Measurement and comparison of Leaf Area Index estimators derived from satellite remote sensing techniques

References

• Aber J. D Melillo J. M 1991 Terrestrial Ecosystems (Chicago, IL: Saunders College Publishing)
   Google Scholar
• Abrahamson W. G Hartnett D. C 1990 Pine flatwoods and dry prairies In Ecosystems of Florida, edited by R. L. Myers and J. J. Ewel (Orlando, FL: University of Central Florida Press), pp.103–149
   Google Scholar
• Barclay , H. J . 1998 . Conversion of total leaf area to projected leaf area in lodgepole pine and Douglas-Fir . Tree Physiology , 18 : 185 – 193 .
   PubMed Web of Science ®Google Scholar
• Benediktsson , J. A , Swain , P. H and Ersoy , O. K . 1990 . Neural network approaches versus statistical methods in classification of multisource remote sensing data . IEEE Transactions on Geoscience and Remote Sensing , 28 : 540 – 551 .
   Web of Science ®Google Scholar
• Bischof , H , Schneider , W and Pinz , A. J . 1992 . Multispectral classification of Landsat-images using neural networks . IEEE Transactions on Geoscience and Remote Sensing , 30 : 482 – 490 .
   Web of Science ®Google Scholar
• Carlson , T. N and Ripley , D. A . 1997 . On the relation between NDVI, fractional vegetation cover, and leaf area index . Remote Sensing of Environment , 62 : 241 – 252 .
   Web of Science ®Google Scholar
• Carter , R. E , MacKenzie , M. D and Gjerstad , D. H . 1999 . Ecological land classification in the southern loam hills of south Alabama . Forest Ecology and Management , 114 : 395 – 404 .
   Web of Science ®Google Scholar
• Chason , J. W , Baldocchi , D. D and Huston , M. A . 1991 . A comparison of direct and indirect methods for estimating forest canopy leaf area . Agricultural and Forestry Meteorology , 57 : 107 – 128 .
   Web of Science ®Google Scholar
• Chen , J. M and Cihlar , J . 1996 . Retrieving leaf area index of boreal conifer forests using Landsat TM images . Remote Sensing of Environment , 55 : 153 – 162 .
   Web of Science ®Google Scholar
• Curran P. J 1994 Attempts to drive ecosystem simulation models at local to regional scales In Environmental Remote Sensing from Regional to Global Scales, edited by G. M. Foody and P. J. Curran (New York: John Wiley and Sons), pp. 149–166
   Google Scholar
• Curran P. J Foody G. M 1994 Environmental issues at regional to global scales In Environmental Remote Sensing from Regional to Global Scales, edited by G. M. Foody and P. J. Curran (New York: John Wiley and Sons), pp. 1–7
   Google Scholar
• Datt , B . 1998 . Remote sensing of chlorophyll a, cholorphyll b, chlorophyll a+b, and total carotenoid content in Eucalyptus leaves . Remote Sensing of Environment , 66 : 111 – 121 .
   Web of Science ®Google Scholar
• Ellsworth , D. S and Reich , P. B . 1993 . Canopy structure and vertical patterns of photosynthesis and related leaf traits in a deciduous forest . Oceologia , 96 : 169 – 178 .
   PubMed Web of Science ®Google Scholar
• Fassnacht , K. S , Gower , S. T , MacKenzie , M. D , Nordheim , E. V and Lillesand , T. M . 1997 . Estimating the leaf area index of North-central Wisconsin forests using the Landsat Thematic Mapper . Remote Sensing of Environment , 61 : 229 – 245 .
   Web of Science ®Google Scholar
• Gholz , H. L . 1982 . Environmental limits on aboveground net primary production, leaf area, and biomass in vegetation zones of the Pacific Northwest . Ecology , 63 : 469 – 481 .
   Web of Science ®Google Scholar
• Gholz H. L Curran P. J Kupiec J. A Smith G. M 1997 Assessing leaf area and canopy biochemistry of Florida pine plantations using remote sensing In The Use of Remote Sensing in the Modelling of Forest Productivity. edited by G. H. Gholz, K. Nakane and H. Shimoda (Boston, MA: Kluwer), pp. 3–22
   Google Scholar
• Gopal , S and Woodcock , C . 1996 . Remote sensing of forest change using artificial neural networks . IEEE Transactions on Geoscience and Remote Sensing , 34 : 398 – 404 .
   Web of Science ®Google Scholar
• Gopal , S , Woodcock , C. E and Strahler , A. H . 1999 . Fuzzy neural network classification of global land cover from a 10 AVHRR data set . Remote Sensing of Environment , 67 : 230 – 243 .
   Web of Science ®Google Scholar
• Green , E. P , Mumby , P. J , Edwards , A. J , Clark , C. D and Ellis , A. C . 1997 . Estimating leaf area index of mangroves from satellite data . Aquatic Botany , 58 : 11 – 19 .
