Journal
REMOTE SENSING
Volume 12, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/rs12091471
Keywords
Land Surface Temperature; Landsat; Google Earth Engine; ASTER GED; high resolution
Categories
Funding
- Fundacao para a Ciencia e a Tecnologia (FCT) [PTDC/CTA-MET/28946/2017]
- Fundação para a Ciência e a Tecnologia [PTDC/CTA-MET/28946/2017] Funding Source: FCT
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Land Surface Temperature (LST) is increasingly important for various studies assessing land surface conditions, e.g., studies of urban climate, evapotranspiration, and vegetation stress. The Landsat series of satellites have the potential to provide LST estimates at a high spatial resolution, which is particularly appropriate for local or small-scale studies. Numerous studies have proposed LST retrieval algorithms for the Landsat series, and some datasets are available online. However, those datasets generally require the users to be able to handle large volumes of data. Google Earth Engine (GEE) is an online platform created to allow remote sensing users to easily perform big data analyses without increasing the demand for local computing resources. However, high spatial resolution LST datasets are currently not available in GEE. Here we provide a code repository that allows computing LSTs from Landsat 4, 5, 7, and 8 within GEE. The code may be used freely by users for computing Landsat LST as part of any analysis within GEE.
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