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Open AccessArticle

Remotely Sensed Water Limitation in Vegetation: Insights from an Experiment with Unmanned Aerial Vehicles (UAVs)

1
Department of Environmental Sciences, Policy and Management, University of California, Berkeley, CA 94720, USA
2
Department of Integrative Biology, University of California, Berkeley, CA 94720, USA
3
University of California Division of Agriculture and Natural Resources, Davis, CA 95618, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1853; https://doi.org/10.3390/rs11161853
Received: 3 July 2019 / Revised: 30 July 2019 / Accepted: 6 August 2019 / Published: 9 August 2019
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
Unmanned aerial vehicles (UAVs) equipped with multispectral sensors present an opportunity to monitor vegetation with on-demand high spatial and temporal resolution. In this study we use multispectral imagery from quadcopter UAVs to monitor the progression of a water manipulation experiment on a common shrub, Baccharis pilularis (coyote brush) at the Blue Oak Ranch Reserve (BORR) ~20 km east of San Jose, California. We recorded multispectral imagery at several altitudes with nearly hourly intervals to explore the relationship between two common spectral indices, NDVI (normalized difference vegetation index) and NDRE (normalized difference red edge index), leaf water content and water potential as physiological metrics of plant water status, across a gradient of water deficit. An examination of the spatial and temporal thresholds at which water limitations were most detectable revealed that the best separation between levels of water deficit were at higher resolution (lower flying height), and in the morning (NDVI) and early morning (NDRE). We found that both measures were able to identify moisture deficit across treatments; however, NDVI was better able to distinguish between treatments than NDRE and was more positively correlated with field measurements of leaf water content. Finally, we explored how relationships between spectral indices and water status changed when the imagery was scaled to courser resolutions provided by satellite-based imagery (PlanetScope).We found that PlanetScope data was able to capture the overall trend in treatments but unable to capture subtle changes in water content. These kinds of experiments that evaluate the relationship between direct field measurements and UAV camera sensitivity are needed to enable translation of field-based physiology measurements to landscape or regional scales. View Full-Text
Keywords: unmanned aerial vehicles; vegetation water status; drought; NDVI; NDRE; Baccharis pilularis unmanned aerial vehicles; vegetation water status; drought; NDVI; NDRE; Baccharis pilularis
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MDPI and ACS Style

Easterday, K.; Kislik, C.; Dawson, T.E.; Hogan, S.; Kelly, M. Remotely Sensed Water Limitation in Vegetation: Insights from an Experiment with Unmanned Aerial Vehicles (UAVs). Remote Sens. 2019, 11, 1853.

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