Photo Open Access
Reinhard, Friedrich; Parkan, Matthew; Produit, Timothée; Betschart, Sonja; Bacchilega, Beatrice; Hauptfleisch, Morgan L.; Meier, Patrick; SAVMAP, Consortium; Joost, Stéphane
To prevent aggravation of existing poverty in semi-arid savannas, a comprehensive concept for the sustainable adaptive management and use of these ecosystems under unprecedented conditions is needed. SAVMAP is an innovative, trans-, and inter-disciplinary initiative whose goal is to develop a valuable monitoring tool for both sustainable land-use management and rare species conservation (black rhinoceros) in semi-arid savanna in Namibia. SAVMAP uses near real-time ultrahigh-resolution photographic imaging (NURI) facilitated by unmanned aerial vehicles (UAVs) designed at EPFL.
Ofli, F., Meier, P., Imran, M., Castillo, C., Tuia, D., Rey, N., Briant, J., Millet, P., Reinhard, F., Parkan, M., 2016. Combining human computing and machine learning to make sense of big (aerial) data for disaster response. Big data 4, 47–59.
Rey, N., Volpi, M., Joost, S., Tuia, D., 2017. Detecting animals in African Savanna with UAVs and the crowds. Remote Sensing of Environment 200, 341–351. https://doi.org/10.1016/j.rse.2017.08.026