Estimating aboveground biomass of grassland having a high canopy cover: an exploratory analysis of in situ hyperspectral data

References

• Anderson , G. L. , Hanson , J. D. and Hass , R. H. 1993 . Evaluating Landsat Thematic Mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands . Remote Sensing of Environment , 45 : 165 – 175 .
   Web of Science ®Google Scholar
• Broge , N. H. and Leblanc , E. 2000 . Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density . Remote Sensing of Environment , 76 : 156 – 172 .
   Web of Science ®Google Scholar
• Chen , J. 1996 . Evaluation of vegetation indices and modified simple ratio for boreal applications . Canada Journal Remote Sensing , 22 : 229 – 242 .
   Google Scholar
• Cho , M. A. and Skidmore , A. K. 2006 . A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method . Remote Sensing of Environment , 101 : 181 – 193 .
   Web of Science ®Google Scholar
• Cho , M. A. , Skidmore , A. , Corsi , F. , Van Wieren , S. E. and Sobhan , I. 2007 . Estimation of green grass/herb biomass form air-borne hyperspectral imagery using spectral indices and partial least squares regression . International Journal of Applied Earth Observation , 9 : 414 – 424 .
   Web of Science ®Google Scholar
• Clark , R. N. and Roush , T. L. 1984 . Reflectance spectroscopy – quantitative analysis techniques for remote sensing applications . Journal of Geophysical Research , 89 : 6329 – 6340 .
   Web of Science ®Google Scholar
• Curran , P. J. 1989 . Remote-sensing of foliar chemistry . Remote Sensing of Environment , 30 : 271 – 278 .
   Web of Science ®Google Scholar
• Curran , P. J. , Dungan , J. L. and Peterson , D. L. 2001 . Estimating the foliar biochemical concentration of leaves with reflectance spectrometry: testing the Kokaly and Clark methodologies . Remote Sensing of Environment , 76 : 349 – 359 .
   Web of Science ®Google Scholar
• Demetriades-Shah , T. H. , Steven , M. D. and Clark , J. A. 1990 . High resolution derivative spectra in remote sensing . Remote Sensing of Environment , 33 : 55 – 64 .
   Web of Science ®Google Scholar
• Di Bella , C. , Faivre , R. , Ruget , F. , Seguin , B. , Guérif , M. , Combal , B. , Weiss , M. and Rebella , C. 2004 . Remote sensing capabilities to estimate pasture production in France . International Journal of Remote Sensing , 25 : 5359 – 5372 .
   Web of Science ®Google Scholar
• Elvidge , C. D. and Chen , Z. K. 1995 . Comparison of broad-band and narrow-band red and near-infrared vegetation index . Remote Sensing of Environment , 54 : 38 – 48 .
   Web of Science ®Google Scholar
• Elvidge , C. D. and Lyon , R. J.P. 1985 . Influence of rock-soil spectral variation on the assessment of green biomass . Remote Sensing of Environment , 17 : 265 – 279 .
   Web of Science ®Google Scholar
• Everitt , J. H. , Escobar , D. E. and Richardson , A. J. 1989 . Estimating grassland phytomass production with near-infrared and mid-infrared spectral variables . Remote Sensing of Environment , 30 : 257 – 261 .
   Web of Science ®Google Scholar
• Filella , I. and Penuelas , J. 1994 . The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status . International Journal of Remote Sensing , 15 : 1459 – 1470 .
   Web of Science ®Google Scholar
• Forina , M. , Lanteri , S. , Oliveros , M. C.C. and Millan , C. P. 2004 . Selection of useful predictors in multivariate calibration . Analytical and Bioanalytical Chemistry , 380 : 397 – 418 .
   PubMed Web of Science ®Google Scholar
• Friedl , M. A. , Michaelsen , J. , Davis , F. W. , Walker , H. and Schimel , D. S. 1994 . Estimating grassland biomass and leaf area index using ground and satellite data . International Journal of Remote Sensing , 15 : 1401 – 1420 .
   Web of Science ®Google Scholar
• Gao , J. 2006 . Quantification of grassland properties: how it can benefit from geoinformatic technologies? . International Journal of Remote Sensing , 27 : 1351 – 1365 .
   Web of Science ®Google Scholar
• Gao , X. , Huete , A. R. , Ni , W. and Miura , T. 2000 . Optical-biophysical relationships of vegetation spectra without background contamination . Remote Sensing of Environment , 74 : 609 – 620 .
   Web of Science ®Google Scholar
• Geerken , R. , Batikha , N. , Celis , D. and Depauw , E. 2005 . Differentiation of rangeland vegetation and assessment of its status: field investigations and MODIS and SPOT VEGETATION data analyses . International Journal of Remote Sensing , 26 : 4499 – 4526 .
