Abstract ID: 3.13481 | Accepted as Poster | Talk | TBA | TBA

The intensification of tourism in high mountain environments poses a significant threat to fragile alpine vegetation. Trampling along trails leads to the degradation of plant cover, affecting species diversity and ecosystem resilience. This study aims to assess the condition of high mountain vegetation and identify trampled areas using remote sensing techniques from ground-based, UAV, airborne, and satellite platforms. The research was conducted in the Tatra National Park (Poland) using multi-source remote sensing data. Ground-based hyperspectral measurements provided detailed spectral characteristics of vegetation, while airborne HySpex hyperspectral data from 2019 and 2020 (2-meter resolution) enabled large-scale vegetation assessment. Additionally, Sentinel-2 satellite imagery was used for broader spatial analysis and temporal monitoring. Vegetation condition was evaluated through remote sensing indices and fluorescence parameters linked to photosynthetic efficiency. The classification of alpine grassland habitats was performed using Random Forest classifiers. The analysis revealed significant differences in vegetation indices depending on proximity to trails. Within 5 meters of the path, vegetation condition was relatively good, but beyond this threshold, trampling effects became evident, leading to reduced plant density and cover. Trampled areas were identified with 91% overall accuracy (Kappa = 0.85). Key vegetation indices included ARVI and NDVI for general condition, RARSa and GI for chlorophyll content, SIPI and PRI for photosynthesis efficiency, NDNI for nitrogen content, PSRI and CAI for dry matter, and WBI and NDWI for water content. Field studies identified critical spectral ranges for pigments (653-690 nm) and water/structural elements (1390-2453 nm). The integration of ground-based, airborne, and satellite remote sensing data allowed for a multi-scale assessment of vegetation conditions and degradation patterns. Multi-platform remote sensing effectively monitors tourism’s impact on high mountain vegetation. Ground-based data ensure accuracy, airborne imaging enables precise mapping, and satellite observations support long-term monitoring. Identifying degraded areas aids conservation efforts, while ongoing multi-scale monitoring supports sustainable tourism management and species distribution modeling.