Radiative Transfer Model parametrization for simulating the reflectance of meadow vegetation

Abstract Natural vegetation is complex and its reflectance is not easy to model. The aim of this study was to adjust the Radiative Transfer Model parameters for modelling the reflectance of heterogeneous meadows and evaluate its accuracy dependent on the vegetation characteristics. PROSAIL input parameters and reference spectra were collected during field measurements. Two different datasets were created: in the first, the input parameters were modelled using only field measurements; in the second, three input parameters were adjusted to minimize the differences between modelled and measured spectra. Reflectance was modelled using two datasets and then verified based on field reflectance using the RMSE. The average RMSE for the first dataset was equal to 0.1058, the second was 0.0362. The accuracy of the simulated spectra was analysed dependent on the value of the biophysical parameters. Better results were obtained for meadows with higher biomass value, greater LAI and lower water content.

[1]  S. Tarantola,et al.  Detecting vegetation leaf water content using reflectance in the optical domain , 2001 .

[2]  N. Zhang,et al.  Estimating leaf area index by inversion of reflectance model for semiarid natural grasslands , 2009 .

[3]  A. Skidmore,et al.  Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland , 2008 .

[4]  Qing Xiao,et al.  Unified Optical-Thermal Four-Stream Radiative Transfer Theory for Homogeneous Vegetation Canopies , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Michael E. Schaepman,et al.  Estimating canopy water content using hyperspectral remote sensing data , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[6]  W. Verhoef,et al.  Coupled soil–leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data , 2007 .

[7]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modeling: The Scattering by Arbitrarily Inclined Leaves (SAIL) model , 1984 .

[8]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[9]  S. Jacquemoud.  Inversion of the PROSPECT + SAIL Canopy Reflectance Model from AVIRIS Equivalent Spectra: Theoretical Study , 1993 .

[10]  John R. Miller,et al.  Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture , 2004 .

[11]  A. Skidmore,et al.  Mapping grassland leaf area index with airborne hyperspectral imagery : a comparison study of statistical approaches and inversion of radiative transfer models , 2011 .

[12]  Lalit Kumar,et al.  Imaging Spectrometry and Vegetation Science , 2001 .

[13]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[14]  Roberta E. Martin,et al.  PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments , 2008 .

[15]  A. Jarocińska.  Ocena skuteczności modeli transferu promieniowania w badaniach stanu roślinności łąk , 2012 .

[16]  V. Demarez,et al.  A Modeling Approach for Studying Forest Chlorophyll Content , 2000 .