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• W2913765718 abstract "Thermal InfraRed (TIR) image data at high temporal and spatial resolution are required to monitor the rapid development of crops during the growing season, taking into account the fragmentation of most agricultural landscapes. Moreover, integrating high-resolution satellite TIR data to calibrate hydrological models is a powerful information to efficiently monitor crop water use. Conversely, no single sensor meets these combined requirements in the TIR spectral region. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing image data to meet the combined requirements on spatial and temporal resolution. A novel spatio-temporal data fusion workflow based on a multi-sensor multi-resolution algorithm was developed and applied to generate TIR synthetic image data at high temporal and spatial resolution. The workflow includes two steps: in the first step, synthetic daily radiance images at Top of Atmosphere (TOA) and 30-m spatial resolution (at the ground) are generated using TIR radiometric data at TOA collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) daily 1-km and Landsat 8/TIRS 16-day 30-m. This procedure is applied to two image pairs on different dates. The workflow yields an estimator to generate TIR TOA radiance data on any given date, provided a MODIS radiance image is available. The next step applies constrained unmixing of the 30 m (now considered as low-resolution) TIR images using the information about sub-pixel land-cover obtained from co-registered images at higher spatial resolution in the VNIR (Visible Near InfraRed) spectrum. In our case study, the L8/TIRS synthetic image data were unmixed to the Sentinel 2/MSI with 10 m × 10 m spatial resolution. Two geographically diverse experiments were carried out using the same procedure: one in The Netherlands to evaluate the procedure and other in Puglia (Italy) to generate a time series of the 10-m × 10-m TIR image data product. The validation experiment, where an actual TIRS image was applied as a reference, gave a RMSE value of 35.3 W/(m2 μm sr), which corresponds to a relative value of 8.5% against the TIRS reference values. The results confirm the feasibility of the proposed methodology, which yields a synthetic thermal band to integrate with the multi-spectral data provided by the S2/MSI at 10 m resolution." @default.
• W2913765718 created "2019-02-21" @default.
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• W2913765718 date "2019-06-01" @default.
• W2913765718 modified "2023-10-17" @default.
• W2913765718 title "Generating high-temporal and spatial resolution TIR image data" @default.
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• W2913765718 doi "https://doi.org/10.1016/j.jag.2019.01.016" @default.
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