1. The open access availability of satellite images from new sensors characterized by various spatial and temporal resolutions provides new challenges and possibilities for biodiversity conservation. Methodologies aiming at characterizing vegetation type, phenology, and function can now benefit from metric spatial resolution imagery combined with an improved revisit capability. Here, we test hybrid methods and data fusion, using very high spatial resolution (VHSR) sensors in different complex landscapes encompassing three French biogeographical regions. 2. The methodological approach presented herein has a generic value in response to national conservation targets based on the concept of essential biodiversity variables accessed by remote sensing (RS-enabled EBVs). We focused on deriving five RS-enabled EBVs from natural and seminatural open ecosystems: (1) ecosystem distribution, (2) land cover, (3) heterogeneity, (4) primary productivity and (5) vegetation phenology. The challenge was to develop a method that would be technically feasible, economically viable, and sustainable in time. 3. We demonstrated that it is possible to derive key parameters required to develop a set of EBVs from remote sensing (RS) data. The combined use of remote sensing data sources with various spatial, temporal, and spectral resolutions is essential to obtain different indicators of natural habitats. 4. One major current challenge for an improved contribution of RS to conservation is to strengthen multiple collaborative frameworks among remote sensing scientists, conservation biologists, and ecologists in order to increase the efficiency of methodological exchange and draw benefits for successful conservation planning strategies.