Spatio-temporal estimation of soil moisture in a tropical region using a remote sensing algorithm

To achieve a soil moisture estimation (m_s) in an accurate way is crucial to understand the water cycle response and avoid traditional runoff estimations where the m_s is assumed as a constant value. The aim of this study is the implementation of optical-radar images into a model to estimate m_s in the Zapotes Lagoon System in Tabasco, Mexico. The satellite images used were Landsat TM and ETM+ sensors, Envisat and also in situ measurements and MDT were available. The field measurements at the soil profile showed a clear pattern of the water movement into the basin corresponding to the lower parts of the system (lagoons). The land use analysis obtained with the optical images indicated a strong change in the floodplain due to the construction of protect barriers around the Villahermosa city losing its hydrological capacity. This allows the identification of three main covers (soil, vegetation and air) that were monitored and feed to the model (MIMICS) in order to estimate iris using the Envisat image. Results provided an empirical equation that relates the m, with the backscattering coefficient.