Journal
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
Volume 88, Issue 2-4, Pages 721-735Publisher
SPRINGER
DOI: 10.1007/s10846-017-0513-x
Keywords
sUAS; Water stress detection; Canopy NDVI; SWP; Canopy NDVI threshold; Canopy NDVI distribution
Funding
- UC ANR [13-2628]
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We conducted a study in a large almond farm in Merced County, California, to monitor water status by using high-resolution multi-spectral imagery accquired by a Small Unmanned Aerial System (sUAS). More specifically, we would like to predict Stem Water Potential (SWP) via canopy Normalized Difference Vegetation Index (NDVI). During 2014, an aircraft equipped with multi-spectral cameras flew over the orchard weekly throughout the growing season. At the same time, SWP was measured for the sample trees under five different water treatment levels. Instead of averaging pixels in an orchard level, a block level or a canopy level, pixels were analyzed in the sub-canopy level to obtain canopy NDVI. An improved correlation between SWP and canopy NDVI was obtained by applying lower NDVI threshold. The relationship between SWP and canopy NDVI was also discussed at different growing stages-fruit development and post-harvest. However, tests of equality of distribution indicated that canopy NDVI distributions from different flights within a day were significantly different. Therefore, further calibration regarding the effects of solar motion on canopy NDVI is necessary.
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