Loading...
Please wait, while we are loading the content...
Similar Documents
Change Detection from Remote Sensing to Guide OpenStreetMap Labeling
| Content Provider | MDPI |
|---|---|
| Author | Albrecht, Conrad M. Zhang, Rui Cui, Xiaodong Freitag, Marcus Hamann, Hendrik F. Klein, Levente J. Finkler, Ulrich Marianno, Fernando Schmude, Johannes Bobroff, Norman Zhang, Wei Siebenschuh, Carlo Lu, Siyuan |
| Copyright Year | 2020 |
| Description | The growing amount of openly available, meter-scale geospatial vertical aerial imagery and the need of the OpenStreetMap (OSM) project for continuous updates bring the opportunity to use the former to help with the latter, e.g., by leveraging the latest remote sensing data in combination with state-of-the-art computer vision methods to assist the OSM community in labeling work. This article reports our progress to utilize artificial neural networks (ANN) for change detection of OSM data to update the map. Furthermore, we aim at identifying geospatial regions where mappers need to focus on completing the global OSM dataset. Our approach is technically backed by the big geospatial data platform Physical Analytics Integrated Repository and Services (PAIRS). We employ supervised training of deep ANNs from vertical aerial imagery to segment scenes based on OSM map tiles to evaluate the technique quantitatively and qualitatively. |
| Starting Page | 427 |
| e-ISSN | 22209964 |
| DOI | 10.3390/ijgi9070427 |
| Journal | ISPRS International Journal of Geo-Information |
| Issue Number | 7 |
| Volume Number | 9 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-07-02 |
| Access Restriction | Open |
| Subject Keyword | ISPRS International Journal of Geo-Information Isprs International Journal of Geo-information Imaging Science Remote Sensing Openstreetmap Data Collection Geospatial Change Detection Image Segmentation Artificial Neural Networks Big Geospatial Databases |
| Content Type | Text |
| Resource Type | Article |
