Abstract
In this paper, we propose to combine two road extractors from very high resolution synthetic aperture radar scenes: one more successful in rural areas and one explicitly designed for urban areas. In order to get the best combination of both, a rapid mapping filter for discriminating rural and urban scenes is utilized. Finally, the results are fused on a feature level and connected by means of a network optimization. The approach is tested and evaluated on TerraSAR-X data containing complex urban areas and urban-rural fringe scenes.
| Original language | English |
|---|---|
| Article number | 2025123 |
| Pages (from-to) | 1294-1296 |
| Number of pages | 3 |
| Journal | IEEE Transactions on Geoscience and Remote Sensing |
| Volume | 48 |
| Issue number | 3 PART 1 |
| DOIs | |
| State | Published - 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Markov random field (MRF)
- Rapid mapping
- Road extraction
- TerraSAR-X
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