral cues from multis-pectral or hyperspectral images to characterize their spectral features, and high resolution imagery to depict the texture information as a supplement. In this study, the texture-spectral indices are established with the multi-sourced remote sensing images of Worldview-2 and ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer)and tested for geological units classification in the western section of Beishan Mountain, which are located at the junction of Gansu Province and Xinjiang Uygur Autonomous Region. Based on the panchromatic band of Worldview-2 imagery, the following graphical features that quantify the bedding structure, distribution morphology and micro-topography features of different rock units were extracted: 0° and 45°directional filtering, the textures of homogeneity, dissimilarity and entropy generated from gray level co-occurrence matrix. Based on multi-spectral bands of Worldview-2 imagery and the short-wave infrared bands of ASTER imagery, the spectral indices were established by the band-ratio and addition-difference methods, including RI (Ratio index)_ASTER, SI(Spectral index) _ASTER, and SI_Worldview-2. First, based on the object-oriented approach and the texture-spectral indices, texture-spectral features were used to conduct multi-resolution segmentation to produce numerous geological units with different scales. Second, the geological units were classified at different scales using spectral indices. The results show that: (1) 17 types of geological units were classified with an overall accuracy of 83.62%, based on the proposed method; (2) and only 13 or 14 types of geological units were classified, by using the Worldview-2 or ASTER images, respectively. The outlined approach could provide the theoretical and remote sensing technical support for geological survey and prospecting work in the high altitude with deep-cut unpopulated areas of western China.
- geological units classification,
- texture index,
- spectral index,
- texture-spectral synergy,
- remote sensing geology

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