Modeling of Spatial-Temporal Distribution of Sosnovsky's Hogweed in the Central Non-Chernozem Region Based on Remote Sensing Data

Biological invasions remain a serious environmental problem, threatening species biodiversity, ecosystem stability and human health. In the European part of Russia, Sosnowsky’s hogweed (Heracleum Sosnowskyi) is considered the most dangerous invasive species, expanding its range by 5–10% each year. Modern remote sensing methods enable the assessment of the spread dynamics of Sosnowsky’s within its secondary range, while species distribution models (SDMs) can determine the suitability of habitats for the growth of this invasive species. The aim of this project is to assess the spatial-temporal dynamics of Sosnowsky’s hogweed in the Central Non-Chernozem Region, using the Moscow Area as an example, based on multi-year Sentinel-2 satellite data. The detection of Sosnowsky’s hogweed stands is performed using the HSI (Heracleum Sosnowskyi Index) spectral index, whilst the suitability of habitats for the spread of the invasive species is assessed using SDM modelling based on the maximum entropy (MaxEnt) method. The proposed methodology can be used for the rapid identification of Sosnowsky’s hogweed hotspots and the planning of control measures for the Central Non-Chernozem Regions.