   Web of Science ®Google Scholar
• Haboudane , D. , Miller , J. R. , Pattey , E. and Zarco-Tejada , P. J. 2004 . Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture . Remote Sensing of Environment , 90 : 337 – 352 .
   Web of Science ®Google Scholar
• Hall , D. O. and Rao , K. K. 1987 . Photosynthesis , 4th , London, FL : Edward Arnold .
   Google Scholar
• Hansen , P. M. and Schjoerring , J. K. 2003 . Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression . Remote Sensing of Environment , 86 : 542 – 553 .
   Web of Science ®Google Scholar
• Holzgang , O. 2001 . Assessing above-ground phytomass in an alpine region using a hand-held radiometer . Botanica Helvetica , 111 : 73 – 85 .
   Google Scholar
• Huang , Z. , Turner , B. J. , Dury , S. J. , Wallis , I. R. and Foley , W. J. 2004 . Estimating foliage nitrogen concentration from HYMAP data using continuum removal analysis . Remote Sensing of Environment , 93 : 18 – 29 .
   Web of Science ®Google Scholar
• Huete , A. R. , Jackson , R. D. and Post , D. F. 1985 . Spectral response of a plant canopy with different soil backgrounds . Remote Sensing of Environment , 17 : 37 – 54 .
   Web of Science ®Google Scholar
• Huete , A. R. 1988 . A soil-adjusted vegetation index (SAVI) . Remote Sensing of Environment , 25 : 295 – 309 .
   Web of Science ®Google Scholar
• Huete , A. , Justice , C. and Liu , H. 1994 . Development of vegetation and soil indexes for MODIS_EOS . Remote Sensing of Environment , 49 : 224 – 234 .
   Web of Science ®Google Scholar
• Hurcom , S. J. and Harrison , A. R. 1998 . The NDVI and spectral decomposition for semi-arid vegetation abundance estimation . International Journal of Remote Sensing , 19 : 3109 – 3125 .
   Web of Science ®Google Scholar
• Ikeda , H. , Okamoto , K. and Fukuhara , M. 1999 . Estimation of aboveground grassland phytomass with a growth model using Landsat TM and climate data . International Journal of Remote Sensing , 20 : 2283 – 2294 .
   Web of Science ®Google Scholar
• Kato , T. , Tang , Y. H. , Gu , S. , Cui , X. , Hirota , M. , Du , M. , Li , Y. , Zhao , X. and Oikawa , T. 2004 . Seasonal patterns of gross primary production and ecosystem respiration in an alpine meadow ecosystem on the Qinghai–Tibetan Plateau . Journal of Geophysical Research , 109 D12109
   Web of Science ®Google Scholar
• Kokaly , R. F. and Clark , R. N. 1999 . Spectroscopic determination of leaf biochemistry using band depth analysis of absorption features and stepwise multiple linear regression . Remote Sensing of Environment , 67 : 267 – 287 .
   Web of Science ®Google Scholar
• Kokaly , R. F. , Despain , D. G. , Clark , R. N. and Livo , K. E. 2003 . Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data . Remote Sensing of Environment , 84 : 437 – 456 .
   Web of Science ®Google Scholar
• Li , W. and Zhou , X. 1998 . “ Ecosystems of Qingha–Xizang (Tibetan) Plateau and approach for their sustainable management ” . In The Series of Studies on Qinghai–Xizang (Tibetan) Plateau , 23 23 23 – 47 . Guangzhou : Guangdong Science & Technology Press .
   Google Scholar
• Liu , H. Q. and Huete , A. R. 1995 . A feedback based modification of the NDVI to minimize canopy background and atmospheric noise . IEEE Transactions on Geoscience and Remote Sensing , 33 : 457 – 465 .
   Web of Science ®Google Scholar
• McCoy , R. M. 2005 . Field Methods in Remote Sensing , 15 – 16 . New York : Guilford Press .
   Google Scholar
• Martens , H. and Martens , M. 2000 . Modified Jack-knife estimation of parameter uncertainty in bilinear modeling by partial least squares regression (PLSR) . Food Quality and Preference , 11 : 5 – 16 .
   Web of Science ®Google Scholar
• Mirik , M. , Norland , J. E. , Crabtree , R. L. and Biondini , M. E. 2005 . Hyperspectral one-meter-resolution remote sensing in Yellowstone National Park, Wyoming: II. Biomass . Rangeland Ecology and Management , 58 : 459 – 465 .
   Web of Science ®Google Scholar
• Monteith , J. L. 1972 . Solar radiation and productivity in tropical ecosystems . Journal of Applied Ecology , 9 : 747 – 766 .
   Web of Science ®Google Scholar
• Moreau , S. , Bosseno , R. , Gu , X. F. and Baret , F. 2003 . Assessing the biomass dynamics of Andean befedal and totora high-protein wetland grasses from NOAA/AVHRR . Remote Sensing of Environment , 85 : 516 – 529 .
