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To develop an operational methodology for estimating soil moisture and crop biophysical parameters and to generate a crop cover map, backscattering signatures of vegetation canopies are investigated using multitemporal Radarsat synthetic aperture radar (SAR) data over a predominantly cotton-growing area in India during low to peak crop growth stage. A simple parameterization of the water-cloud model with volumetric soil moisture content (mv) and leaf area idex (LAI) is used to simulate the microwave backscattering coefficient (σ0), as it is found to be a good candidate for operational purposes as demonstrated by several workers in past. The influence of crop height (H), LAI, and mv on σ0 is investigated during peak crop growth stage. A linear relationship between LAI and crop height is derived semiempirically, and a linear zone is chosen for analysis during the peak crop-growing stage. Estimation of average volume fraction of leaves (V~l) and attenuation factor (L) by two different approaches is discussed: 1) using linear relationship between LAI versus crop height and 2) from the water-cloud model parameter (κ) estimation by iterative minimum least square error approach. It is observed that model-estimated parameters agree well with the measured values within an acceptable error limit. At lower soil moisture, mv≅0.02(cm3·cm-3), the dynamic range of σ0 is found to be about +5 dB for 0-70 cm of crop height but monotonously decreases to at a transition point, having mv≈0.38(cm3·cm-3). A positive correlation is found between backscattering coefficient and crop height till this transition point but shows a negative correlation beyond that, signifying the predominant attenuation by vegetation over soil. Differential moisture sensitivity (dσ0/dmv) of the backscattering coefficient decreases by half from 20.55 dB/(cm3·cm-3) for dry and bare-field conditions to 10.68 dB/(cm3·cm-3) for wet and crop-covered fields (mv=0.38cm3·cm-3, H=70cm), whereas differential crop height sensitivity (dσ0/dH) varies from - 0.22-0.03 dB/cm for bare-field conditions to crop-covered fields with crop height 70 cm. It is found that the percentage of relative error is smallest (2.27%) for LAI and attenuation factor estimation using the value of V~l, from LAI models, whereas it is 4.25% when estimating from the attenuation coefficient (κ) from the model.
Geoscience and Remote Sensing, IEEE Transactions on (Volume:42 , Issue: 3 )
Date of Publication: March 2004