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http://dx.doi.org/10.7780/kjrs.2010.26.5.465

Design and Construction of Spectral Library for the Korean Peninsular  

Shin, Jung-Il (Department of Geoinformatic Engineering, Inha University)
Kim, Sun-Hwa (Department of Geoinformatic Engineering, Inha University)
Lee, Kyu-Sung (Department of Geoinformatic Engineering, Inha University)
Publication Information
Korean Journal of Remote Sensing / v.26, no.5, 2010 , pp. 465-475 More about this Journal
Abstract
Spectral library is a database that archives spectral reflectance and related metadata of earth surface materials. Spectral library plays important role to assist analyzing several types of remote sensor data, to determine suitable wavelength band for detecting a certain material, and to classify hyperspectal image data. This paper describes the structure and content of a spectral library that is suitable for the environment of the Korea peninsula while existing spectral libraries have certain limitations to apply for surface materials covering the region. We designed a spectral library that includes vegetation and man-made materials indigenous to the region. The spectral library also includes spectra of mineral and rock, soil, liquid, and some man-made materials from existing spectral libraries. Newly augmented spectra of vegetation and man-made materials were obtained by spectral measurements in laboratory and field. The spectral library viewer was developed to increase efficiency of usage and searching.
Keywords
Spectral library; spectral reflectance; hyperspectral data;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Kokaly, R. F., D. G. Despain, R. N. Clark, and K. E. Livo, 2003. Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data. Remote Sensing of Environment, 84(3): 437-456.   DOI   ScienceOn
2 Kruse, F. A., A. B. Lefkoff, J. W. Boardman, K. B. Heidebrecht, A. T. Shapiro, P. J. Barloon, and A. F. H. Goetz, 1993. The spectral image processing system (SIPS) - Interactive visualization and analysis of imaging spectrmeter data. Remote Sensing of Environment, 44(2-3): 145-163.   DOI   ScienceOn
3 Franke, J., D. A. Roberts, K. Halligan, and G. Menz, 2009. Hierarchical multiple endmember spectral mixture analysis (MESMA) of hyperspectral imagery for urban environments. Remote Sensing of Environment, 113(8): 1712-1723.   DOI   ScienceOn
4 Johns Hopkins university spectral library, http://speclib.jpl.nasa.gov/documents/jhu_desc
5 Baldridge, A. M., S. J. Hook, C. I. Grove, and G. Rivera, 2009. The ASTER spectral library version 2.0. Remote Sensing of Environment, 113(4): 711-715.   DOI   ScienceOn
6 Clark, R. N., G. A. Swayze, A. J. Gallagher, T. V. V. King, and W. M. Calvin, 1993. The U. S. Geological Survey, Digital spectral library: version 1 (0.2 to 3.0mm). U.S. Geological Survey, Open file report, 93-592, http://speclab.cr.usgs.gov/spectral.lib04/clark1993/spectral_lib.html.
7 DiGregorio, B. E., 2003. The planetary shared sample library - A new tool for planetary science. Spectroscopy, 18(3): 32.
8 Drake, N. A., S. Mackin, and J. J. Settle, 1999. Mapping vegetation, soils, and geology in semiarid shrublands using spectral matching and mixture modeling of SWIR AVIRIS imagery. Remote Sensing of Environment, 68(1): 12-25.   DOI   ScienceOn
9 임업연구원, 1996. 활엽수자원조사보고서: 전국총괄. 임업연구원 연구자료, 제122호.
10 ICRAF spectral library, http://gcmd.nasa.gov/KeywordSearch/Metadata.do? Portal=GCMD&KeywordPath=&NumericId=15023&MetadataView=Brief&Metad ataType=0&lbnode=mdlb2
11 Swain, P. H. and S. M. Davis, 1978. Remote Sensing: The Quantitative Approach, McGraw-Hill Inc., U.S.A.
12 지광훈, 이성순, 이홍진, 2007. 지표피복물 분광정보 라이브러리 - 암석.식생.인공구조물. 한국지질자원연구원 공공원격탐사 지상센터.
13 통계청, 2007. 한국통계연감. 제54호.
14 김주원, 2002. 간추린 아스팔트 혼합물의 역사. 토지개발기술, 15(1): 7-24.
15 Schaepman-Strub, G., Schaepman, M. E., Painter, T. H., Dangel, S., and Martonchik, J. V., 2006. Reflectance quantities in optical remote sensing - definitions and case studies. Remote Sensing of Environment, 103(1): 27-42.   DOI   ScienceOn
16 Shepherd, K. D. and M. G. Walsh, 2002. Development of reflectance spectral libraries for characterization of soil properties. Soil Science Society of America Journal, 66: 988-998.   DOI
17 Van Der Meer, F. D. and S. M. De Jong, 2003. Imaging spectrometry - Basic principles and prospective application. Kluwer academic publishers, Dordrecht, The Neherlands.
18 이규성, 윤여상, 김선화, 신정일, 윤정숙, 강성진, 2009. 한반도 토지이용 및 토지피복 모니터링을 위한 현안 분석. 대한원격탐사학회지, 25(1): 71-83.   과학기술학회마을   DOI
19 농림부, 2006. 농림통계연보.
20 산림청, 2009. 임업통계연보. 제 39호.
21 Meston, S. K. T., 2004. Far-infrared spectroscopy helps defend against threat of terrorism. Spectroscopy, 19(1): 66.
22 ASU spectral library, http://speclib.asu.edu/
23 Lillesand, T. M. and Kiefer, R. W., 1994. Remote sensing and image interpretation, Third edition. John Wiley & Sons, New York, pp. 12-17.
24 Lowry, S., Wieboldt, D., Dalrymple, D., Jasinevicius, R., and Downs R. T., 2009. The use of a Raman spectral database of minerals for the rapid verification of semiprecious gemstones. Spectroscopy, 24(5): 52-60.
25 Milton, E. J., M. E. Schaepman, K. Anderson, M. Kneubuhler, and N. Fox, 2009. Progress in field spectroscopy. Remote Sensing of Environment, 113(S1): S92-S109.   DOI
26 Powell, R. L., D. A. Roberts, P. E. Dennison, and L. L. Hess, 2007. Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil. Remote Sensing of Environment, 106(2): 256-267.
27 Howari, F. M., 2003. Comparison of spectral matching algorithms for identifying natural salt crusts. Journal of Applied Spectroscopy, 70(5): 782-787.   DOI
28 Rivard, B., J. Feng, A. Gallie, and A. Sanchez- Azofeifa, 2008. Continuous wavelets for the improved use of spectral libraries and hyperspectral data. Remote Sensing of Environment, 112(6): 2850-2862.   DOI   ScienceOn
29 Grebenyuk, N. N. and Blank, A. B., 2001. Method of eliminating systematic errors of atomic absorption analysis in atomization of a material in a graphite furnace. Journal of Applied Spectroscopy, 68(5): 859-861.   DOI   ScienceOn
30 Heiden, U., K. Segl, S. Roessner, and H. Kaufmann, 2007. Determination of robust spectral features for identification of urban surface materials in hyperspectral remote sensing data. Remote Sensing of Environment, 111(4): 537-552.   DOI   ScienceOn