Estimating land-surface temperature under clouds using MSG/SEVIRI observations
| Autor: | V. Venus, Tiejun Wang, Andrew K. Skidmore, Geping Luo, Lei Lu |
|---|---|
| Přispěvatelé: | Department of Natural Resources, UT-I-ITC-FORAGES |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Mean squared error
media_common.quotation_subject irradiance satellite net-radiation Management Monitoring Policy and Law heat-flux soil thermal-conductivity Approximation error Diurnal cycle moisture Emissivity Computers in Earth Sciences Earth-Surface Processes Remote sensing media_common Global and Planetary Change Propagation of uncertainty algorithm METIS-303927 PE&RC diurnal cycle Overcast Geography Sky Wildlife Ecology and Conservation emissivity Satellite solar-radiation |
| Zdroj: | International Journal of Applied Earth Observation and Geoinformation (JAG), 13(2), 265-276. Elsevier International Journal of applied Earth Observation and Geoinformation 13 (2011) 2 International Journal of applied Earth Observation and Geoinformation, 13(2), 265-276 |
| ISSN: | 0303-2434 1569-8432 |
| DOI: | 10.1016/j.jag.2010.12.007 |
| Popis: | The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the diurnal cycle of LST by exploiting the temporal domain offered by geo-stationary satellite observations (i.e. MSG/SEVIRI), and yields LST estimates even for overcast moments when satellite sensor can only record cloud-top temperatures. Contrasting to the neighboring pixel approach as presented by Jin and Dickinson (2002), our approach naturally satisfies all sorts of spatial homogeneity assumptions and is hence more suited for earth surfaces characterized by scattered land-use practices. Validation is performed against in situ measurements of infrared land-surface temperature obtained at two validation sites in Africa. Results vary and show a bias of −3.68 K and a RMSE of 5.55 K for the validation site in Kenya, while results obtained over the site in Burkina Faso are more encouraging with a bias of 0.37 K and RMSE of 5.11 K. Error analysis reveals that uncertainty of the estimation of cloudy sky LST is attributed to errors in estimation of the underlying clear sky LST, all-sky global radiation, and inaccuracies inherent to the ‘neighboring pixel’ scheme itself. An error propagation model applied for the proposed temporal neighboring-pixel approach reveals that the absolute error of the obtained cloudy sky LST is less than 1.5 K in the best case scenario, and the uncertainty increases linearly with the absolute error of clear sky LST. Despite this uncertainty, the proposed method is practical for retrieving the LST under a cloudy sky condition, and it is promising to reconstruct diurnal LST cycles from geo-stationary satellite observations. |
| Databáze: | OpenAIRE |
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