Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 431-435, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-431-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
23 Jun 2016
GEOLOGICAL MAPPING BY COMBINING SPECTRAL UNMIXING AND CLUSTER ANALYSIS FOR HYPERSPECTRAL DATA
N. Ishidoshiro1, Y. Yamaguchi1, S. Noda1, Y. Asano1, T. Kondo2, Y. Kawakami2, M. Mitsuishi2, and H. Nakamura2 1Graduate School of Environmental Studies, Nagoya University, Chikusa-ku, Nagoya, 464-8601 Japan
2Exploration Technology Division, Japan Oil, Gas and Metals National Corporation, 2-10-1 Toranomon, Minato-ku, Tokyo, 105-0001 Japan
Keywords: Geology, Mineral, Unmixing, Cluster Analysis, Hyperspectral, Cuprite Abstract. Spectral unmixing of hyperspectral data often fails to select some minerals and rocks having flat spectra but no diagnostic absorption features as endmembers, even if they are actually important endmembers. To avoid this problem, we propose a novel approach that combined two methods: spectral unmixing and full-pixel classification. First, all pixels were divided into two categories, hydrothermally altered areas and unaltered rocks based on the absorption depth of 2.0 to 2.5 μm. For the hydrothermally altered areas, endmembers were extracted by the Improved Causal Random Pixel Purity Index (ICRPPI) method, which was improved from the existing Pixel Purity Index (PPI) and Causal Random Pixel Purity Index (CRPPI) methods. Endmember abundance in each pixel was calculated by linear spectral unmixing. In a separate operation, k-means clustering was applied to the unaltered rock areas. Finally, the results of these two methods were combined to generate a single distribution map of rocks and minerals. This approach was applied to the airborne hyperspectral HyMap data of Cuprite, Nevada, U.S.A. We confirmed that our mapping result was consistent with the existing geological map as well as our field survey result.
Conference paper (PDF, 7492 KB)


Citation: Ishidoshiro, N., Yamaguchi, Y., Noda, S., Asano, Y., Kondo, T., Kawakami, Y., Mitsuishi, M., and Nakamura, H.: GEOLOGICAL MAPPING BY COMBINING SPECTRAL UNMIXING AND CLUSTER ANALYSIS FOR HYPERSPECTRAL DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 431-435, https://doi.org/10.5194/isprs-archives-XLI-B8-431-2016, 2016.

BibTeX EndNote Reference Manager XML