sUAS Remote Sensing of Vineyard Evapotranspiration Quantifies Spatiotemporal Uncertainty in Satellite-Borne ET Estimates

Kalua, Michael; Rallings, Anna M.; Booth, L.; Medellín–Azuara, Josué; Carpin, Stefano; Viers, Joshua H.

doi:10.3390/rs12193251

Cited by 7 publications

(3 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Deep learning is being applied to satellite and in situ data to produce daily soil moisture measurements at 9 km spatial resolution (Liu et al., 2022). Recent advances in unmanned aerial vehicles may also improve the scalability of DDWB methods (Kalua et al., 2020) such as soil moisture mapping by unpiloted aerial systems (Araya et al., 2021). Future research into how these new data sets can be incorporated into a DDWB, along with artificial intelligence and machine learning, are at the current frontier of tools for improving water management at all scales.…”

Section: Discussion and Future Research Opportunitiesmentioning

confidence: 99%

A Decade of Data‐Driven Water Budgets: Synthesis and Bibliometric Review

Moyers,

Sabie,

Waring

et al. 2023

Water Resources Research

Self Cite

View full text Add to dashboard Cite

Scarce water resources across the globe have prompted the development of data‐driven water budgets to account for and distribute limited water more effectively across various land uses and purposes. Data‐driven approaches for estimating individual water budget components have been extensively developed and subsequently reviewed (e.g., evapotranspiration, precipitation, groundwater, surface water, runoff), but the state of the art of data‐driven approaches for estimating and integrating complete water budgets has not been the subject of a review paper to our knowledge. In this review, we fill this void by reviewing 81 systematically identified publications from the last decade (2012–2022) on data‐driven water budget approaches. We describe the current state of measurements and data products for data‐driven water budgets for various spatiotemporal scales. Our analysis suggests that spatiotemporal parameters drive the approach for data‐driven water budgets, with larger spatiotemporal scales relying more on satellite remote sensing data products and smaller spatiotemporal scales relying more on ground‐based monitoring. The incorporation of satellite remote sensing data products and ground‐based monitoring was common across various spatiotemporal scales and enabled the estimation of complete water budgets in areas of limited data availability. We conclude that improved reporting of simplifying assumptions, uncertainty analysis methods, and data sources are required for the alignment of water budget estimations between resource managers at varied spatiotemporal scales. Our review calls for the standardization of data‐driven water budget reporting protocols to improve the interpretability of data‐driven water budgets across decision‐makers working at various spatiotemporal scales.

show abstract

Section: Discussion and Future Research Opportunitiesmentioning

confidence: 99%

A Decade of Data‐Driven Water Budgets: Synthesis and Bibliometric Review

Moyers,

Sabie,

Waring

et al. 2023

Water Resources Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this case, we could apply the ratios to the fluxes determined by EC methods. The partition ratio can also be applied to satellite ET derived results or conventional methods used for ET estimation [36].…”

Section: Discussionmentioning

confidence: 99%

“…IMB results are valuable. Combined with other ET methods, the results can provide calibration to remotely sensed regional ET estimates [36]. The ET scaled estimations preserve their accuracy and compare well with other methods.…”

mentioning

confidence: 81%

The Use of Water Vapor Isotopes to Determine Evapotranspiration Source Contributions in the Natural Environment

Bernier

2020

Water

View full text Add to dashboard Cite

Water balance measurements are the simplest and most direct means of estimating evapotranspiration (ET). However, numerous factors relating to climate and terrain characteristics contribute to the variability that makes the assessment of evapotranspiration challenging at the ecosystem or even the plot scale. Alternative methods, such as an isotope mass balance (IMB), can provide evapotranspiration estimates. This paper illustrates two IMB examples of partitioning evaporation and transpiration. The first example demonstrates at the laboratory scale how accurate mass-balance measurements provide a complete validation and refinement of the isotope mass balance methods. The second IMB case uses similar data processing methods for an experimental field design. These methods are further validated by comparison with previous laboratory and field studies. Finally, this paper presents a comparison between partitioned ET ratios from a nearby U.S. Geological Survey (USGS) microclimate site produced using the Flux Variance Similarity (FVS) method. The results suggest the potential of employing these methods to estimate evaporation and transpiration source contributions at various scales. This technique and its further development show IMB methods are an appropriate tool for partitioning evapotranspiration.

show abstract

Satellite and UAV-based anomaly detection in vineyards

Araújo,

Norberto,

Pinheiro

et al. 2023

BIO Web Conf.

View full text Add to dashboard Cite

One of the most frequent, most expensive and potentially more impactful tasks in crop management is surveying and scouting the fields for problems in crop development. Any biotic / abiotic stress undetected becomes a bigger problem to solve later, with a potentially cascading effect on yield and/or quality and, subsequently, crop value. For annual crops (such as corn, soy, etc.) this can be solved in a cost-effective way with Sentinel data. For permanent crops planted in rows (such as vineyards), the interference from the inter-row makes it much more challenging. Under a contract for the European Space Agency (ESA), Spin.Works has been developing an early anomaly detection system based on fusion of Sentinel-2 and UAV imagery, targeting an update rate of 5 days. The early anomaly detection is applied to vineyards, particularly, for nutrient and water stresses. The early anomaly detection system is integrated into Spin.Works’ MAPP.it platform and its development is being carried out in close cooperation with the internal R&D group of Sogrape Vinhos, Portugal's largest winemaker and a long-standing MAPP.it user.

show abstract

sUAS Remote Sensing of Vineyard Evapotranspiration Quantifies Spatiotemporal Uncertainty in Satellite-Borne ET Estimates

Cited by 7 publications

References 59 publications

A Decade of Data‐Driven Water Budgets: Synthesis and Bibliometric Review

A Decade of Data‐Driven Water Budgets: Synthesis and Bibliometric Review

The Use of Water Vapor Isotopes to Determine Evapotranspiration Source Contributions in the Natural Environment

Satellite and UAV-based anomaly detection in vineyards

Contact Info

Product

Resources

About