International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
  
ce (%) 
Reflectar 
Wavelenyth {nm} 
Figure 10. High resolution spectra of Kentucky Lake (the 
scale is between 0 and 1 (100%) for the reflectance axis) 
The RDACS data used in this study provided the highest 
accuracy in terms of classification of individual overstory 
species. Although AVIRIS generally provides very good 
results, the datasets collected for the study area had many 
problems. Only very limited areas could be used to classify 
the land cover; therefore, the AVIRIS datasets were not fully 
utilized in the comparison process. Although the Hyperion 
data had a low spatial resolution, the results showed that the 
data could be used for mapping of vegetation alliances in 
forestry related studies. Water quality studies using the 
Hyperion sensor should be more cost effective than using 
airborne hyperspectral imagery. 
7. REFERENCES 
Adams, J. B., M. O. Smith, and P. E. Johnson, 1986. 
Spectral mixture modeling: A new analysis of rock and soil 
types at Viking Lander 1 site. Journal of Geophysical 
Research (JGR), 91:8098-8112. 
Bateson, A., and B. Curtiss, 1996. A method for manual 
endmember selection and spectral unmixing. Remote Sensing 
of the Environment, 55:229-243. 
Boardman, J. W., 1990. Inversion of high spectral resolution 
data. Society of Photo-Optical Instrumentation Engineers 
(SPIE), 1298:222-233. 
Cetin, H., 1990. 
dimensional probability density functions for remotely 
sensed data. Proceedings of the 10th Annual International 
nPDF-An algorithm for mapping n- 
Geoscience & Remote Sensing Symposium, 1GARSS'90, I: 
353-356. 
Cetin, H. and Levandowski, D. W., 1991. Interactive 
classification and mapping of multi-dimensional remotely 
sensed data using n-dimensional probability density functions 
(nPDF). Photogrammetric Engineering and Remote Sensing, 
57(12): 1579-1587. 
1312 
Cetin, H., Warner, T. A., and Levandowski, D. W., 1993. 
Data classification, visualization and enhancement using n- 
dimensional probability density functions (nPDF): AVIRIS, 
TIMS, TM and geophysical applications. Photogrammetric 
Engineering and Remote Sensing, 59(12): 1755-1764. 
Clark, R.N, G.A. Swayze, and A. Gallagher, 1992. Mapping 
the mineralogy and lithology of anyonlands, Utah with 
imaging spectrometer data and the Multiple Spectral Feature 
Mapping Algorithm. The Third Annual JPL Airborne 
Geosciences Workshop, Volume I: AVIRIS Workshop; JPL 
Publication, 92-14:11-13 
Cloutis, E. A., 1996. 
sensing: evaluation of analytical techniques. [International 
Journal of Remote Sensing, 17(12):2215-2242. 
Hyperspectral geological remote 
Dwyer, J. L., F. A. Kruse, and A. B. Lefkoff, 1995, Effects 
of empirical versus model-based reflectance calibration on 
automated analysis of imaging spectrometer data: A case 
study from the Drum Mountains, Utah. Photogrammetric 
Engineering and Remote Sensing, 61:1247-1254. 
Green, R.O., M.L. Eastwood, C.M. Sarture, T.G. Chrien, M. 
Aronsson, B.J. Chippendale, J.A. Faust, B.E. Pauri, C.I. 
Chovit, M. Solis, M.R. Olah and O. Williams, 1998. Imaging 
Spectroscopy and the Airborne Visible/Infrared Imaging 
Spectrometer (AVIRIS). Remote Sensing of the Environment, 
65:227-248. 
Huete, A., Justice, C., and Liu, H., 1994. Development of 
vegetation and oil indices for MODIS-EOS. Remote Sensing 
of Environment, 49:224-234. 
Jakubauskas, M.E., and Price, K.E., 1997. 
relationships between structural and spectral factors of 
Empirical 
Yellowstone Lodgepole pine forests. Photogrammetric 
Engineering and Remote Sensing, 63(12):1375-1381. 
Lee, C. and D..A. Landgrebe, 1993 
dimensional multispectral data. [EEE Transactions on 
Geoscience and Remote Sensing, 31 (4):792-800. 
Analyzing high - 
Marmo, J., 1996. Hyperspectral imager will view many 
colors of earth. Laser FocusWorld, 8:85-92. 
Martin, M. E. and J. D. Aber, 1997. High spectral resolution 
remote sensing of forest canopy lignin, nitrogen, and 
ecosystem processes. Ecological Applications, 7 (2):431 -443. 
Mustard, J. F., and Pieters, 1987. Quantitative abundance 
estimates from bidirection reflectance measurements. The 
[7th Lunar Planet Science Conference, JGR, supplemen,: 
92:E617-E626.