Assessment of surface soil moisture distribution across small scale tomato fields using L band SAR data

Punithraj Gururaj,Amba Shetty,Pruthviraj Umesh

doi:10.5194/egusphere-egu2020-623

Abstract

&lt;p&gt;Soil moisture is very important in several disciplines such as agriculture, hydrology and meteorology. It can be mapped using active and passive microwave remote sensing techniques. From literature it is observed that quad polarized data acquired at L-band is sensitive to soil moisture and can map surface soil moisture at high spatial resolution. The main objective of this study is to analyze the potential use of L-band radar data for the retrieval of surface soil moisture over small scale agricultural areas under vegetation cover conditions. Study area selected for this study was Malavalli, village in Karnataka state India which falls in Tropical semi-arid region. Two radar images were acquired using the Phased Array Synthetic Aperture Radar/Advanced Land Observing Satellite (PALSAR/ALOS)-2 sensor over the study area between 23/07/2018 and 17/09/2018 which has spatial resolution of 5m. Ground Soil moisture over 30 sample sites were collected in synchronization with satellite pass over the study area. Acquired ALOS PALSAR-2 images were processed using PolSARpro (Polarimetric SAR data Processing and Education Toolbox). ALOS PALSAR-2 has been processed and lee speckle filter is applied with window size of 3*3. Surface soil moisture distribution over small scale tomato fields are mapped by adding incidence angle using Oh Model. Incidence angle map which is not available with PolSARpro (Polarimetric SAR data Processing and Education Toolbox) software was derived using the polynomial given in the leader file which was required for oh model inversion. Study site clearly shown increasing trend of soil moisture from July to September. It is interesting to note that vegetation and urban areas are clearly discriminated in the PauliRGB images. The retrieval of soil moisture using Oh model is validated using Ground truth samples. The accuracy of Oh model over small scale tomato fields with RMSE of 1.83 m&lt;sup&gt;3&lt;/sup&gt;/m&lt;sup&gt;-3&lt;/sup&gt;.&lt;/p&gt;

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