Evaluating vegetation indices for assessing productivity along a tropical rain forest chronosequence in Western Amazonia

References

• Aguilar-Amuchastegui, N., Henebry, G.M. 2006. Monitoring sustainability in tropical forests: how changes in canopy spatial pattern can indicate forest stands for biodiversity surveys. IEEE Geosci. Remote Sens. Lett. 3: 329-333.
   Google Scholar
• Aguilar-Amuchastegui, N., Henebry, G.M. 2008. Characterizing tropical forest spatio-temporal heterogeneity using the Wide Dynamic Range Vegetation Index (WDRVI). Int. J. Remote Sens. 29: 7285-7291.
   Google Scholar
• Chander, G., Markham, B.L., Helder, D.L. 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sens. Environ. 113: 893-903.
   Google Scholar
• Chen, W.R., Henebry, G.M. 2010. Spatio-spectral heterogeneity analysis using EO-1 Hyperion imagery. Comput. Geosci. 36: 167-170.
   Google Scholar
• Ciganda, V., Gitelson, A., Schepers, J. 2008. Vertical profile and temporal variation of chlorophyll in maize canopy: quantitative "crop vigor" indicator by means of reflectance-based techniques. Agron. J. 100: 1409-1417.
   Google Scholar
• Congalton, R.G. 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens. Environ. 37: 35-46.
   Google Scholar
• DeFries, R., Achard, F., Brown, S., Herold, M., Murdiyarso, D., Schlamadinger, B., de Souza, C. 2007. Earth observations for estimating greenhouse gas emissions from deforestation in developing countries. Environ. Sci. Policy 10: 385-394.
   Google Scholar
• Ewusie, J.Y. 1992. Phenology in tropical ecology. Accra: Ghana Universities Press.
   Google Scholar
• Feldpausch, T.R., Rondon, M.A., Fernandes, E.C.M., Riha, S.J., Wandelli, E. 2004. Carbon and nutrient accumulation in secondary forests regenerating on pastures in central Amazonia. Ecol. Appl. 14: S164-S176.
   Google Scholar
• Garbulsky, M.F., Penuelas, J., Papale, D., Filella, I. 2008. Remote estimation of carbon dioxide uptake by a Mediterranean forest. Glob. Change Biol. 14: 2860-2867.
   Google Scholar
• Gentry, A.H. 1992. Tropical forest biodiversity: distributional patterns and their conservational significance. Oikos 63: 19-28.
   Google Scholar
• Gibbs, H.K., Brown, S., Niles, J.O., Foley, J.A. 2007. Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ. Res. Lett. 2: DOI: 10.1088/1748-9326/1082/1084/045023.
   Google Scholar
• Gitelson, A.A. 2004. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. J. Plant Physiol. 161: 165-173.
   Google Scholar
• Gitelson, A.A., Gritz, Y., Merzlyak, M.N. 2003a. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. J. Plant Physiol. 160: 271-282.
   Google Scholar
• Gitelson, A.A., Verma, S.B., Viña, A., Rundquist, D.C., Keydan, G., Leavitt, B., Arkebauer, T.J., Burba, G.G., Suyker, A.E. 2003b. Novel technique for remote estimation of CO2 flux in maize. Geophys. Res. Lett. 30:486, doi:410.1029/2002GL016543.
   Google Scholar
• Gitelson, A.A., Viña, A., Arkebauer, T.J., Rundquist, D.C., Keydan, G., Leavitt, B. 2003c. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophys. Res. Lett. 30:1248, doi: 1210.1029/2002GL016450.
   Google Scholar
• Gitelson, A.A., Viña, A., Ciganda, V., Rundquist, D.C., Arkebauer, T.J. 2005. Remote estimation of canopy chlorophyll content in crops. Geophys. Res. Lett. 32: L08403, doi:08410.01029/02005GL022688.
   Google Scholar
• Gitelson, A.A., Keydan, G.P., Merzlyak, M.N. 2006a. Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophys. Res. Lett. 33: DOI: 10.1029/2006GL026457.
   Google Scholar
• Gitelson, A.A., Viña, A., Verma, S.B., Rundquist, D.C., Arkebauer, T.J., Keydan, G., Leavitt, B., Ciganda, V., Burba, G.G., Suyker, A.E. 2006b. Relationship between gross primary production and chlorophyll content in crops: implications for the synoptic monitoring of vegetation productivity. J. Geophys. Res.-Atmos. 111: D08S11, doi: 10.1029/2005JD006017.
   Google Scholar
• Gitelson, A.A., Viña, A., Masek, J.G., Verma, S.B., Suyker, A.E. 2008. Synoptic monitoring of gross primary productivity of maize using Landsat data. IEEE Geosci. Remote Sens. Lett. 5: 133-137.
   Google Scholar
• Henebry, G.M., Viña, A., Gitelson, A.A. 2004. The Wide Dynamic Range Vegetation Index and its potential utility for Gap Analysis. Gap Analysis Program Bulletin 12: 50-56.
   Google Scholar
• Hernández-Camacho, J.A., Hurtado-Guerra, A., Ortiz-Quijano, R., Walschburger, T. 1992. Unidades biogeográficas de Colombia. In: Halffter, G., ed. La diversidad biológica de Iberoamérica. Instituto de Ecologia, Mexico D.F., Mexico.
   Google Scholar
• Holdridge, L.R. 1967. Life zone ecology. Tropical Science Center, San José, Costa Rica.
