Validation of AVHRR Land Surface Temperature with MODIS and in situ LST — a TIMELINE thematic processor

Please always quote using this URN: urn:nbn:de:bvb:20-opus-246051
  • Land Surface Temperature (LST) is an important parameter for tracing the impact of changing climatic conditions on our environment. Describing the interface between long- and shortwave radiation fluxes, as well as between turbulent heat fluxes and the ground heat flux, LST plays a crucial role in the global heat balance. Satellite-derived LST is an indispensable tool for monitoring these changes consistently over large areas and for long time periods. Data from the AVHRR (Advanced Very High-Resolution Radiometer) sensors have been availableLand Surface Temperature (LST) is an important parameter for tracing the impact of changing climatic conditions on our environment. Describing the interface between long- and shortwave radiation fluxes, as well as between turbulent heat fluxes and the ground heat flux, LST plays a crucial role in the global heat balance. Satellite-derived LST is an indispensable tool for monitoring these changes consistently over large areas and for long time periods. Data from the AVHRR (Advanced Very High-Resolution Radiometer) sensors have been available since the early 1980s. In the TIMELINE project, LST is derived for the entire operating period of AVHRR sensors over Europe at a 1 km spatial resolution. In this study, we present the validation results for the TIMELINE AVHRR daytime LST. The validation approach consists of an assessment of the temporal consistency of the AVHRR LST time series, an inter-comparison between AVHRR LST and in situ LST, and a comparison of the AVHRR LST product with concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) LST. The results indicate the successful derivation of stable LST time series from multi-decadal AVHRR data. The validation results were investigated regarding different LST, TCWV and VA, as well as land cover classes. The comparisons between the TIMELINE LST product and the reference datasets show seasonal and land cover-related patterns. The LST level was found to be the most determinative factor of the error. On average, an absolute deviation of the AVHRR LST by 1.83 K from in situ LST, as well as a difference of 2.34 K from the MODIS product, was observed.show moreshow less

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Metadaten
Author: Philipp Reiners, Sarah Asam, Corinne Frey, Stefanie Holzwarth, Martin Bachmann, Jose Sobrino, Frank-M. Göttsche, Jörg Bendix, Claudia Kuenzer
URN:urn:nbn:de:bvb:20-opus-246051
Document Type:Journal article
Faculties:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Language:English
Parent Title (English):Remote Sensing
ISSN:2072-4292
Year of Completion:2021
Volume:13
Issue:17
Article Number:3473
Source:Remote Sensing (2021) 13:17, 3473. https://doi.org/10.3390/rs13173473
DOI:https://doi.org/10.3390/rs13173473
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 52 Astronomie / 526 Mathematische Geografie
5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 559 Geowissenschaften anderer Gebiete
Tag:AVHRR; Europe; Land Surface Temperature; MODIS; TIMELINE; time series; validation
Release Date:2023/05/25
Date of first Publication:2021/09/01
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International