University of Twente Proceedings
An open-source semi-automated processing chain for urban obia classification
Grippa, T. and Lennert, M. and Beaumont, B. and Vanhuysse, S. and Stephenne, N. and Wolff, E. (2016) An open-source semi-automated processing chain for urban obia classification. In: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) .
|
PDF
812kB |
| Event: | GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) |
| Abstract: | This study presents the development of a semi-automated processing chain for OBIA urban land-cover and land-use classification. Implemented in Python and relying on existing open-source software GRASS GIS and R. The complete tool chain is available in open-access and adaptable to specific user needs. For automation purpose, we developed two GRASS GIS add-ons allowing (1) to optimize segmentation parameters in an unsupervised manner and (2) to classify remote sensing data using several individual machine learning classifiers or their predictions combination through voting-schemes. We tested the performance and transferability of the processing chain using sub-metric multispectral and height data on two very different urban environments: Ouagadougou, Burkina Faso in sub-Saharan Africa and Liège, Belgium in Western Europe. Using a hierarchical classification scheme, the kappa values reached for both cities about 0.78 at the second level (9 and 11 classes) and 0.90 at the first level (5 classes). |
| Item Type: | Conference or Workshop Item (Paper) |
| Link to this item: | https://doi.org/10.3990/2.367 |
| Conference URL: | https://www.geobia2016.com/ |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page