Abstract
Abstract. A modified water cloud model (WCM) was used to estimate the biophysical parameters of wheat crop using Sentinel-1A and Landsat-8 satellite images. The approach of combining the potential of SAR and optical data provided a new technique for the estimation of biophysical parameters of wheat crop. The biophysical parameters estimation was done using non-linear least squares optimization technique by minimizing the cost function between the backscattering coefficients (σ0) computed from the Sentinel-1A image and simulated by the modified WCM followed by look up table algorithm(LUT). The modified WCM integrates the full account of backscattering response on vegetation and bare soil by adding vegetation fraction. The modified WCM was found more sensitive than the original WCM because of incorporation of vegetation fraction (fveg) derived from the Landsat-8 satellite data. The estimated values of leaf area index (LAI) by modified WCM at VV polarization shows good correlation (R2 = 83.08 % and RMSE = 0.502 m2/m2) with the observed values. Whereas, leaf water area index (LWAI) shows comparatively poor correspondence (R2 = 76 % and RMSE = 0.560 m2/m2) with the observed data in comparison to LAI estimation at VV polarization. The performance indices show that the modified WCM was found more accurate for the estimation of wheat crop parameters during the whole growth season in Varanasi district, India. Thus, the modified WCM shows significant potential for the accurate estimation of LAI and LWAI of wheat crop on incorporating both SAR and optical satellite data.
Highlights
Earth surface vegetation parameters have been identified as the most important physical properties of terrestrial surfaces due to their specific roles in atmosphere interactions and climate change studies
Vegetation monitoring can be achieved through the evaluation of their biophysical parameters such as leaf area index (LAI), leaf water area index (LWAI) and vegetation water content (VWC) etc
Figures.3 shows the relationship between simulated σ0 from modified water cloud model (WCM) and computed from Sentinel-1A satellite data
Summary
Earth surface vegetation parameters have been identified as the most important physical properties of terrestrial surfaces due to their specific roles in atmosphere interactions and climate change studies. This parameter regulates the energy exchanges between the earthatmosphere interfaces, and dominates the functioning of hydrological processes through modification of interception, infiltration, and its effects on surface albedo, roughness and evapotranspiration etc. WCM considers only the single scattering from ground and vegetation slab. It does not include the multiple scattering from the vegetation- soil layers
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