UAV-Based Land Cover Classification for Hoverfly (Diptera: Syrphidae) Habitat Condition Assessment: A Case Study on Mt. Stara Planina (Serbia)

Abstract

Habitat degradation, mostly caused by human impact, is one of the key drivers of biodiversity loss. This is a global problem, causing a decline in the number of pollinators, such as hoverflies. In the process of digitalizing ecological studies in Serbia, remote-sensing-based land cover classification has become a key component for both current and future research. Object-based land cover classification, using machine learning algorithms of very high resolution (VHR) imagery acquired by an unmanned aerial vehicle (UAV) was carried out in three different study sites on Mt. Stara Planina, Eastern Serbia. UAV land cover classified maps with seven land cover classes (trees, shrubs, meadows, road, water, agricultural land, and forest patches) were studied. Moreover, three different classification algorithms—support vector machine (SVM), random forest (RF), and k-NN (k-nearest neighbors)—were compared. This study shows that the random forest classifier performs better with respect to the other classifiers in all three study sites, with overall accuracy values ranging from 0.87 to 0.96. The overall results are robust to changes in labeling ground truth subsets. The obtained UAV land cover classified maps were compared with the Map of the Natural Vegetation of Europe (EPNV) and used to quantify habitat degradation and assess hoverfly species richness. It was concluded that the percentage of habitat degradation is primarily caused by anthropogenic pressure, thus affecting the richness of hoverfly species in the study sites. In order to enable research reproducibility, the datasets used in this study are made available in a public repository.

Nuevos datos del género Parhelophilus Girschner, 1897 de España, incluidos los primeros registros de P. crococoronatus Reemer, 2000 (Diptera, Syrphidae)

“…The habitat degradation is one of the many threats for the survival of Syrphidae (Ivošević et al, 2021) and hydro dam construction is considered as one of these specific threats for hoverfly biodiversity. Especially in the dry and vulnerable Mediterranean Region, this could lead to the extinction of many species depending on small streams and its specialised flora and fauna (Baffert & Bauer, 2020).…”

Investigating habitat degradation of Ursus arctos using species distribution modelling and remote sensing in Zagros Mountains of Iran

“…Intensive field surveys cannot keep pace with the rate of LULC change over large areas and new methods are needed for regional-scale mapping (Osborne et al 2001). Remote sensing has recently shown a great potential for species distribution mapping, LULC changes, and habitat condition assessment (Ivosevic et al 2021;Moon et al 2017;Randin et al 2020) and anticipated to be utilized more in studying combined effects of climate and land use changes (Santos et al 2017).…”