Biodiversity is under threat from habitat loss and fragmentation, climate change, extreme land use and invasive alien species. Biodiversity monitoring for conservation purposes using geospatial data has seen some progress in recent years. Traditional survey methods are time-consuming, labour-intensive and require skilled staff. Surveying can be challenging, especially to keep track of rare or elusive species living in inaccessible or dangerous areas. Photogrammetric and LiDAR data has led to important advancements and impacts on ecosystem understanding as they enable precise assessments of habitat structures, mapping of species distributions or ecosystem dynamics, all essential information for conservation efforts. Nonetheless, better objective processes and monitoring solutions, with new tools to enhance and enrich current practices and assist ecologists, are needed. Therefore, the goal of the interdisciplinary PhD is to: (i) create and validate processes, based on 3D remote sensing data (airborne/drone monochromatic/multispectral LiDAR, photogrammetric point clouds, aerial/drone hyperspectral images, etc.) and AI methods, to locate and study various species, either animal or vegetal (ii) use ground robotics platforms and sensors for terrestrial biodiversity exploration and monitoring in challenging environments (iii) find biodiversity patterns, through multimodal data analytics, detecting hotspots of current issues, their trends and emerging threats (v) combine/fuse 3D data to cross-validate the methods (vi) find new links within geographical data between animals and vegetation.