Procrustean analysis of the set of spectral indices reveals the transformations in plant community hemeroby and functional structure induced by anthropogenic disasters

Abstract

This study presents an integrated remote sensing approach for assessing the ecological consequences of the destruction of the Kakhovka Reservoir in Southern Ukraine. The methodology combines spectral vegetation indices, principal component analysis, and Procrustean analysis to evaluate spatial and functional transformations in vegetation cover following a large-scale anthropo genic disaster. The approach was applied to floodplain ecosystems on Khortytsia Island and adjacent areas using satellite imagery from the Sentinel-2 mission for the years 2022 and 2024. A set of twenty-nine spectral indices, sensitive to vegetation density, pigment composition, water conditions, and soil properties, was employed to identify patterns in plant community dynamics and environmental change. Principal component analysis was utilized to identify the dominant axes of spectral variability, while Procrustean rotations facilitated the detection of significant spatial shifts over time. The results demonstrated strong correlations between changes in vegetation patterns and key ecological indicators, including hemeroby, naturalness, species richness, and functional diversity. Two primary ecological trends were identified. The first trend is associated with ecosystem degradation due to anthropogenic pressure, characterized by increasing hemeroby, a decline in naturalness, and reductions in both functional evenness and functional divergence. The second trend reflects the internal reorganization of plant communities under near-natural conditions, where increases in projective cover and species richness occur alongside a decrease in functional richness. Spectral ind ices, such as the normalized difference vegetation index, the normalized difference chlorophyll index, the red-edge vegetation index, the normalized difference tillage index, and the normalized difference water index, have proven particu larly effective in detecting both degradation and successional processes. This study demonstrates that satellite-based spectral indices can serve as reliable proxies for assessing the functional structure and ecological condition of vegetation. The proposed methodology provides an effective tool for spatially explicit and timely environmental monitoring, thereby supporting evidence-based decision-making in post-disaster landscape management, including the question of restoring water bodies or conserving newly formed floodplain ecosystems. This approach has broad applicability for long-term ecological monitoring, restoration planning, and adaptive ma n agement in regions impacted by significant anthropogenic transformations