Abstract
Earth observation has traditionally required a compromise in data collection. That is, one could sense the Earth with high spatial resolution occasionally; or with lower spatial fidelity regularly. For many applications, both frequency and detail are required. Precision agriculture is one such example, with sub-10 m spatial, and daily or sub-daily retrieval representing a key goal. Towards this objective, we produced the first cloud-free 3 m daily evaporation product ever retrieved from space, leveraging recently launched nano-satellite constellations to showcase this emerging potential. Focusing on three agricultural fields located in Nebraska, USA, high-resolution crop water use estimates are delivered via CubeSat-based evaporation modeling. Results indicate good model agreement (r2 of 0.86–0.89; mean absolute error between 0.06 and 0.08 mm/h) when evaluated against corrected flux tower data. CubeSat technologies are revolutionizing Earth observation, delivering novel insights and new agricultural informatics that will enhance food and water security efforts, and enable rapid and informed in-field decision making.
Highlights
Earth observation has traditionally required a compromise in data collection
An alternative approach to single-mission driven Earth observation is one based instead on many nanosatellites that are launched in constellations, which can act in unison to collect high-resolution data across the globe at near-daily s cales[25]
Apart from showcasing paradigm changing advances in Earth observation, our work demonstrates the game-changing potential that CubeSats offer to a variety of fields, those where space and time constraints have limited process insights and advances
Summary
Earth observation has traditionally required a compromise in data collection. That is, one could sense the Earth with high spatial resolution occasionally; or with lower spatial fidelity regularly. Using a range of these space-based platforms, there have been many studies that have investigated remotely sensed E, at the regional-to-global s cale[12,13,14,15] While such efforts are essential to characterize and describe large-scale processes and behavior, they have been produced at coarse spatial resolutions (generally between 1 and 25 km), which precludes their use in capturing smaller scale patterns and variability. A number of approaches have explored the fusion of higher spatial resolution LandSat data with the enhanced temporal resolution of MODIS to develop a 30 m daily p roduct[22,23] These and related studies provide E at varying resolutions and scales, none have achieved the long-term high-spatial and high-temporal (daily) resolution retrievals needed to drive precision agricultural applications and advances[16,24]. Previous studies have highlighted the spatial resolution advantages of CubeSats, none have provided E at the temporal scales required to accurately capture and track in-field crop water use d ynamics[32] (i.e., daily) until now
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