Daily 100 m land surface temperature generated through MODIS-Landsat fusion for 12 OzFlux regions across Australia during 2013-2021
CSIRO RDS Repository
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Title |
Daily 100 m land surface temperature generated through MODIS-Landsat fusion for 12 OzFlux regions across Australia during 2013-2021
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Creator |
Yi Yu
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Subject |
Earth system sciences
Photogrammetry and remote sensing |
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Description |
This collection aims to provide land surface temperature (LST) data for benchmarking algorithmic refinements of spatiotemporal fusion approaches. It contains LST data generated through MODIS-Landsat fusion for 12 OzFlux regions across Australia during 2013-2021 (and Himawari-Landsat fusion for 3 OzFlux regions within southeast Australia during 2016-2021). The area of each region is 100 × 100 km. The spatial resolution is 100 m and the temporal frequency is daily (around 10:30 am local solar time). This collection also provides the MODIS (and Himawari) and Landsat data that were used as inputs into the fusion, as well as an independent LST collection from the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) that was employed for cross-platform comparison. Several important updates within this version: - Updated the site description file with climate, land cover, and monthly emissivity values for each site. - Updated the OzFlux LST data using a new strategy. This strategy does not consider daylight saving time and does explicitly claim the 'seconds' timestep in the TOI (Time of Interests). Compared to the strategy used in our RSE paper, this strategy is expected to better coincide with the satellite overpass time. - Added MOD11A1 LST and viewtime data for the Australian continent during 2013-2021, with their native resolution of 1 km. Users can just simply clip the data to their targetted study areas. - Added the Himawari-Landsat fusion LST data for 3 OzFlux regions within southeast Australia during 2016-2021. The data format is identical to the MODIS-Landsat fusion LST data. |
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Publisher |
CSIRO
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Contributor |
Luigi Renzullo
Tim McVicar Brendan Malone Siyuan Tian |
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Date |
2023-11-23
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Type |
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Format |
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Identifier |
csiro:59165
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Language |
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