Semi-natural landscapes are recognized as suitable habitats for different plant species and provide ecosystem services that contribute to increased plant biodiversity. At the stand level, plant biodiversity is influenced by vegetation structure, of which vegetation height is an important parameter. Photogrammetry from drone captured images has the potential to provide a quick and cost-effective analysis of vegetation height. In addition, the relation between spectral signatures and species distribution can indicate where higher plant biodiversity can be found, as species can be identified based on their spectral signature. Spectral signatures are thus used in the current study in conjunction with vegetation height as a proxy for plant biodiversity in herbaceous-dominated patches. Two field surveys were conducted to collect drone data and reflectance data in July and August 2019. Twelve plots of ten metres diametre were delimited in the drone-derived orthophotos around the reflectance readings coordinates. In order to assess vegetation height, the difference between the digital surface model derived from the orthophotos and the national digital elevation model was determined. Two statistical indices were calculated: the modified soil-adjusted vegetation index (MSAVI) and the coefficient of variation of heights (CV). The relationship between the two indices was evaluated as a proxy for plant biodiversity. Drone-derived point clouds can be used to measure vegetation height in herbaceous-dominated environments due to the very fine scale of drone imagery. A possible negative correlation was found between MSAVI and CV on both surveyed months (July r2 = 0.675; August r2 = 0.401) if the outlier plots were removed from the analysis. There is not enough evidence to clearly explain the anomalous behaviour of the outlier plots. Further research is needed to confirm the use of the relationship between vegetation height variability and reflectance as a proxy for plant biodiversity assessment in herbaceous-dominated environments.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-199161 |
| Date | January 2020 |
| Creators | Santiago, Jo |
| Publisher | Stockholms universitet, Institutionen för naturgeografi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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