   Web of Science ®Google Scholar
• Haykin S 1994 Neural Networks a Comprehensive Foundation (Upper Saddle River, NJ: Prentice–Hall)
   Google Scholar
• Herwitz , S. R , Peterson , D. L and Eastman , J. R . 1990 . Thematic Mapper detection of changes in the leaf area of closed canopy pine plantations in central Massachusetts . Remote Sensing of Environment , 29 : 129 – 140 .
   Google Scholar
• IGBP 1990 The International Geosphere-Biosphere Program: A study of global change: the initial core projects (Stockholm: International Geosphere-Biosphere Programme)
   Google Scholar
• Jackson , R. D . 1983 . Spectral indices in n–Space . Remote Sensing of Environment , 13 : 409 – 421 .
   Web of Science ®Google Scholar
• Jensen J. R 1996 Introductory Digital Image Processing: A remote sensing perspective (Upper Saddle River, NJ: Prentice-Hall)
   Google Scholar
• Jensen J. R 2000 Remote Sensing of the Environment: An Earth resources perspective (Upper Saddle River, NJ: Prentice-Hall)
   Google Scholar
• Jensen , J. R , Qui , F and Ji , M . 2000 . Predictive modeling of coniferous forest age using statistical and artificial neural network approaches applied to remote sensor data . International Journal of Remote Sensing , 20 : 2805 – 2822 .
   Web of Science ®Google Scholar
• Jensen , R. R . 2002 . Spatial and temporal leaf area index dynamics in a north central Florida, USA preserve . Geocarto International , 17 : 45 – 51 .
   Google Scholar
• Keiner , L. E and Yan , X . 1998 . A neural network model for estimating sea surface chlorophyll and sediments from thematic mapper imagery . Remote Sensing of Environment , 66 : 153 – 165 .
   Web of Science ®Google Scholar
• Larcher W 1975 Physiological Plant Ecology (New York: Springer-Verlag)
   Google Scholar
• Lawrence , R. L and Ripple , W. J . 1998 . Comparisons among vegetation indices and bandwise regression in a highly disturbed, heterogeneous landscape: Mount St Helens, Washington . Remote Sensing of Environment , 64 : 91 – 102 .
   Web of Science ®Google Scholar
• Lillesand T. M Keifer R. W 2000 Remote Sensing and Image Interpretation, 4th edn (New York: John Wiley and Sons)
   Google Scholar
• Liu , Q and Huete , A . 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
• Lymburner , L , Beggs , P. J and Jacobson , C. R . 2000 . Estimation of canopy-average surface-specific leaf area using Landsat TM data . Photogrammetric Engineering and Remote Sensing , 66 : 183 – 191 .
   Web of Science ®Google Scholar
• Manly B. F 1992 The Design and Analysis of Research Studies (Cambridge: Cambridge University Press)
   Google Scholar
• Mather P. M 1987 Computer Processing of Remotely Sensed Images: An introduction (New York: John Wiley and Sons)
   Google Scholar
• Myers R. L 1990 Scrub and High Pine In Ecosystems of Florida, edited by R. L. Myers and J. J. Ewel, (Orlando, FL: University of Central Florida Press), pp.150–193
   Google Scholar
• Nel , E. M and Wessman , C. A . 1993 . Canopy transmittance models for estimating forest leaf area index . Canadian Journal of Forest Resources , 23 : 2579 – 2586 .
   Web of Science ®Google Scholar
• Pierce , L. L and Running , S. W . 1988 . Rapid estimation of coniferous forest leaf area index using a portable integrating radiometer . Ecology , 69 : 1762 – 1767 .
   Web of Science ®Google Scholar
• Platt W. J Schwartz M. W 1990 Temperate hardwood forests In Ecosystems of Florida, edited by R. L. Myers and J. J. Ewel (Orlando, FL: University of Central Florida Press), pp.194–229
   Google Scholar
• Ruimy , A , Saugier , B and Dedieu , G . 1994 . Methodology for the estimation of terrestrial net primary production from remotely sensed data . Journal of Geophysical Research , 99 : 5263 – 5283 .
   Web of Science ®Google Scholar
• Sellers , P. J , Tucker , C. J , Collatz , G. J , Los , S. O , Justice , C. O , Dazlich , D. A and Randall , D. A . 1994 . A global 1° by 1° NDVI data set for climate studies. Part 2: The generation of global fields of terrestrial biophysical parameters from the NDVI . International Journal of Remote Sensing , 15 : 3519 – 3545 .
   Web of Science ®Google Scholar
• Sellers , P , Los , S and Tucker , C . 1995 . A revised land surface parameterization (SiB2) for atmospheric GCMs. Part 2: The generation of global fields of terrestrial biophysical parameters from satellite . Journal of Climatology , 9 : 706 – 737 .
   Web of Science ®Google Scholar
• Weiss , M and Baret , F . 1999 . Evaluation of canopy biophysical variable retrieval performances from the accumulation of large swath satellite data . Remote Sensing of the Environment , 70 : 293 – 306 .
   Web of Science ®Google Scholar
• Yoshida , T and Omatu , S . 1994 . Neural network approach to land cover mapping . IEEE Transactions on Geoscience and Remote Sensing , 32 : 1103 – 1109 .
   Web of Science ®Google Scholar