Surface soil moisture knowledge is important, especially in agriculture and irrigation management. Properties of microwave remote sensing like penetration power and longer wavelength facilitate retrieval of surface soil moisture. ALOS PALSAR-2, quad polarized data are used to retrieve surface soil moisture using polarization decomposition techniques in a marginal farmer small-scale maize field. The focus of the study is to explore the utility of ALOS PALSAR-2 in retrieving surface soil moisture using the polarization decomposition technique. The demonstration of the study is carried out in Malavalli village, southern India, an agricultural predominant area. The study involves field soil moisture sampling in synchronous with satellite pass, measuring soil properties, preprocessing of SAR data, polarization decomposition, proportional analysis, regression analysis, model calibration and validation. Van Zyl decomposition gave the highest surface scattering component (43%) and reduced volumetric scattering component compared to Yamaguchi and Freeman–Durden decomposition. Surface scattering component of Yamaguchi decomposition gave a good coefficient of determination (R² = 0.8029) with field-measured surface soil moisture. The semi-empirical model (SEM) was developed using surface scattering component and depolarization ratio with adjusted R² = 0.75 at 95% confidence interval. On its comparison with existing soil moisture models, it is observed that the developed model is performing well with RMSE and AE_max of 1.81 and 2.88, respectively. Implying the applicability of ALOS PALSAR-2 in soil moisture retrieval in marginal farmer small-scale maize fields gave satisfactory results of accuracy.

地表土壤水分知识很重要，尤其是在农业和灌溉管理中。微波遥感的特性，如穿透力和更长的波长，有利于表层土壤水分的获取。在边缘农民小规模玉米田中，使用ALOS PALSAR-2四极化数据通过极化分解技术来获取表层土壤水分。研究的重点是探索ALOS PALSAR-2在利用极化分解技术获取地表土壤水分方面的实用性。该研究的论证是在印度南部农业为主的地区Malavalli村进行的。这项研究涉及与卫星通行证同步的田间土壤水分采样，测量土壤特性，SAR数据的预处理，极化分解，比例分析，回归分析，模型校准和验证。与Yamaguchi和Freeman-Durden分解相比，Van Zyl分解产生的表面散射分量最高（43％），而体积散射分量减少。Yamaguchi分解的表面散射分量具有良好的测定系数（R ²  = 0.8029），其中有实地测得的表层土壤湿度。使用表面散射分量和去极化比（ 在95％置信区间内调整R ² = 0.75 ）开发了半经验模型（SEM）。与现有的土壤水分模型进行比较后，可以发现该模型在RMSE和AE _max分别为1.81和2.88时表现良好。这暗示了ALOS PALSAR-2在边际农民小规模玉米田土壤水分获取中的适用性，获得了令人满意的精度结果。