The ATI-ET Triangle Model: A Novel Approach to Estimate Soil Moisture Applied to MODIS Data

Abstract

A simple soil moisture (SM) estimation method is proposed using apparent thermal inertia (ATI) and evapotranspiration (ET) data. Among the methods of estimating SM by using thermal infrared (TIR) remote sensing, the ATI method is widely used in bare soil and low vegetation areas. However, large surface ET will cause ATI error, resulting in lower accuracy of SM estimation. To overcome this problem, the potential of ATI-ET space for estimating the SM of bare and vegetated farmland in the dry season (no irrigation) is studied. ATI and ET data were used to construct triangle feature space, and six distance parameters are extracted from the positions of random pixels in the triangle. Some correlation estimates were made to derive those parameters that were useful for SM estimation, which were three in total. The SM estimation model consisting of these three parameters was built. Compared with the ATI model, the ATI-ET triangle model can not only be applied to areas with high ET, but also has higher accuracy in estimating SM. The ATI-ET triangle model is more suitable for application in bare soil and low vegetation areas. As the Normalized Difference Vegetation Index increases, the accuracy of the model estimates decreases. To show the high portability of the proposed model for SM estimation, we chose another set of in situ SM data acquired in Tibetan Plateau. The results proved the effectiveness of the model in other similar study regions.