   Google Scholar
• Huete, A.R., Justice, C., van Leeuwen, W. 1996. MODIS vegetation index (MOD13). Algorithm Theoretical Basis Document. Version 2. NASA Goddard Space Flight Center, Greenbelt, Maryland 20771. USA.
   Google Scholar
• Huete, A.R., Liu, H.Q., Batchily, K., vanLeeuwen, W. 1997. A comparison of vegetation indices global set of TM images for EOS-MODIS. Remote Sens. Environ. 59: 440-451.
   Google Scholar
• Huete, A.R., Restrepo-Coupe, N., Ratana, P., Didan, K., Saleska, S.R., Ichii, K., Panuthai, S., Gamo, M. 2008. Multiple site tower flux and remote sensing comparisons of tropical forest dynamics in Monsoon Asia. Agr. Forest Meteorol. 148: 748-760.
   Google Scholar
• IPCC. 2007. Climate Change 2007: The Physical Science Basis. Cambridge University Press, New York, NY, USA.
   Google Scholar
• Jensen, J.R. 1996. Introductory digital image processing, a remote sensing perspective. Second edition. Prentice Hall., New Jersey:.
   Google Scholar
• Khurshid, K.S., Staenz, K., Sun, L.X., Neville, R., White, H.P., Bannari, A., Champagne, C.M., Hitchcock, R. 2006. Preprocessing of EO-1 Hyperion data. Can. J. Remote Sens. 32: 84-97.
   Google Scholar
• Mayaux, P., Holmgren, P., Achard, F., Eva, H., Stibig, H., Branthomme, A. 2005. Tropical forest cover change in the 1990s and options for future monitoring. Philos. T. Roy. Soc. B. 360: 373-384.
   Google Scholar
• McGuffie, K., Henderson-Sellers, A., Zhang, H., Durbridge, T.B., Pitman, A.J. 1995. Global climate sensitivity to tropical deforestation. Global and Planetary Change 10: 97-128.
   Google Scholar
• Myneni, R.B., Nemani, R.R., Running, S.W. 1997. Estimation of global leaf area index and absorbed PAR using radiative transfer models. IEEE Trans. Geosci. Electron. 35: 1380-1393.
   Google Scholar
• Nakaji, T., Ide, R., Takagi, K., Kosugi, Y., Ohkubo, S., Nasahara, K.N., Saigusa, N., Oguma, H. 2008. Utility of spectral vegetation indices for estimation of light conversion efficiency in coniferous forests in Japan. Agr. Forest Meteorol. 148: 776-787.
   Google Scholar
• Rouse, J.W., Haas Jr., R.H., Schell, J.A., Deering, D.W. 1974. Monitoring vegetation systems in the Great Plains with ERTS. pp 309-317 In: Third ERTS-1 Symposium. NASA, Washington, DC.
   Google Scholar
• Ruimy, A., Kergoat, L., Bondeau, A., Intercomparison, P.P. N.M. 1999. Comparing global models of terrestrial net primary productivity (NPP): analysis of differences in light absorption and light-use efficiency. Glob. Change Biol. 5: 56-64.
   Google Scholar
• SAS. 2004. SAS/STAT User's Guide Version 9.1. SAS Institute Inc., Cary, NC, USA.
   Google Scholar
• Suyker, A.E., Verma, S.B., Burba, G.G., Arkebauer, T.J., Walters, D.T., Hubbard, K.G. 2004. Growing season carbon dioxide exchange in irrigated and rainfed maize. Agr. Forest Meteorol. 124: 1-13.
   Google Scholar
• Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8: 127-150.
   Google Scholar
• Verma, S.B., Dobermann, A., Cassman, K.G., Walters, D.T., Knops, J.M., Arkebauer, T.J., Suyker, A.E., Burba, G.G., Amos, B., Yang, H.S., Ginting, D., Hubbard, K.G., Gitelson, A.A., Walter-Shea, E.A. 2005. Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems. Agri. Forest Meteorol. 131: 77-96.
   Google Scholar
• Viña, A., Gitelson, A.A. 2005. New developments in the remote estimation of the fraction of absorbed photosynthetically active radiation in crops. Geophys. Res. Lett. 32: L17403.
   Google Scholar
• Viña, A., Echavarria, F.R., Rundquist, D.C. 2004a. Satellite change detection analysis of deforestation rates and patterns along the Colombia-Ecuador border. Ambio 33: 118-125.
   Google Scholar
• Viña, A., Henebry, G.M., Gitelson, A.A. 2004b. Satellite monitoring of vegetation dynamics: Sensitivity enhancement by the wide dynamic range vegetation index. Geophys. Res. Lett. 31: L04503.
   Google Scholar
• Viña, A., Gitelson, A.A., Nguy-Robertson, A.L., Peng, Y. 2011. Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sens. Environ.: DOI: 10.1016/j.rse.2011.1008.1010.
   Google Scholar
• Walker, R., Moore, N.J., Arima, E., Perz, S., Simmons, C., Caldas, M., Vergara, D., Bohrer, C. 2009. Protecting the Amazon with protected areas. Proc. Natl. Acad. Sci. U.S.A. 106: 10582-10586.
   Google Scholar
• Xiao, X.M., Hagen, S., Zhang, Q.Y., Keller, M., Moore, B. 2006. Detecting leaf phenology of seasonally moist tropical forests in South America with multi-temporal MODIS images. Remote Sens. Environ. 103: 465-473.
   Google Scholar