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The role of feature-level fusion using the Dempster-Shafer rule and that of the data-level fusion in the Markov random field (MRF) context is studied to obtain an optimally segmented image. Subsequently, segments are validated, and classification accuracy for the test data is evaluated.

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 ([m.sub.v]) and leaf area idex (LAI) is used to simulate the microwave backscattering coefficient ([[sigma].sup.0]), 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 [m.sub.v] on [[sigma].sup.0] 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 croup-growing stage. Estimation of average volume fraction of leaves ([[bar.V].sub.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 (K) 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, [m.sub.v] [congruent to] 0.02 ([cm.sup.3] x [cm.sup.-3]), the dynamic range of [[sigma.sup.0] is found to be about +5 dB for 0-70 cm of crop height but monotonously decreases to null at a transition point, having [m.sub.v] [approximately equal to] 0.38 ([cm.sup.3] x [cm.sup.-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 (d[[sigma].sup.0]/d[m.sub.v]) of the backscattering coefficient decreases by half from 20.55 dB/([cm.sup.3] x [cm.sup.-3]) for dry and bare-field conditions to 10.68 dB/([cm.sup.3] x [cm.sup.-3]) for wet and crop-covered fields ([m.sub.v] = 0.38 [cm.sup.3] x [cm.sup.-3], H = 70 cm), whereas differential crop height sensitivity (d[[sigma].sup.0]/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 [[bar.V].sub.l], from LAI models, whereas it is 4.25% when estimating from the attenuation coefficient (K) from the model. Index Terms--Crop attenuation, differential moisture and crop height sensitivity, leaf area index (LAI), synthetic aperture radar (SAR) backscatter, water-cloud model.