   Web of Science ®Google Scholar
• Mutanga , O. and Skidmore , A. K. 2004a . Narrow band vegetation indices solve the saturation problem in biomass estimation . International Journal of Remote Sensing , 25 : 1 – 16 .
   Web of Science ®Google Scholar
• Mutanga , O. and Skidmore , A. K. 2004b . Hyperspectral band depth analysis for a better estimation of grass biomass (Cenchrus ciliaris) measured under controlled laboratory conditions . International Journal of Applied Earth Observation and Geoinformation , 5 : 87 – 96 .
   Google Scholar
• Qi , J. , Chehbouni , A. , Huete , A. R. , Kerr , Y. H. and Sorooshian , S. 1994 . A modified soil adjusted vegetation index . Remote Sensing of Environment , 48 : 119 – 126 .
   Web of Science ®Google Scholar
• Pearson , R. L. and Miller , L. D. 1972 . Remote Mapping of Standing Crop Biomass for Estimation of the Productivity of the Short-grass Prairie, Pawnee National Grasslands, Colorado , Ann Arbor, MI : ERIM .
   Google Scholar
• Richardson , A. J. and Wiegand , C. L. 1977 . Distinguishing vegetation from soil background information (by gray mapping of Landsat MSS data) . Photogrammetric Engineering and Remote Sensing , 43 : 1541 – 1552 .
   Web of Science ®Google Scholar
• Roujean , J. L. and Breon , F. M. 1995 . Estimating PAR absorbed by vegetation from bidirectional reflectance measurements . Remote Sensing of Environment , 51 : 375 – 384 .
   Web of Science ®Google Scholar
• Rouse , J. W. , Haas , R. H. , Schell , J. A. , Deering , D. W. and Harlan , J. C. 1974 . Monitoring the vernal advancements and retrogradation of natural vegetation. NASA/GSFC, Final Report Greenbelt, , MD, USA
   Google Scholar
• Roy , P. S. , Pant , D. N. and Jonna , S. 1991 . Evaluation of grasslands and spectral reflectance relationship to its biomass in Kanha National Park (M.P.), India . Geocarto-International Journal of Remote Sensing , 6 : 39 – 45 .
   Google Scholar
• Sellers , P. J. 1985 . Canopy reflectance, photosynthesis and transpiration . International Journal of Remote Sensing , 6 : 1335 – 1372 .
   Web of Science ®Google Scholar
• Thenkabail , P. S. , Smith , R. B. and De Pauw , E. 2000 . Hyperspectral vegetation indices and their relationships with agricultural crop characteristics . Remote Sensing of Environment , 71 : 158 – 182 .
   Web of Science ®Google Scholar
• Todd , S. W. , Hoffer , R. M. and Milchunas , D. G. 1998 . Biomass estimation on grazed and ungrazed rangelands using spectral indices . International Journal of Remote Sensing , 19 : 427 – 438 .
   Web of Science ®Google Scholar
• Tsai , F. and Philpot , W. 1998 . Derivative analysis of hyperspectral data . Remote Sensing of Environment , 66 : 41 – 51 .
   Web of Science ®Google Scholar
• Tucker , C. J. 1977 . Spectral estimation of grass canopy variables . Remote Sensing of Environment , 6 : 11 – 26 .
   Web of Science ®Google Scholar
• Wold , H. 1982 . “ Soft modeling: the basic design and dome extensions ” . In Systems under Indirect Observations: Causality, structure, prediction , Edited by: Wold , H. and Joreskog , K. G. 1 – 54 . Amsterdam, FL : Elsevier .
   Google Scholar
• Wold , S. , Sjostrom , M. and Eriksson , L. 2001 . PLSR: a basic tool of chemometrics . Chemometrics and Intelligent Laboratory Systems. , 58 : 109 – 130 .
   Web of Science ®Google Scholar
• Wylie , B. K. , Denda , I. , Pieper , R. D. , Harrington Jr , J. A. , Reed , B. C. and Southwood , G. M. 1995 . Satellite-based herbaceous biomass estimates in the pastoral zone of Niger . Journal of Range Management , 48 : 159 – 164 .
   Google Scholar
• Wylie , B. K. , Meyer , D. J. , Tieszen , L. L. and Mannel , S. 2002 . Satellite mapping of surface biophysical parameters at the biome scale over the North American grasslands. A case study . Remote Sensing of Environment , 79 : 266 – 278 .
   Web of Science ®Google Scholar
• Xu , B. , Yang , X. C. , Tao , W. G. , Qin , Z. H. , Liu , H. Q. , Miao , J. M. and Bi , Y. Y. 2008 . MODIS-based remote sensing monitoring of grass production in China . International Journal of Remote Sensing , 29 : 5313 – 5327 .
   Web of Science ®Google Scholar