ArticlePloS one2025
High resolution descriptors for UAV mapping in biodiversity conservation - A case study of sandy steppe habitat renewal.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Due to the large-scale disappearance of grasslands there is an urgent need for revitalization. It calls for consistent and accessible monitoring and mapping plans, and an integrated management approach. However, revitalization efforts often focus solely on the vegetation component, and skip the link to other animal species that perform vital functions as ecosystem engineers and umbrella species. In this study, we combine an in-situ standard phytocoenological survey with an UAV-based technology in the effort to improve the monitoring and mapping of the sandy steppe habitat of the European ground squirrel (Spermophilus citellus; EGS), undergoing revitalization in the northern Serbia. It is a model organism of an animal species that enables identifying habitat quality and quantity indicators to understand the broader implications of the ecosystem revitalization efforts on the wildlife populations. The proposed approach tested whether the commercially available RGB sensor and a relatively high flight height of the UAV have discriminative capacity to aid site managers by mapping identified steppe development stages (specific plant assemblages, reflecting different habitat types). Thus, a novel set of high-resolution image descriptors that are capable of discriminating plant mixtures corresponding to Fallow land, Forest steppe and shrubs, Young steppe I and II, was proposed. Despite high resolution imaging, the method solves a challenging problem of UAV vegetation mapping in the case of limited spectral and spatial information in the image (by using only RGB camera and multitemporal approach). Although the lack of visual information that would allow identification of individual plant parts and shapes prevented the use of usual object-based image analysis, proposed pixel-based descriptors and feature selection were able to provide the extent of the targeted areas and their compositional carriers. Presented holistic approach enables implementation of effective management strategies that support the entire ecological community.
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