11:00 - 12:00
Th-STS10
Chair:
Peter Stoltze (Statistics Denmark, Denmark)
ADELE: Overview of a deep learning application for land use and land cover change detection and classification in Switzerland
Michael Leuenberger, (Email) 1, 2, Gillian Milani, (Email) 3, Claudio Facchinetti, (Email) 3
1 Statistical Methods Unit, Federal Statistical Office, Switzerland
2 Institute of Statistics, University of Neuchâtel, Switzerland
3 Geoinformation Unit, Federal Statistical Office, Switzerland

During the past decades, the Swiss Federal Statistical Office has elaborated highly accurate land use and land cover classification surveys covering the Swiss territory. Until now, the classification of the 4 million sample points covering Switzerland was elaborated by visual interpretation of aerial images. The project “Arealstatistik Deep Learning” (ADELE) aims to speed up the process of classification by using deep learning algorithms and keeping a high level of accuracy. The results and knowledge obtained so far demonstrated the innovation potential for the SFSO in using artificial intelligence to process images.