Roberts, D.A. 2011 Hyperspectral vegetation indices. Chapter
14. pp. 309-328, in Hyperspectral Remote Sensing of Vegeta-
tion, P.S. Thenkabail, et al., Eds., ed: CRC Press- Taylor and
Francis group, Boca Raton, London, New York. 781, 2011 pp.
Schlemmer, M., Gitelson, A., Schepers, J., Ferguson, R., Peng,
Y., Shanahan, J. and Rundquist, D. 2013. Remote estima-
tion of nitrogen and chlorophyll contents in maize at leaf
and canopy levels,
International Journal of Applied Earth
Observation and Geoinformation,
25(0): 47-54.
Schlerf, M., Rock, G., Lagueux, P., Ronellenfitsch, F., Ger-
hards, M., Hoffmann, L. and Udelhoven, T. 2012. A Hyper-
spectral Thermal Infrared Imaging Instrument for Natural
Resources Applications,
Remote Sensing,
4(12): 3995-4009.
Slonecker, E.T., Fisher, G.B., Marr, D.A., Milheim, L.E. and
Roig-Silva, C.M. 2013 Advanced and applied remote sensing
of environmental conditions: U.S. Geological Survey Fact
Sheet 2013-3007, 2 pp., available only at
gov/fs/2013/3007/.
Staenz, K. and Held, A. 2012. Summary of current and future
terrestrial civilian hyperspectral spaceborne systems,
Geo-
sciences and Remote sensing Symposium
(IGARSS). 123-
126. ISSN: 2153-6996.
Swatantran, A., Dubayah, R., Roberts, D., Hofton, M. and
Blair, J.B. 2011. Mapping biomass and stress in the Sierra
Nevada using lidar and hyperspectral data fusion,
Remote
Sensing of Environment,
115(11): 2917-2930.
Thenkabail, P.S. 2002. Optimal Hyperspectral Narrowbands
for Discriminating Agricultural Crops,
Remote Sensing Re-
views,
20(4): 257-291.
Thenkabail, P.S., Enclona, E.A., Ashton, M.S., Legg, C. and
De Dieu, M.J. 2004. Hyperion, IKONOS, ALI, and ETM+
sensors in the study of African rainforests,
Remote Sensing
of Environment,
90(1): 23-43.
Thenkabail, P.S., Enclona, E.A., Ashton, M.S. and Van Der
Meer, B. 2004. Accuracy assessments of hyperspectral wave-
band performance for vegetation analysis applications,
Re-
mote Sensing of Environment,
91(3-4): 354-376.
Thenkabail, P.S., Lyon, G.J. and Huete, A. 2011 Book Chapter
# 28: Hyperspectral Remote Sensing of Vegetation and Ag-
ricultural Crops: Current Status and Future Possibilities.
In Book entitled: “Remote Sensing of Global Croplands for
Food Security” (CRC Press- Taylor and Francis group, Boca
Raton, London, New York. Edited by Thenkabail, P.S., Lyon,
G.J., and Huete, A. 663-668 pp.
Thenkabail, P.S., Lyon, G.J. and Huete, A. 2011
Book entitled:
“Hyperspectral Remote Sensing of Vegetation”. CRC Press-
Taylor and Francis group, Boca Raton, London, New York.
Pp. 781 (80+ pages in color). Reviews of this book: http://
Thenkabail, P.S., Mariotto, I., Gumma, M.K., Middleton, E.M.,
Landis, a.D.R. and Huemmrich, F.K. 2013. Selection of hy-
perspectral narrowbands (HNBs) and composition of hyper-
spectral twoband vegetation indices (HVIs) for biophysical
characterization and discrimination of crop types using field
reflectance and Hyperion/EO-1 data,
IEEE Journal of Se-
lected Topics in Applied Earth Observations and Remote
Sensing,
6(2): 427-438.
Thenkabail, P.S., Smith, R.B. and De-Pauw, E. 2002. Evalua-
tion of Narrowband and Broadband Vegetation Indices for
Determining Optimal Hyperspectral Wavebands for Agri-
cultural Crop Characterization,
Photogrammetric Engineer-
ing and Remote Sensing,
68(6): 607-621.
Thenkabail, P.S., Smith, R.B. and De Pauw, E. 2000. Hyper-
spectral Vegetation Indices and Their Relationships with
Agricultural Crop Characteristics,
Remote Sensing of Envi-
ronment,
71(2): 158-182.
Thorp, K.R., French, A.N. and Rango, A. 2013. Effect of image
spatial and spectral characteristics on mapping semi-arid
rangeland vegetation using multiple endmember spectral
mixture analysis (MESMA),
Remote Sensing of Environ-
ment,
132(0): 120-130.
Udelhoven, T., Delfosse, P., Bossung, C., Ronellenfitsch, F.,
Mayer, F., Schlerf, M., Machwitz, M. and Hoffmann, L.
2013. Retrieving the Bioenergy Potential from Maize Crops
Using Hyperspectral Remote Sensing,
Remote Sensing,
5(1):
254-273.
Verrelst, J., Romijn, E. and Kooistra, L. 2012. Mapping Vege-
tation Density in a Heterogeneous River Floodplain Ecosys-
tem Using Pointable CHRIS/PROBA Data,
Remote Sensing,
4(9): 2866-2889.
Zhang, B., Wang, X., Liu, J., Zheng, L. and Tong, Q. 2000. Hy-
perspectral Image Processing and Analysis System (HIPAS)
and its application,
Photogrammetric Engineering and Re-
mote Sensing,
66(5): 605-619.
Zhang, C., Kovacs, J., Wachowiak, M. and Flores-Verdugo, F.
2013. Relationship between Hyperspectral Measurements
and Mangrove Leaf Nitrogen Concentrations,
Remote Sens-
ing,
5(2): 891-908.
A
uthors
Prasad S. Thenkabail
, Western Geographic Science Center,
U. S. Geological Survey, USA
Murali Krishna Gumma
, International Crops Research
Institute for the Semi-Arid Tropics (ICRISAT)
Pardhasaradhi Teluguntla
, Western Geographic Science
Center,U. S.Geological Survey, and theBayAreaEnvironmental
Research Institute (BAERI),California, USA
Irshad A. Mohammed
, International Crops Research
Institute for the Semi-Arid Tropics (ICRISAT)
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
August 2014
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