Poster + Paper
12 September 2021 Estimation of holm oak flowering intensity in dehesa farms using high-resolution aerial images
Author Affiliations +
Conference Poster
Abstract
The intensity of flowering of the holm oak trees is important for the annual phenological monitoring and as a predictive index of final acorn production. Their male flowers present in long catkins of intense yellow color and the estimation of their abundance in the field is a time-consuming task that becomes unfeasible at a large scale. In this work, a methodology to estimate the intensity of flowering of oak trees using RGB (Red Green Blue) images, provided by an unmanned aerial vehicle, was tested. During the spring of 2019, three aerial zenith images of 3 cm spatial resolution were taken in three selected dehesa sites, together with simultaneous ground digital photographs per tree (50 at each site). The intensity of flowering was visually estimated using the ground digital photographs in three categories, ranging from 1 (little or no flowering) to 3 (high flowering). A simple flowering intensity index, based on the closeness to pure yellow within a Cartesian RGB space, was developed to check the relationship between the drone images and the visually analyzed photographs. The results showed that those trees with lower flowering intensity were grouped in higher yellow distances and the high flowering intensity trees in the lower ones. As a result, it can be concluded that this index was able to identify qualitatively the flowering intensity of holm oaks at the farm level and could be useful for future phenological or productivity applications.
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Pedro J. Gómez-Giráldez, María D. Carbonero, Elisabet Carpintero, and María P. González-Dugo "Estimation of holm oak flowering intensity in dehesa farms using high-resolution aerial images", Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, 1185616 (12 September 2021); https://doi.org/10.1117/12.2601186
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KEYWORDS
Unmanned aerial vehicles

Digital photography

Ecosystems

Spatial resolution

Visual analytics

Climatology

Image analysis

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