Possibilities of UAV based identification and Monitoring Of Common Milkweed (Asclepias syriaca L.)
DOI:
https://doi.org/10.56617/tl.4948Keywords:
Asclepias syriaca, biological invasion, drone (UAV), geographic information system, image processing, remote sensing, vegetation indicesAbstract
Invasive species cause serious and often irreversible damage to biodiversity and ecosystem services, which are essential for human survival and can also be a public health problem due to their pollen. Both the defense against them, and the economic and nature conservation damage caused by them result in enormous costs worldwide. To manage invasive species effectively, we need to know their current distribution, the dynamics of their spread, and their exact impact on ecosystems, habitats, and the economy. Nowadays, the most efficient way to collect this information from large areas is by drones (UAV – unmanned aerial vehicle). Semi-natural grasslands have significant biodiversity and provide important ecosystem services, but these habitats are also vulnerable to damage by invasive species. Hungary's Pannonian sand grasslands are threatened by the spread of many invasive species. From these, we mapped and monitored the common milkweed (Asclepias syriaca L.) as it is one of the most common and dangerous invasive species on the Southern Great Plain region. As the conservation management of invasive plant species is based on the approach and methods of agricultural weed control, this study can be evaluated as a methodological development of the adaptation of monitoring procedures used in agriculture. Our aim was to examine whether vegetation indices used in precision agriculture are suitable for the identification of individual common milkweed stands and their sizes. Therefore, in our study we examined vegetation indices (TGI, VARI, NDVI and SAVI) derived from aerial images taken with UAVs (RGB and CIR). The drone-based survey and mapping of milkweed was carried out on two regenerating fields adjacent to the Kolon Lake central area of the Kiskunság National Park in July 2020. According to our results, TGI proved to be the most suitable index for milkweed shoots and individual-level identification. NDVI and SAVI indices were less suitable than the TGI for determining of milkweed coverage and shoot number, however, they may be suitable for determining the effectiveness of nature conservation treatments. Our results provide a simple, fast, cost-effective, and minimally destructive method for mapping large-scale populations of invasive species for repeated monitoring. Thus, it can provide nature conservation with information that allows accurate planning of defense against invasion and monitoring of the effectiveness of treatments in the future.
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