Filippo Greco
Enhancing Spatial Resolution in Sentinel-3 Data - A Landsat 8 Supervised Approach.
Rel. Giovanni Squillero, Giacomo Blanco, Luca Barco, Lorenzo Innocenti. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2024
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Abstract
The temperature of Earth's surface has become in recent years critical for various research areas including weather forecasting, environmental monitoring, vegetation health analysis, urban planning, human well-being, and agricultural management. A major issue arising from urbanization is the development of urban heat islands — a phenomenon analyzed within microclimate studies, which focuses on localized areas that exhibit significantly higher temperatures than their surroundings. This challenge has increased the demand for finer spatial resolution of Land Surface Temperature (LST), enabling stakeholders and policymakers to make informed decisions and implement effective strategies within their areas of responsibility. Remote sensing instruments on satellites have been a main tool for estimating LST.
In this case study datasets of temperature measurements come from Sentinel-3 and Landsat 8, which are two satellite missions that use spectral bands to calculate LST, each with its own limitations: Sentinel-3 provides multiple readings per day but with a spatial resolution of 1 km, whereas Landsat 8 offers a finer spatial resolution of 100 m but revisits the same area only every eight days
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