Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions
Current land surface temperature (LST) products, estimated by sensors on board satellites, show a trade-off between their spatial and temporal resolution. If the spatial resolution is high (i.e., around 100 m), the LST product is delivered every 2 weeks, and for those LST products estimated daily, i...
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MDPI AG
2025-07-01
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| Online Access: | https://www.mdpi.com/2072-4292/17/14/2387 |
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| author | Vicente Garcia-Santos Alejandro Buil Juan Manuel Sánchez César Coll Raquel Niclòs Jesús Puchades Martí Perelló Lluís Pérez-Planells Joan Miquel Galve Enric Valor |
| author_facet | Vicente Garcia-Santos Alejandro Buil Juan Manuel Sánchez César Coll Raquel Niclòs Jesús Puchades Martí Perelló Lluís Pérez-Planells Joan Miquel Galve Enric Valor |
| author_sort | Vicente Garcia-Santos |
| collection | DOAJ |
| description | Current land surface temperature (LST) products, estimated by sensors on board satellites, show a trade-off between their spatial and temporal resolution. If the spatial resolution is high (i.e., around 100 m), the LST product is delivered every 2 weeks, and for those LST products estimated daily, its spatial resolution is 1 km. Current spatial and temporal resolutions are not adequate for disciplines such as high-precision agriculture, urban decision making, and planning how to mitigate the overheating of cities, for which LST maps at 50–100 m resolution every few days are desirable. This situation has led to the development of disaggregation techniques in order to enhance the spatial resolution of daily LST products. Unfortunately, disaggregation techniques are usually complex since they rely on a number of external inputs and computer resources and are difficult to apply in practice. To our knowledge, there are only two operative downscaled 10 m LST products available to the end user, which are implemented in the Google Earth Engine (GEE) tool. They are the Daily Ten-ST-GEE and LST-downscaling-GEE systems. This study provides a critical benchmark by performing the first direct intercomparison and rigorous in situ validation of these two operative GEE systems. The validation, conducted with reference temperature data from dedicated field campaigns over contrasting agricultural sites in Spain, showed a good correlation of both methods with a R<sup>2</sup> of 0.74 for Daily Ten-ST-GEE and 0.94 for LST-downscaling-GEE, but the poor results of the first method in a highly heterogeneous site (RMSE of 5.8 K) make the second method the most suitable (RMSE of 3.6 K) for obtaining high-spatiotemporal-resolution LST maps. |
| format | Article |
| id | doaj-art-8167e5a59bba40feb4a5ac1b6e9e1067 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-8167e5a59bba40feb4a5ac1b6e9e10672025-08-20T03:32:15ZengMDPI AGRemote Sensing2072-42922025-07-011714238710.3390/rs17142387Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal ResolutionsVicente Garcia-Santos0Alejandro Buil1Juan Manuel Sánchez2César Coll3Raquel Niclòs4Jesús Puchades5Martí Perelló6Lluís Pérez-Planells7Joan Miquel Galve8Enric Valor9Department of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, 46100 Valencia, SpainMeteoclim, Calle Sophie Germain, Edificio Lleret, Planta Baja Derecha Parc Bit, 07121 Palma, SpainDepartment of Physics, University of Castilla-La Mancha, 02071 Albacete, SpainDepartment of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, 46100 Valencia, SpainDepartment of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, 46100 Valencia, SpainDepartment of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, 46100 Valencia, SpainDepartment of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, 46100 Valencia, SpainDepartment of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, 46100 Valencia, SpainDepartment of Physics, University of Castilla-La Mancha, 02071 Albacete, SpainDepartment of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, 46100 Valencia, SpainCurrent land surface temperature (LST) products, estimated by sensors on board satellites, show a trade-off between their spatial and temporal resolution. If the spatial resolution is high (i.e., around 100 m), the LST product is delivered every 2 weeks, and for those LST products estimated daily, its spatial resolution is 1 km. Current spatial and temporal resolutions are not adequate for disciplines such as high-precision agriculture, urban decision making, and planning how to mitigate the overheating of cities, for which LST maps at 50–100 m resolution every few days are desirable. This situation has led to the development of disaggregation techniques in order to enhance the spatial resolution of daily LST products. Unfortunately, disaggregation techniques are usually complex since they rely on a number of external inputs and computer resources and are difficult to apply in practice. To our knowledge, there are only two operative downscaled 10 m LST products available to the end user, which are implemented in the Google Earth Engine (GEE) tool. They are the Daily Ten-ST-GEE and LST-downscaling-GEE systems. This study provides a critical benchmark by performing the first direct intercomparison and rigorous in situ validation of these two operative GEE systems. The validation, conducted with reference temperature data from dedicated field campaigns over contrasting agricultural sites in Spain, showed a good correlation of both methods with a R<sup>2</sup> of 0.74 for Daily Ten-ST-GEE and 0.94 for LST-downscaling-GEE, but the poor results of the first method in a highly heterogeneous site (RMSE of 5.8 K) make the second method the most suitable (RMSE of 3.6 K) for obtaining high-spatiotemporal-resolution LST maps.https://www.mdpi.com/2072-4292/17/14/2387land surface temperature (LST)downscaling techniquesGoogle Earth Engine (GEE)temperature-based (T-b) validation |
| spellingShingle | Vicente Garcia-Santos Alejandro Buil Juan Manuel Sánchez César Coll Raquel Niclòs Jesús Puchades Martí Perelló Lluís Pérez-Planells Joan Miquel Galve Enric Valor Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions Remote Sensing land surface temperature (LST) downscaling techniques Google Earth Engine (GEE) temperature-based (T-b) validation |
| title | Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions |
| title_full | Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions |
| title_fullStr | Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions |
| title_full_unstemmed | Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions |
| title_short | Validation of Two Operative Google Earth Engine Applications to Generate 10 m Land Surface Temperature Maps at Daily to Weekly Temporal Resolutions |
| title_sort | validation of two operative google earth engine applications to generate 10 m land surface temperature maps at daily to weekly temporal resolutions |
| topic | land surface temperature (LST) downscaling techniques Google Earth Engine (GEE) temperature-based (T-b) validation |
| url | https://www.mdpi.com/2072-4292/17/14/2387 |
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