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%.
Originalsprache | englisch |
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Titel | 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings |
Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers |
Seiten | 4367-4370 |
Seitenumfang | 4 |
ISBN (elektronisch) | 9781538671504 |
DOIs | |
Publikationsstatus | Veröffentlicht - 31 Okt. 2018 |
Veranstaltung | 38th Annual IEEE International Geoscience and Remote Sensing Symposium: IGARSS 2018 - Valencia, Valencia, Spanien Dauer: 22 Juli 2018 → 27 Juli 2018 https://igarss2018.org |
Publikationsreihe
Name | International Geoscience and Remote Sensing Symposium (IGARSS) |
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Band | 2018-July |
Konferenz
Konferenz | 38th Annual IEEE International Geoscience and Remote Sensing Symposium |
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Kurztitel | IGARSS |
Land/Gebiet | Spanien |
Ort | Valencia |
Zeitraum | 22/07/18 → 27/07/18 |
Internetadresse |
ASJC Scopus subject areas
- Angewandte Informatik
- Allgemeine Erdkunde und Planetologie