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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #390228

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Improving the spatiotemporal resolution of remotely sensed ET information for water management through Landsat, Sentinel-2, ECOSTRESS and VIIRS data fusion

Author
item XUE, J. - US Department Of Agriculture (USDA)
item Anderson, Martha
item Gao, Feng
item HAIN, C. - Nasa Marshall Space Flight Center
item Knipper, Kyle
item YANG, Y. - US Department Of Agriculture (USDA)
item Kustas, William - Bill
item YANG, Y. - US Department Of Agriculture (USDA)
item BAMBACH, N. - University Of California, Davis
item McElrone, Andrew
item CASTRO, S.J - University Of California, Davis
item Alfieri, Joseph
item Prueger, John
item McKee, Lynn
item HIPPS, L.E - Utah State University
item ALSINA, M. - E & J Gallo Winery

Submitted to: Irrigation Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/29/2022
Publication Date: 5/21/2022
Citation: Xue, J., Anderson, M.C., Gao, F.N., Hain, C., Knipper, K.R., Yang, Y., Kustas, W.P., Yang, Y., Bambach, N., Mcelrone, A.J., Castro, S., Alfieri, J.G., Prueger, J.H., McKee, L.G., Hipps, L., Alsina, M. 2022. Improving the spatiotemporal resolution of remotely sensed ET information for water management through Landsat, Sentinel-2, ECOSTRESS and VIIRS data fusion. Irrigation Science. https://doi.org/10.1007/s00271-022-00799-7.
DOI: https://doi.org/10.1007/s00271-022-00799-7

Interpretive Summary: Satellite remote sensing is able to provide information on crop water use (evapotranspiration, ET) at field scales that is useful for a range of water management actions, from irrigation scheduling to groundwater management planning. The current set of satellites that collect the thermal infrared imagery used to map ET at this scale, however, do not individually provide the frequency of imaging needed to accurately capture changes in water use at daily to weekly timesteps. This paper explores the use of imaging from multiple satellites, which collectively provide better temporal ET mapping capabilities than any single satellite in isolation. The mapping system described involves sharpening methods for bringing the images to a common spatial resolution, and a data fusion process for filling in time gaps between satellite overpasses. Improvement in ET estimation using these multi-sensor methods is assessed with ground-based ET measurements in irrigated crops in the Central Valley of California, demonstrating utility for real-time irrigation management.

Technical Abstract: Robust information on consumptive water use (evapotranspiration, ET) derived from remote sensing can significantly benefit water decision making in agriculture, informing irrigation schedules and water management plans over extended regions. To be of optimal utility for operational usage, these remote sensing ET data should be generated at the sub-field spatial resolution and daily-to-weekly timesteps commensurate with the scales of water management activities. However, current methods for field-scale ET retrieval based on thermal infrared (TIR) imaging, a valuable diagnostic of canopy stress and surface moisture status, are limited by the temporal revisit of available medium-resolution (100 m or finer) thermal satellite sensors. This study investigates the efficacy of a data fusion method for combining information from multiple medium-resolution sensors toward generating high spatiotemporal resolution ET products for water management TIR data from Landsat and ECOSTRESS (both at ~ 100-m native resolution), and VIIRS (750-m native) are sharpened to a common 30-m grid using surface reflectance data from the Harmonized Landsat-Sentinel dataset. 30-m ET retrievals from these combined thermal data sources are fused with daily retrievals from unsharpened VIIRS to generate daily, 30-m ET image timeseries. The accuracy of this mapping method is tested over several irrigated cropping systems in the Central Valley of California in comparison with flux tower observations, including measurements over irrigated vineyards collected in the GRAPEX campaign. Results demonstrate the operational value added by the augmented TIR sensor suite compared to Landsat alone, in terms of capturing daily ET variability and reduced latency for real-time applications. The method also provides means for incorporating new sources of imaging from future planned thermal missions, further improving our ability to map rapid changes in crop water use at field scales.