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        Capturing drought stress resilience in grass through UAV Hyperspectral imaging

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        MasterThesis_StijnKant.pdf (4.443Mb)
        Publication date
        2024
        Author
        Kant, Stijn
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        Summary
        This research investigates the impact of drought stress on various turfgrass species to identify those that are resilient under such conditions. Given the increased frequency and severity of droughts due to climate change over the past decade, understanding this impact is crucial for developing adaptation strategies. The study, conducted at the Nergena experimental field near Wageningen, Netherlands, utilized hyperspectral remote sensing to analyze vegetation health changes. It compared drought-stressed turfgrass plots with irrigated controls across different species, mixtures, and mowing heights tailored for sports, parks, and roadside applications. Data collected on four dates via a Headwall Nano-Hyperspec camera helped calculate fifteen vegetation indices to assess drought stress. The analysis included Principal Component Analysis and hierarchical clustering to rank grasses based on drought resistance and to identify patterns among them. The findings highlighted significant differences between mowing heights; turfgrass mown at 6cm showed better drought resilience than that mown at 3cm. Species like Tall Fescue and Hard Fescue, with deeper root systems, exhibited the highest drought resistance, while Perennial Ryegrass tetraploid, with open sods, was least resistant. Moreover, the study revealed that mixtures containing Tall Fescue and Hard Fescue had the highest drought resistance, whereas those including Perennial Ryegrass tetraploid were the least resistant. These results provide valuable insights into selecting species, mixtures, and mowing heights that best adapt to climate change, addressing gaps in knowledge about the drought resistance of different cool season turfgrass setups in established sods.
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        https://studenttheses.uu.nl/handle/20.500.12932/46470
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