Abstract
Small Unmanned Aerial Systems (sUAS) show promise in being able to collect high resolution spatiotemporal data over small extents. Use of such remote sensing platforms also show promise for quantifying uncertainty in more ubiquitous Earth Observation System (EOS) data, such as evapotranspiration and consumptive use of water in agricultural systems. This study compares measurements of evapotranspiration (ET) from a commercial vineyard in California using data collected from sUAS and EOS sources for 10 events over a growing season using multiple ET estimation methods. Results indicate that sUAS ET estimates that include non-canopy pixels are generally lower on average than EOS methods by >0.5 mm day−1. sUAS ET estimates that mask out non-canopy pixels are generally higher than EOS methods by <0.5 mm day−1. Masked sUAS ET estimates are less variable than unmasked sUAS and EOS ET estimates. This study indicates that limited deployment of sUAS can provide important estimates of uncertainty in EOS ET estimations for larger areas and to also improve irrigation management at a local scale.
Highlights
Global environmental change and anthropogenic activity have long stressed Earth’s hydrological cycle [1,2]
Through cross-platform comparisons, we asked: 1. Do Earth Observation Systems (EOS) and Small Unmanned Aerial Systems (sUAS) ET estimates fundamentally differ over same period of time? In other words, over the course of the growing season, does either the mean or variance of sUAS and EOS ET estimates differ? While we expect that ET estimates to track the growing season, it remains unknown if the variance in ET estimates track either the growing season or each other, sUAS compared to EOS
We focused on the comparative utility of EOS and sUAS ET estimates over a single growing season (2018)
Summary
Global environmental change and anthropogenic activity have long stressed Earth’s hydrological cycle [1,2]. Evapotranspiration remains the least certain quantified component of the hydrological cycle [3], with implications for water resources planning and management, and for human livelihoods and supporting ecosystems [4]. New advances in satellite remote sensing of ET via Earth Observation Systems (EOS) show promise in providing consistent and reliable quantitative estimates with global coverage and reasonable repeat cycles. Small Unmanned Aerial Systems (sUAS) operated under the Federal Aviation Administration (FAA) Part 107 licensing outfitted with optical sensors are increasingly used in vegetation remote sensing [6] and precision agriculture applications [7]. Comparative studies of EOS and sUAS observations of crop water stress have shown significant spatiotemporal uncertainty in coarser EOS data [8,9]
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