@Article{MaireMVPLBSN:2011:LeArIn,
               author = "le Maire, Guerric and Marsden, Claire and Verhoef, Wouter and 
                         Ponzoni, Flavio Jorge and Lo Seen, Danny and Begue, Agnes and 
                         Stape, Jose-Luiz and Nouvellon, Yann",
          affiliation = "CIRAD, UPR 80, Sc UMR Eco\&Sols, Persyst, F-34060 Montpellier 01, 
                         France and CIRAD, UMR TETIS, F-34093 Montpellier 5, France and 
                         Univ Twente, Fac Geoinformat Sci \& Earth Observat ITC, NL-7500 
                         AE Enschede, Netherlands and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and CIRAD, UMR TETIS, F-34093 Montpellier 5, 
                         France and CIRAD, UMR TETIS, F-34093 Montpellier 5, France and N 
                         Carolina State Univ, Dept Forestry \& Environm Sci, Raleigh, NC 
                         27695 USA and Univ Sao Paulo, IAG, Dept Ciencias Atmosfer, 
                         BR-05508 Sao Paulo, Brazil",
                title = "Leaf area index estimation with MODIS reflectance time series and 
                         model inversion during full rotations of Eucalyptus plantations",
              journal = "Remote Sensing of Environment",
                 year = "2011",
               volume = "115",
               number = "2",
                pages = "586--599",
                month = "Feb.",
             keywords = "Leaf area index, Remote sensing, MOD13Q1, Radiative transfer 
                         model, PROSAIL, GESAVI, Eucalypt, CBERS , OPTICAL-PROPERTIES, 
                         VEGETATION INDEX, BIDIRECTIONAL REFLECTANCE, USE EFFICIENCY, 
                         CANOPY, IMAGERY, FOREST, CHLOROPHYLL, RESOLUTION, GLOBULUS.",
             abstract = "The leaf area index (LAI) of fast-growing Eucalyptus plantations 
                         is highly dynamic both seasonally and interannually, and is 
                         spatially variable depending on pedo-climatic conditions. LAI is 
                         very important in determining the carbon and water balance of a 
                         stand, but is difficult to measure during a complete stand 
                         rotation and at large scales. Remote-sensing methods allowing the 
                         retrieval of LAI time series with accuracy and precision are 
                         therefore necessary. Here, we tested two methods for LAI 
                         estimation from MODIS 250m resolution red and near-infrared (NIR) 
                         reflectance time series. The first method involved the inversion 
                         of a coupled model of leaf reflectance and transmittance 
                         (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative 
                         transfer (4SAIL2). Model parameters other than the LAI were either 
                         fixed to measured constant values, or allowed to vary seasonally 
                         and/or with stand age according to trends observed in field 
                         measurements. The LAI was assumed to vary throughout the rotation 
                         following a series of alternately increasing and decreasing 
                         sigmoid curves. The parameters of each sigmoid curve that allowed 
                         the best fit of simulated canopy reflectance to MODIS red and NIR 
                         reflectance data were obtained by minimization techniques. The 
                         second method was based on a linear relationship between the LAI 
                         and values of the GEneralized Soil Adjusted Vegetation Index 
                         (GESAVI), which was calibrated using destructive LAI measurements 
                         made at two seasons, on Eucalyptus stands of different ages and 
                         productivity levels. The ability of each approach to reproduce 
                         field-measured LAI values was assessed, and uncertainty on results 
                         and parameter sensitivities were examined. Both methods offered a 
                         good fit between measured and estimated LAI (R(2) = 0.80 and R(2) 
                         = 0.62 for model inversion and GESAVI-based methods, 
                         respectively), but the GESAVI-based method overestimated the LAI 
                         at young ages.",
                  doi = "10.1016/j.rse.2010.10.004",
                  url = "http://dx.doi.org/10.1016/j.rse.2010.10.004",
                 issn = "0034-4257",
             language = "en",
           targetfile = "galvao.pdf",
        urlaccessdate = "28 abr. 2024"
}