Improving the Downscaling of Diurnal Land Surface Temperatures Using the Annual Cycle Parameters as Disaggregation Kernels
作者： Panagiotis Sismanidis , Iphigenia Keramitsoglou , Benjamin Bechtel , Chris Kiranoudis
DOI: 10.3390/RS9010023
关键词: Spectroradiometer 、 Geostationary orbit 、 Downscaling 、 Diurnal temperature variation 、 Environmental science 、 Daytime 、 Temporal resolution 、 Annual cycle 、 Climatology 、 Spatial ecology 、 Remote sensing
摘要: The downscaling of geostationary diurnal thermal data can ease the lack land surface temperature (LST) datasets that combine high spatial and temporal resolution. However, LST is more demanding than single scenes. This because spatiotemporal interrelationships original have to be preserved accurately reproduced by downscaled (DLST) data. To end, disaggregation kernels/predictors provide information about distribution during different times a day prove especially useful. Such predictors are Annual Cycle Parameters (ACPs). In this work, multitemporal ACPs employed for daytime nighttime ~4 km from SEVIRI (Spinning Enhanced Visible Infrared Imager) down 1 km. overall goal assess if use improve estimation range DLST (daytime minus DLST). evaluation performed comparing maps with reference MODIS (Moderate Imaging Spectroradiometer) also retrieved modified version TsHARP (Thermal Sharpening) algorithm. results suggest increase performance, produce accurate patterns.
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