Abstract
Earth observation technologies can provide a significant contribution to the monitoring urban areas and critical infrastructures. In this paper, we show how to exploit the recently introduced multitemporal SAR RGB images of the Level-1α and Level-1β family in these applications. Simple, ad hoc algorithms are discussed to adapt these generalist products to the specific case study. In particular, self-organizing map clustering and object-based image analysis are used for urban area mapping. As for infrastructure monitoring, an application concerning railway monitoring is discussed.
Original language | English |
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Title of host publication | 2017 Joint Urban Remote Sensing Event, JURSE 2017 |
Publisher | IEEE |
Number of pages | 4 |
ISBN (Electronic) | 9781509058082 |
ISBN (Print) | 9781509058099 |
DOIs | |
Publication status | Published - 10 May 2017 |
Event | 2017 Joint Urban Remote Sensing Event, JURSE 2017 - Dubai, UAE United Arab Emirates Duration: 6 Mar 2017 → 8 Mar 2017 |
Conference
Conference | 2017 Joint Urban Remote Sensing Event, JURSE 2017 |
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Country/Territory | UAE United Arab Emirates |
City | Dubai |
Period | 6/03/17 → 8/03/17 |
ASJC Scopus subject areas
- Signal Processing
- Urban Studies
- Management, Monitoring, Policy and Law
- Instrumentation