Published March 29, 2015
| Version 2.0
Photo
Open
Near real-time ultrahigh-resolution imaging from unmanned aerial vehicles for sustainable land use management and biodiversity conservation in semi-arid savanna under regional and global change (SAVMAP)
Creators
- 1. Kuzikus.org, P.Bag 13112 Windhoek, Namibia
- 2. Laboratory of Geographical Information Systems (LASIG), School of Architecture, Civil and environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 18, Lausanne, Switzerland
- 3. Drone Adventure, Lausanne, Switzerland, droneadventures.org/
- 4. Department of Nature Conservation, School of Natural Resources and Tourism, Polytechnic of Namibia, Private Bag 13388, Windhoek, Namibia
- 5. Qatar Computing Research Institute & iRevolution.net
- 6. http://lasig.epfl.ch/savmap
Description
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.
Notes
Files
readme.txt
Files
(3.5 GB)
Name | Size | Download all |
---|---|---|
md5:4abf4636b87b486e0adcfe00ec6975b4
|
860 Bytes | Preview Download |
md5:f87bd2ace593ec742fb03fd91975d566
|
3.5 GB | Preview Download |
Additional details
References
- 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