Abstract
The challenges presented by climate change are escalating and pose significant threats to global biodiversity, which in turn increases the risk of species extinctions. Therefore, meticulous monitoring efforts are necessary to mitigate the consequential impacts on both human well-being and environmental equilibrium. Biodiversity mapping is pivotal for establishing conservation priorities, often accomplished by assessing alpha, beta, and gamma diversity levels. Two main data sources, in situ and remote sensing (RS) data, are key for this task. In situ methods entail direct data collection from specific study areas, offering detailed insights into ecological patterns, albeit limited by resource constraints. Conversely, RS provides a broader observational platform, albeit at lower spatial resolution than in situ approaches. RS-derived diversity metrics have potential, particularly in linking spectral and biological diversity through high-resolution imagery for precise differentiation at fine scales. Coupling in situ and RS data underscores their complementary nature, contingent upon various factors including study scale and logistical considerations. In situ methods excel in precision, while RS offers efficiency and broader coverage. Despite prior investigations predominantly relying on limited datasets, our study endeavors to employ both in situ and RS data to assess plant and spectral species diversity across France at a high spatial resolution, integrating diverse metrics to unravel different biogeographical structures while gaining in understanding the relationship between plant and spectral diversity within and across bioregions.