A probabilistic vision-language framework for habitat mapping within biodiversity projects using remote sensing data, ecological text and prior maps
Sareh Rowlands
Accurate and time-sensitive spatial ecological information is essential for biodiversity policies and environmental planning, yet existing remote sensing (RS) classification workflows may struggle to integrate ecological semantics and prior domain knowledge, limiting their interpretability and performance for statutory habitat assessments such as Biodiversity Net Gain (BNG). In this study we explore the potential of Vision-Language Models (VLM) for UK Habitat (UKHab) classification, the standard