Measuring soil moisture with active microwave: effect of vegetation

Abstract

An empirical algorithm for the retrieval of soil moisture content and surface root mean square (RMS) height from remotely sensed radar data over bare fields requiring two co-polarized channels at a frequency between 1.5 GHz and 11 GHz is presented. It gives best results for kh less than 2.5 where k is the wave number and h is the RMS height of the surface and for the local incidence angle greater than 30 degrees. Inversion results indicate that significant amounts of vegetation cause the algorithm to underestimate soil moisture and overestimate RMS height. To address this problem, a simple criteria based on the ratio of the cross-polarized return over the vv-polarized return is developed to select the areas where the inversion results are more reliable, i.e. where the vegetation is sparse enough. In order to assess the inversion accuracy, the derived soil moisture values are compared with in-situ measurements collected over a variety of scenes between 1989 and 1994. The experiments involved are Washita'92, Washita'94, EFEDA'91. Both spaceborne (SIR-C) and airborne (AIRSAR) data are used in the test. The studied areas include an agricultural area in the Mid-West (Washita) and an agricultural area in a semi-arid climate (EFEDA). Over this large sample of conditions, the RMS error in the soil moisture estimate is found to be 3.5% and the RMS error in the RMS height estimate is less than 0.35 cm absolute for bare or slightly vegetated surfaces. The algorithm accuracy over areas with intermediate vegetation cover are discussed.