Abstract
Modern spaceborne synthetic aperture radar (SAR) sensors, such as TerraSAR-X/TanDEM-X and COSMO-SkyMed, can deliver very high resolution (VHR) data beyond the inherent spatial scales (on the order of 1m) of buildings, constituting invaluable data source for large-scale urban mapping. Processing this VHR data with advanced interferometric techniques, such as SAR tomography (TomoSAR), enables the generation of 3-D (or even 4-D) TomoSAR point clouds from space. In this paper, we present a novel and generic workflow that exploits these TomoSAR point clouds in a way that is capable to automatically produce benchmark annotated (buildings/nonbuildings) SAR datasets. These annotated datasets (building masks) have been utilized to construct and train the state-ofthe- A rt deep Fully Convolution Neural Networks with an additional Conditional Random Field represented as a Recurrent Neural Network to detect building regions in a single VHR SAR image. The results of building detection are illustrated and validated over TerraSAR-X VHR spotlight SAR image covering approximately 39 km2 . almost the whole city of Berlin . with mean pixel accuracies of around 93.84%.
Original language | English |
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Title of host publication | 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 4367-4370 |
Number of pages | 4 |
ISBN (Electronic) | 9781538671504 |
DOIs | |
Publication status | Published - 31 Oct 2018 |
Event | 38th Annual IEEE International Geoscience and Remote Sensing Symposium: IGARSS 2018 - Valencia, Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 https://igarss2018.org |
Publication series
Name | International Geoscience and Remote Sensing Symposium (IGARSS) |
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Volume | 2018-July |
Conference
Conference | 38th Annual IEEE International Geoscience and Remote Sensing Symposium |
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Abbreviated title | IGARSS |
Country/Territory | Spain |
City | Valencia |
Period | 22/07/18 → 27/07/18 |
Internet address |
Keywords
- Building Detection
- Fully Convolution Neural Networks
- OpenStreetMap
- SAR Tomography
- Synthetic Aperture Radar (SAR)
- TerraSAR-X/TanDEM-X
ASJC Scopus subject areas
- Computer Science Applications
- General Earth and Planetary Sciences