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  Willem de Kooning (1904-1997)
A Tree in Naples (1960)

 
  • Ganguly et al., 2008. Generating vegetation leaf area index earth system data records from multiple sensors. Part 1: Theory. Remote Sens. Environ., Vol. 112(2008)4333–4343, doi:10.1016/j.rse.2008.07.014

  • Ganguly et al., 2008. Generating vegetation leaf area index earth system data records from multiple sensors. Part 2: Implementation, Analysis and Validation. Remote Sens. Environ., 112(2008)4318–4332, doi:10.1016/j.rse.2008.07.013

  • Robinson et al., 2008. An empirical approach to retrieve monthly evapotranspiration over Amazonia, Int. J. Remote Sens., Vol. 29:7045–7063, 2008.

  • Garrigues et al., 2008. Validation and Intercomparison of Global Leaf Area Index Products Derived from Remote Sensing Data, J. Geophys. Res., VOL. 113, G02028, doi:10.1029/2007JG000635, 2008.

  • Garrigues et al., 2008. Intercomparison and sensitivity analysis of leaf area index retrievals from LAI-2000, AccuPAR, and digital hemispherical photography over croplands, Agric. For. Meteorol., doi:10.1016/j.agrformet.2008.02.014.

  • Gao et al., 2008. An Algorithm to Produce Temporally and Spatially Continuous MODIS-LAI Time Series. Geophys. Res. Lett., doi: 10.1109/LGRS.2007.907971.

  • Huang et al., 2008. Stochastic transport theory for investigating the three-dimensional canopy structure from space measurement, Remote Sensing of Environ., 112:35–50, 2008.

  • Myneni et al., 2007. Large seasonal changes in leaf area of amazon rainforests. Proc. Natl. Acad. Sci., 104: 4820-4823, doi:10.1073/pnas.0611338104.

  • Huang et al., 2007. Canopy spectral invariants for remote sensing and model applications, Remote Sens. Environ., 106: 106–122.

  • Tan et al., 2006. The impact of geolocation offsets on the local spatial properties of MODIS data: Implications for validation, compositing, and band-to-band registration, Remote Sens. Environ., 105: 98–114.

  • Yang et al., 2006. Analysis of prototype collection 5 products of leaf area index from Terra and Aqua MODIS sensors, Remote Sens. Environ., 104, 297–312.

  • Ahl et al., 2006. Monitoring Spring Canopy Phenology of a Deciduous Broadleaf Forest Using MODIS, Remote Sens. Environ., 104: 88–95.

  • Huang et al., 2006. The Importance of Measurement Error for Deriving Accurate Reference Leaf Area Index Maps for Validation of the MODIS LAI Product. IEEE Trans. Geosci. Remote Sens., 44:1866-1871.

  • Yang et al., 2006. Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005. IEEE Trans. Geosci. Remote Sens., 44: 1829-1842.

  • Yang et al., 2006. MODIS Leaf Area Index Products: From Validation to Algorithm Improvement. IEEE Trans. Geosci. Remote Sens., 44: 1885-1898.

  • Baret et al., 2006. Evaluation of the representativeness of networks of sites for the validation and inter-comparison of global land biophysical products. Proposition of the CEOS-BELMANIP. IEEE Trans. Geosci. Remote Sens., 44: 1794-1803.

  • Morisette et al., 2006. Validation of global moderate resolution LAI Products: a framework proposed within the CEOS Land Product Validation subgroup IEEE Trans. Geosci. Remote Sens. 44: 1804-1817.

  • Zhang et al., 2006. Monitoring of the 2005 U.S. Corn-belt Yield using Satellite Data, Eos, s and A. Marshak [Eds], "Three-Dimensional Radiative Transfer in the Cloudy Atmosphere," Springer-Verlag, (book chapter to appear).

  • Potter et al., 2003. Satellite data help predict terrestrial carbon sinks. EOS, 84(46): pages 502 & 508.

  • Zhou et al., 2003. Comparison of seasonal and spatial variations of albedos from MODIS and the Common Land Model. J. Geophys. Res., 108(D15), 4488, doi:10.1029/2002JD003326, 2003

  • Lotsch et al., 2003. Land cover mapping in support of LAI/FPAR retrievals from EOS-MODIS and MISR: Classification methods and sensitivities to errors, Int. J. Remote Sesns. 24, 1997-2016.

  • Shabanov et al., 2003. The effect of spatial heterogeneity in validation of the MODIS LAI and FPAR algorithm over broadleaf forests, Remote Sens. Environ.,85: 410-423.

  • Wang et al., 2003. A new parameterization of canopy spectral response to incident solar radiation: case study with hyperspectral data from pine dominant forest, Remote Sens. Environ., 85:304-315.

  • Tian et al., 2002. Radiative transfer based scaling of LAI/FPAR retrievals from reflectance data of different resolutions. Remote Sens. Environ., 84:143-159.

  • Combal et al., 2002. Retrieval of Canopy Biophysical Variables from Bidirectional Refectance: Using Prior Information to solve the Ill-posed Inverse Problem, Remote Sens. Environ., 84:1-15.

  • Tian et al., 2002. Multiscale Analysis and Validation of the MODIS LAI Product. I. Uncertainty Assessment. Remote Sens. Environ., 83:414-430.

  • Tian et al., 2002. Multiscale Analysis and Validation of the MODIS LAI Product. II. Sampling Strategy. Remote Sens. Environ., 83:431-441.

  • Privette et al., 2002. Early spatial and temporal validation of MODIS LAI product in Africa. Remote Sens. Environ., 83: 232-243.

  • Myneni et al., 2002. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ., 83: 214-231.

  • Wang et al., 2001. Investigation of product accuracy as a function of input and model uncertainities: Case study with SeaWiFS and MODIS LAI/FPAR Algorithm. Remote Sens. Environ., 78:296-311.

  • Panferov et al., 2001. The role of canopy structure in the spectral variation of transmission and absorption of solar radiation in vegetation canopies. IEEE Trans. Geosci. Remote Sens., 39:241-253.

  • Tian et al., 2000. Prototyping of MODIS LAI and FPAR algorithm with LASUR and LANDSAT data. IEEE Trans. Geosci. Remote Sens., 38(5): 2387-2401.

  • Privette et al., 1998. Global validation of EOS LAI and FPAR products. The Earth Observer, 10(6):39-42.

  • Knyazikhin et al., 1998. Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. J. Geophys. Res., 103:32,257-32,276.

  • Justice, et al., 1998. The moderate resolution imaging spectroradiometer (MODIS): Land remote sensing for global change research. IEEE Trans. Geosc. Remote Sens., 36:1228-1249.

  • MODIS LAI & FPAR ATBD

  • Journal articles currently in review process can be downloaded from here.

    • Climate and Vegetation Research Group
    Dept. of Geography,Boston University. Nov-19-2008