Hyperspectral indices for characterizing upland peat composition

References

• AIG Analytical Geophysics (available online), AIG HyMap USA group shoot USA: Tutorial – Getting Started With Your HyMap Data http://www.aigllc.com/data_acq/hym_tut.htm
   Google Scholar
• Baird A Beckwith C Heathwaite L 1997 Water movement in undamaged blanket peats In Blanket Mire Degradation: Causes, consequences and challenges, edited by J. H Tallis, R. Meade and P.D. Hulme (Aberdeen: Macaulay Land Use Research Institute), pp.128–139
   Google Scholar
• Ben-Dor , E , Inbar , Y and Chen , Y . 1997 . The reflectance spectra of organic matter in the visible near-infrared and short wave infrared region (400–2500 nm) during a controlled decomposition process . Remote Sensing of Environment , 61 : 1 – 15 .
   Web of Science ®Google Scholar
• Blackburn , G. A . 1998 . Quantifying chlorophylls and carotenoids at leaf and canopy scales; an evaluation of some hyperspectral approaches . Remote Sensing of Environment , 66 : 273 – 285 .
   Web of Science ®Google Scholar
• Blackford , J. J and Chambers , F. M . 1993 . Determining the degree of peat decomposition for peat-based palaeoclimatic studies . International Peat Journal , 5 : 7 – 24 .
   Google Scholar
• BNSC British National Space Centre Earth Observation News Announcement of SAR & Hyperspectral Airborne Campaign (SHAC) Data Availability http://www.bnsc.gov.uk/
   Google Scholar
• Bower , M . 1961 . The distribution of erosion in blanket peat bogs in the Pennines . Transactions of the Institute of British Geographers , 29 : 17 – 30 .
   Web of Science ®Google Scholar
• Bozkurt , S , Lucisano , M , Moreno , L and Neretnieks , I . 2001 . Peat as a potential analogue for the long-term evolution in landfills . Earth Science Reviews , 53 : 95 – 147 .
   Web of Science ®Google Scholar
• Bruce , L. M and Li , J . 2001 . Wavelets for computationally efficient hyperspectral derivative analysis . IEEE Transactions on Geoscience and Remote Sensing , 39 : 1540 – 1546 .
   Web of Science ®Google Scholar
• Burns D. A Ciurczuk E. W 1992 Handbook of Near-Infrared Analysis (New York: Marcel Decker)
   Google Scholar
• Burt T Labadz J Butcher D 1997 The hydrology and fluvial geomorphology of blanket peat: implications for integrated catchment management In Blanket Mire Degradation: Causes, Consequences and Challenges, edited by J.H. Tallis, R. Meade and P.D. Hulme (Aberdeen: Macaulay Land Use Research Institute), pp. 121–127
   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
• CIRES University of Colorado, Boulder Atmospheric removal program (ATREM). http://cires.colorado.edu/cses/atrem.html
   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 . 2001 . Spectrometry for ecological applications . International Journal of Applied Earth Observation and Geoinformation , 3 : 305 – 312 .
   Google Scholar
• Dawson , T. P , Curran , P. J and Plummer , S. E . 1998 . The biochemical decomposition of slash pine needles from reflectance spectra using neural networks . International Journal of Remote Sensing , 19 : 1433 – 1438 .
   Web of Science ®Google Scholar
• Demetriades-Shah , T. H and Steven , M. D . 1990 . High resolution derivative spectra in remote sensing . Remote Sensing of Environment , 33 : 55 – 64 .
   Web of Science ®Google Scholar
• Garnett , M. H , Ineson , P and Stevenson , A. C . 2000 . Effects of burning and grazing on carbon sequestration in a Pennine blanket bog, UK . The Holocene , 10 : 729 – 736 .
   Web of Science ®Google Scholar
• Gillon , D , Joffre , R and Dardenne , P . 1993 . Predicting the stage of decay of decomposing leaves by near infrared reflectance spectroscopy . Canadian Journal of Forest Research , 23 : 2552 – 2559 .
   Web of Science ®Google Scholar
• Gillon , D , Joffre , R and Ibrahima , A . 1999 . Can litter decomposability be predicted by near infrared reflectance spectroscopy . Ecology , 80 : 175 – 186 .
   Web of Science ®Google Scholar
• Goetz , A. F. H , Boardman , J. W , Kindel , B and Heidebrecht , K. B . 1997 . Atmospheric corrections: on deriving surface reflectance from hyperspectral imagers . Proceedings of the SPIE , 3118 : 14 – 22 .
   Google Scholar
• Gong , P , Pu , R and Yu , B . 1997 . Conifer species recognition: an exploratory analysis of in situ hyperspectral data . Remote Sensing of Environment , 29 : 350 – 357 .
   Google Scholar
• Gorham , E . 1991 . Northern peatlands: role in the carbon cycle and probable responses to climatic warming . Ecological Applications , 1 : 182 – 195 .
   PubMed Web of Science ®Google Scholar
• Green , R. O , Eastwood , C. M , Sarture , C. M , Chrien , T. G , Aronsson , M , Chippendale , B. J , Faust , J. A , Pauri , B. E , Chovit , C. J , Solis , M , Olah , M. R and Williams , O . 1998 . Imaging spectrometry and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) . Remote Sensing of Environment , 65 : 227 – 248 .
