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Open AccessArticle

An Empirical Assessment of Angular Dependency for RedEdge-M in Sloped Terrain Viticulture

Environmental Remote Sensing and Geoinformatics, Trier University, 54286 Trier, Germany
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Remote Sens. 2019, 11(21), 2561; https://doi.org/10.3390/rs11212561
Received: 2 September 2019 / Revised: 25 October 2019 / Accepted: 29 October 2019 / Published: 31 October 2019
(This article belongs to the Special Issue Remote Sensing in Viticulture)
For grape canopy pixels captured by an unmanned aerial vehicle (UAV) tilt-mounted RedEdge-M multispectral sensor in a sloped vineyard, an in situ Walthall model can be established with purely image-based methods. This was derived from RedEdge-M directional reflectance and a vineyard 3D surface model generated from the same imagery. The model was used to correct the angular effects in the reflectance images to form normalized difference vegetation index (NDVI) orthomosaics of different view angles. The results showed that the effect could be corrected to a certain scope, but not completely. There are three drawbacks that might restrict a successful angular model construction and correction: (1) the observable micro shadow variation on the canopy enabled by the high resolution; (2) the complexity of vine canopies that causes an inconsistency between reflectance and canopy geometry, including effects such as micro shadows and near-infrared (NIR) additive effects; and (3) the resolution limit of a 3D model to represent the accurate real-world optical geometry. The conclusion is that grape canopies might be too inhomogeneous for the tested method to perform the angular correction in high quality. View Full-Text
Keywords: viticulture; multispectral; UAV; BRDF; geometric viticulture; multispectral; UAV; BRDF; geometric
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Gong, C.; Buddenbaum, H.; Retzlaff, R.; Udelhoven, T. An Empirical Assessment of Angular Dependency for RedEdge-M in Sloped Terrain Viticulture. Remote Sens. 2019, 11, 2561.

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