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EO4Urban: First-year results on Sentinel-1A SAR and Sentinel-2A MSI data for global urban services
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
2016 (English)In: European Space Agency, (Special Publication) ESA SP, 2016Conference paper (Refereed)
Abstract [en]

The overall objective of this research is to evaluate multitemporal Sentinel-1A SAR and Sentinel-2A MSI data for global urban services using innovative methods and algorithms, namely KTH-Pavia Urban Extractor, a robust algorithm for urban extent extraction and KTHSEG, a novel object-based classification method for detailed urban land cover mapping. Ten cities around the world in different geographical and environmental conditions were selected as study areas. Large volume of Sentinel-1A SAR and Sentinel-2A MSI data were acquired during vegetation season in 2015 and 2016. The preliminary urban extraction results showed that urban areas and small towns could be well extracted using multitemporal Sentinel-1A SAR data with the KTH-Pavia Urban Extractor. For urban land cover mapping, multitemporal Sentinel-1A SAR data alone yielded an overall classification accuracy of 60% for Stockholm. Sentinel-2A MSI data as well as the fusion of Sentinel-1A SAR and Sentinel-2A MSI data, however, produced much higher classification accuracies, both reached 80%.

Place, publisher, year, edition, pages
2016.
Keyword [en]
EO4Urban, Global urban services, KTH-SEG, Sentinel-1A SAR, Sentinel-2A MSI, Urban extractor, Extraction, Mapping, Sentinel-1, Urban services, Data mining
National Category
Remote Sensing
Identifiers
URN: urn:nbn:se:kth:diva-197093ScopusID: 2-s2.0-84988530429ISBN: 9789292213053OAI: oai:DiVA.org:kth-197093DiVA: diva2:1056039
Conference
Living Planet Symposium 2016, 9 May 2016 through 13 May 2016
Note

QC 20161213

Available from: 2016-12-13 Created: 2016-11-30 Last updated: 2016-12-13Bibliographically approved

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Other links

Scopushttp://lps16.esa.int/

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