Assessing the relationship between bee/flower diversity and vegetation structural heterogeneity through UAV photogrammetry

Ceola, Giada (2022) Assessing the relationship between bee/flower diversity and vegetation structural heterogeneity through UAV photogrammetry. [Laurea magistrale], Università di Bologna, Corso di Studio in Analisi e gestione dell'ambiente [LM-DM270] - Ravenna
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Abstract

The ecosystem services provided by bees are very important. Factors as habitat fragmentation, intensive agriculture and climate change are contributing to the decline of bee populations. The use of remote sensing could be a useful tool for the recognition of sites with a high diversity, before performing a more expensive survey in the field. In this study the ability of Unmanned Aerial Vehicles (UAV) images to estimate biodiversity at local scale has been analysed testing the concept of the Height Variation Hypothesis (HVH). This approach states that, the higher the vegetation height heterogeneity (HH) measured by remote sensing information, the higher the vertical complexity and the higher vegetation species diversity. In this thesis the concept has been brought to a higher level, in order to understand if the vegetation HH can be considered a proxy also of bee species diversity and abundance. We tested this approach collecting field data on bees/flowers and RGB images through an UAV campaign in 30 grasslands in the South of the Netherlands. The Canopy Height Model (CHM) were derived through the photogrammetry technique "Structure from Motion" (SfM) with resolutions of 10cm, 25cm, 50cm. Successively, the HH assessed on the CHM using the Rao's Q heterogeneity index was correlated to the field data (bee abundance, diversity and bee/flower species richness). The correlations were all positive and significant. The highest R2 values were found when the HH was calculated at 10cm and correlated to bee species richness (R2 = 0.41) and Shannon’s H index (R2 = 0.38). Using a lower spatial resolution the goodness of fit slightly decreases. For flower species richness the R2 ranged between 0.36 to 0.39. Our results suggest that methods based on the concept behind the HVH, in this case deriving information of HH from UAV data, can be developed into valuable tools for large-scale, standardized and cost-effective monitoring of flower diversity and of the habitat quality for bees.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Ceola, Giada
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
bees, vegetation, UAV, remote sensing, Canopy Height Model, Height Variation Hypothesis, Rao’s Q index, Height Heterogeneity, biodiversity, spatial resolution, photogrammetry
Data di discussione della Tesi
13 Dicembre 2022
URI

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