LST Quality Evaluation Service for Heterogeneous Earth Observation Data

• Published in: 2023 International Conference on Information and Digital Technologies (IDT) pp. 195 - 200
• Main Authors: Lukashevich, Pavel, Belotserkovsky, Alexei, Grigoryan, Hayk, Abrahamyan, Rita, Astsatryan, Hrachya, Sasnovich, Aliaksei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22-06-2023
• Subjects: Artificial satellites; Earth; Earth Observation; Land surface temperature; Landsat; LST; meteorology; Remote Sensing; Satellite broadcasting; satellite images; Temperature distribution; Temperature sensors; Time series analysis; VIIRS
• ISSN: 2575-677X
• DOI: 10.1109/IDT59031.2023.10194405

The study aims to evaluate the Landsat 8 Thermal Infrared Sensor land surface temperature (LST) products and Visible Infrared Imager Radiometer Suite (VIIRS) LST environmental data record against ground observations in Armenia and Belarus. The data from the Landsat-8 satellite is used due to its high spatial resolution. In contrast, the VIIRS information is obtained due to its high temporal resolution, accessible with a minimal delay after the flyby of satellites. Algorithms to calculate LST were analyzed to find the best performance for both daytime and nighttime data. The evaluation shows that the current VIIRS LST products demonstrate a reasonable accuracy, with a root mean squared error average of 2.77 \mathbf{K} and an average coefficient of determination of 0.92 K.