Improved cropland mapping in Ethiopia
- Author(s)
- Christoph Perger, Ian McCallum, Franziska Albrecht, Linda See, Steffen Fritz, David Thau
- Abstract
Across the globe, accurate national spatial datasets on cropland extent are lacking. These are necessary for a number of reasons, including accurately monitoring and predicting crop yield, land use, land acquisitions and food security. This study describes the use of crowd-sourcing information retrieved over Ethiopia depicting the extent of cropland area. This information has been used to train a classification algorithm in Google Earth Engine to produce a continuous cropland extent map of Ethiopia. Preliminary results of this novel approach are encouraging, with an overall validity of 96%.
- Organisation(s)
- Department of Geography and Regional Research
- External organisation(s)
- International Institute for Applied Systems Analysis
- Publication date
- 2013
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 105403 Geoinformatics
- Sustainable Development Goals
- SDG 2 - Zero Hunger, SDG 15 - Life on Land
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/8b0c827d-c197-410f-89e7-942511686fbc