Estimation of soil thermal inertia from geostationary Meteosat Second Generation (MSG) data

The soil thermal inertia is an important parameter in remote sensing monitoring of soil heat flux and soil moisture, while its quantitative estimation from remote sensing data is still a great challenge. Most past methods use data at specific time points, which are limited to the local times of satellite passes and sensitive to single moment observation error. Moreover, most of these methods need field measurements as extra parameters. In this paper, to overcome these deficiencies, the least square adjustment real thermal inertia analytical (LSA-TI) model is proposed to estimate real thermal inertia by making full use of the high-frequency land surface temperature (LST) measurements from geostationary satellites (i.e. Meteosat Second Generation, MSG). The thermal inertia values in North African region are calculated using this method as MSG sequences of LST measurements are adopted as the only inputs.