This repository provides a code to model Land Surface Temperature (LST) as one of the most important environmental factors used to monitor surface processes at local to regional scales. LST is mainly obtained from thermal infrared (TIR) remote sensing data, even though it is often limited by cloud contamination. Given that LST is directly involved in determining Evapotranspiration (ET), TIR remote sensing-based LST retrievals lead to discontinuities in ET calculations. Surface Energy Balance (SEB) modeling can estimate LST continuously; however, it is conducted mainly on a daily or sub-daily temporal resolution. Difficulties in collecting the high temporal resolution data at the watershed scale makes it impossible to implement the energy balance model with daily and sub-daily resolutions. Therefore, the monthly temporal scale has been selected for the current use of the energy balance model to estimate LST. Since it is possible to accumulate the heat fluxes during a month, the modeling has been conducted under unstable conditions, and SEB closure has performed by considering all of the heat storages in the soil-vegetation-atmosphere continuum. The methodology is described and applied in this paper: Taheri, M., Shamsi Anboohi, M., Nasseri, M., Kiavarz, M., Mohammadian, A., (2021). Monthly closure of surface energy balance to estimate land surface temperature and evapotranspiration over a watershed with a variety of land covers considering all the heat storages: Model development and evaluation, Submitted to Agricultural and Forest Meterology.
xiaositan/FSEB
This repository provides a code to model Land Surface Temperature (LST) by Surface Energy Balance (SEB) modeling. The methodology is described in paper: Taheri, M., et al., (2021). Monthly closure of surface energy balance to estimate land surface temperature and evapotranspiration over a watershed considering all the heat storages.
Python