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Lithological fuzzy classification by combining WorldView-2 data and OLI data

  • role： First author第一作者
  • Affiliation：

    Institute of Geologic Survey, China University of Geosciences (Wuhan), Wuhan 430074, China

    Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China

  • Email：21844ss@cug.edu.cn
  • Introduction：帅爽，研究方向为遥感地质、地学遥感应用。E-mail： 21844ss@cug.edu.cn
SHUAI Shuang13,  
  • role： Corresponding author通信作者
  • Affiliation：

    Institute of Geophysics & Geomatics, China University of Geoscience (Wuhan), Wuhan 430074, China

  • Email：3slab@cug.edu.cn
  • Introduction：张志，研究方向为遥感地质、地学遥感应用。E-mail： 3slab@cug.edu.cn
ZHANG Zhi2*,  
  • Affiliation：

    Institute of Geologic Survey, China University of Geosciences (Wuhan), Wuhan 430074, China

LYU Xinbiao1,  
  • Affiliation：

    Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China

MA Zicheng3,  
  • Affiliation：

    Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China

CHEN Si3,  
  • Affiliation：

    College of Earth Science, Chengdu University of Technology, Chengdu 610052, China

HAO Lina4

résumé

Medium spatial resolution data, such as TM (Theme Mapper), ETM+ (Enhanced Theme Mapper Plus), OLI (Operational Land Imager) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), has been widely applied in lithological mapping and minerals mapping, because of covering the diagnostic spectral regions of carbonate rocks, clay minerals, iron oxide minerals, etc. However, due to the relatively coarse spatial resolution, the phenomenon of mixed pixels is obvious, which severely restricts the accuracy of lithological mapping of medium spatial resolution data. High spatial resolution data, such as WorldView and QuickBird, provides rich spatial structure information of rock surfaces. Meanwhile, the improvement of spatial resolution is also the most effective way to alleviate the phenomenon of mixed pixels, but the spectral range of high spatial resolution data is often narrow and difficult to extract of minerals and rocks with characteristic reflectance absorption in short-wave infrared and thermal infrared regions. And, for lithological classification method, pixel-based classification methods are still mainly used in previous studies, exhibiting the undesired “salt-and-pepper” phenomenon.The objectives of this study are to (1) combine and enhance the spectral information and spatial structure information of high spatial resolution data (WorldView-2) and medium spatial resolution data (OLI) and (2) evaluate fuzzy classification method for lithological mapping. Firstly, WorldView-2 data and OLI data were structural and spectral combined. Then, texture information and spectral information of the combined data were compressed by PCA, compressed texture layer and compressed spectral layers are selected and stacked. The feature combined data was multi-scale segmented. Finally, the fuzzy logic membership functions of the rock types were built, based on the texture and spectral difference of rock types. And the lithological fuzzy classification of study area was carried out.Results showed that the proposed method classifies the rock types of study area successfully, and received a high total accuracy of 89.35％.

mots-clés

remote sensing;WorldView-2;Landsat 8 OLI;Combined use;rock types;Fuzzy classification

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