Abstract
Building extraction is a component of many environmental modelling and data analysis applications. It is however data and knowledge intensive. We investigate the use of publicly available data from Google Earth and OpenStreetMap and of neural networks for this task. We evaluate different candidate algorithms for the case of building extraction on the island of Bali.
| Original language | English |
|---|---|
| Title of host publication | ACM International Conference Proceeding Series |
| Subtitle of host publication | 21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Proceedings |
| Editors | Maria Indrawan-Santiago, Eric Pardede, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Anderst-Kotsis |
| Place of Publication | New York USA |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 502-511 |
| Number of pages | 10 |
| ISBN (Electronic) | 9781450371797 |
| DOIs | |
| Publication status | Published - 2 Dec 2019 |
| Externally published | Yes |
| Event | Information Integration and Web-Based Applications and Services 2019 - Munich, Germany Duration: 2 Dec 2019 → 4 Dec 2019 Conference number: 21st https://dl.acm.org/doi/proceedings/10.1145/3366030 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | Information Integration and Web-Based Applications and Services 2019 |
|---|---|
| Abbreviated title | iiWAS 2019 |
| Country/Territory | Germany |
| City | Munich |
| Period | 2/12/19 → 4/12/19 |
| Internet address |
Keywords
- Building extraction
- Neural networks
- Public data sets
- Remote sensing