   Web of Science ®Google Scholar
• Hobbs , N. B . 1986 . Mire morphology and the properties and behaviour of some British and foreign peats . Quarterly Journal of Engineering Geology , 16 : 7 – 80 .
   Web of Science ®Google Scholar
• Huerte , A. R and Escadafal , R . 1991 . Assessment of biophysical soil properties through spectral decomposition techniques . Remote Sensing of Environment , 35 : 149 – 159 .
   Web of Science ®Google Scholar
• Huguenin , R. L and Jones , J. L . 1986 . Intelligent information extraction from reflectance spectra: absorption and band positions . Journal of Geophysical Research , 19 : 9585 – 9598 .
   Web of Science ®Google Scholar
• Hulme P. D Birnie R. V 1997 Grazing-induced degradation of blanket mire: its measurement and management In Blanket Mire Degradation: Causes, consequences and challenges, edited by J.H. Tallis, R. Meade and P.D. Hulme (Aberdeen: Macaulay Land Use Research Institute), pp. 163–173
   Google Scholar
• Ishida , T , Ando , H and Fukuhara , M . 1991 . Estimation of complex refractive-index of soil particles and its dependence on soil chemical-properties . Remote Sensing of Environment , 38 : 173 – 182 .
   Web of Science ®Google Scholar
• Joffre , R , Gillon , D , Dardenne , P , Agneessens , R and Biston , R . 1992 . The use of near-infrared reflectance spectroscopy in litter decomposition studies . Annales des Sciences Forrestières , 49 : 481 – 488 .
   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 linear regression . Remote Sensing of Environment , 67 : 267 – 287 .
   Web of Science ®Google Scholar
• Krishnan , P , Alexander , J. D , Butler , B. J and Hummel , J. W . 1980 . Reflectance technique for predicting soil organic matter . Soil Science Society of America Journal , 44 : 1282 – 1285 .
   Web of Science ®Google Scholar
• Latter , P. M , Howson , G , Howard , D. M and Scott , W. A . 1997 . Long-term study of litter decomposition on a Pennine peat bog: which regression? . Oecologia , 113 : 94 – 103 .
   PubMed Web of Science ®Google Scholar
• Liu , W. D , Baret , F , Gu , X. F , Tong , Q. X , Zheng , L. F and Zhang , B . 2002 . Relating soil surface moisture to reflectance . Remote Sensing of Environment , 81 : 238 – 246 .
   Web of Science ®Google Scholar
• Lobell , D. B and Asner , G. P . 2002 . Moisture effects on soil reflectance . Soil Science Society of America Journal , 66 : 722 – 727 .
   Web of Science ®Google Scholar
• McLellan , T. M , Martin , M. E and Aber , J. D . 1991a . Comparison of wet chemistry and near infrared reflectance measurements of carbon-fraction chemistry and nitrogen concentration of forest foliage . Canadian Journal of Forest Research , 21 : 1689 – 1693 .
   Web of Science ®Google Scholar
• McLellan , T. M , Aber , J. D , MartiN , M. E , Melillo , J. M and Nadelhoffer , K. J . 1991b . Determination of nitrogen, lignin and cellulose content of decomposing leaf material by near-infrared reflectance spectroscopy . Canadian Journal of Forest Research , 21 : 1684 – 1688 .
   Web of Science ®Google Scholar
• McMorrow J. M Cutler M. E. J Evans M. E 2002 Synergy of HyMap and digital elevation data for the analysis of upland peat erosion patterns and composition SAR and Hyperspectral Airborne Campaign (SHAC) final report to BNSC, London and NERC, Swindon
   Google Scholar
• McTiernan , K. B , Garnett , M. H , Mauquoy , D , Ineson , P and Couteaux , M. M . 1998 . Use of near-infrared reflectance spectroscopy (NIRS) in palaeoecological studies of peat . The Holocene , 8 : 729 – 740 .
   Web of Science ®Google Scholar
• Moore , P. D . 1995 . Biological processes controlling the development of modern peat-forming systems . International Journal of Coal Geology , 28 : 99 – 110 .
   Web of Science ®Google Scholar
• Nagler , P. L , Daughtry , C. S. T and Goward , S. N . 2000 . Plant litter and soil reflectance . Remote Sensing of Environment , 71 : 207 – 215 .
   Web of Science ®Google Scholar
• Osborne B. G Fearn T 1986 Near Infrared Spectroscopy in Food Analysis (London: Longman)
   Google Scholar
• Soukupová , J , Rock , B. N and Albrechtová , J . 2002 . Spectral characteristics of lignin and soluble phenolics in the near infrared – a comparative study . International Journal of Remote Sensing , 23 : 3039 – 3056 .
   Web of Science ®Google Scholar
• Tallis J. H 1997 The Southern Pennine experience: an overview of Blanket Mire degradation In Blanket Mire Degradation: Causes, Consequences and Challenges, edited by J.H. Tallis, R. Meade and P.D. Hulme (Aberdeen: Macaulay Land Use Research Institute), pp. 7–15
   Google Scholar
• Taylor , B. J , Parkinson , D and Parsons , W. F. J . 1989 . Nitrogen and lignin content as predictors of litter decay rates: a microcosm test . Ecology , 70 : 97 – 104 .
   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