Validation of LAI and assessment of winter wheat status using spectral data and vegetation indices from SPOT VEGETATION and simulated PROBA-V images

Due to the information gap between the VEGETATION sensors and Sentinel-3 mission, the Belgian state decided to build a small satellite, Project for Onboard Autonomy-Vegetation PROBA-V, to ensure the continuity of the data record for vegetation studies. In this study, simulated PROBA-V data generated by the Landsat Thematic Mapper TM were used to evaluate the potential of this mission to assess winter wheat status. The root mean square error RMSE of PROBA-V's leaf area index LAI, which was generated using the exponential method and the interpolation method, is 0.33 and 0.96 for March 2011 and 1.40 and 3.33 for May 2011, respectively. Système Pour l'Observation de la Terre SPOT VEGETATION's LAI does not show a significant relationship with the reference LAI values except for the LAI values during the stem elongation 100% phenological stage generated using the exponential method correlation coefficient, r = 0.91; p = 0.01. For the tillering and stem elongation 100% phenological stages, linear regression models for the fraction of absorbed photosynthetically active radiation FAPAR with PROBA-V's normalized difference vegetation index NDVI were developed coefficient of determination, R2, of 0.94 and 0.88. Exponential models for LAI R2 of 0.91 and 0.93 and fresh weight of above-ground biomass AGBf R2 of 0.90 and 0.93 with PROBA-V's near-infrared NIR and visible and near-infrared bands VNIR B2 were developed accordingly. The assessment of winter wheat status showed that the highest and the lowest values of PROBA-V's simulated data SD, i.e. NDVI, normalized difference water index NDWI, and LAI of Field 2 and Field 4, correspond to the ground-measured biometric parameters.