Geospatial Approaches to Monitoring the Spread of Invasive Species of Solidago spp.

Global climate change influences plant invasion which spreads all over the Europe. Invasive plants are predominantly manifest negative impacts, which require increased attention not only from ecologists. The research examines the possibilities offered by geospatial technologies in mapping the spatial spread of invasive plants of the genus Solidago. Invasive plant population was investigated at two localities, MalATIN SMALL LETTER Y WITH ACUTE Saris and Chminianska Nova Ves in Slovakia, as well as the mapping of the area by multispectral imaging to determine the spectral reflectance curve of the monitored plant species. Using spatial analyses in the geographic information system, we evaluated changes in the plant density in the two localities. Based on the obtained results, we found that the number of individuals (ramets) in the MalATIN SMALL LETTER Y WITH ACUTE Saris is significantly increasing, while in the examined area of Chminianska Nova Ves, there is a decrease in the number of Solidago spp. in the last monitored year. At the same time, we can state that in the areas with the highest increase in the number of ramets, the highest plant density per hectare was also recorded. We can also say that due to the spectral proximity of the surrounding vegetation, the spectral resolution in four spectral bands is insufficient for the classification of multispectral records in the case of Solidago spp. and cannot replace the advantages of high spectral resolution hyperspectral imaging, which significantly refines the feature space for Solidago spp. and the surrounding vegetation.

Automated summary

Global climate change influences plant invasion, with invasive plants of the genus Solidago spreading throughout Europe. Geospatial technologies, specifically multispectral imaging, were used to map the spatial spread of these invasive plants. Results showed an increase in the number of Solidago spp. individuals in MalATIN and a decrease in Chminianska Nova Ves. However, classification of Solidago spp. using four spectral bands was insufficient, highlighting the need for higher spectral resolution hyperspectral imaging for more accurate classification and feature extraction.