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Summary of Proposal LAN1904

TitleMultitemporal Terra SAR-X Data for Urban Land Cover Mapping and Monitoring
Investigator Ban, Yifang - KTH Royal Institute of Technology, Urban Planning and Environment
Team Member
Associate Gamba, Paolo - University of Pavia, Department of Electronics
SummaryIn 2008, the world crossed an invisible but momentous milestone - more than half of the people onthe planet - roughly 3.2 billion human beings - lived in cities (World Watch Institute, 2007, UN 2008). Between now and 2030,the world is expected to add an additional 2 billion urban dwellers, or 62% of the estimated global population of 8.1 billion will live in cities.Although only a small percentage of global land cover, urban areas significantly alter climate, biogeochemistry, and hydrology at local,regional, and global scales (Seto et al., 2011). Cities are hot spots of production, consumption, and waste generation. According to the United Nations, cities are responsible for 75% of global energy consumption and 80% of greenhouse gas emissions (Ash et al.,2008). For example, the impact of urban areas on atmospheric chemistry and aerosols is both pronounced and well-documented(Atkinson 2000). Urban land use influences local to regional climates through urban heat islands (Oke1982, Quattrochi and Ridd 1994), impervious surfaces alter sensible and latent heat fluxes (Offerle et al 2006), and recent evidence has suggested that cities may also significantly affect precipitation regimes (Shepherd2005). Recent studies have demonstrated that accurate representation of urban land use is both important and poorly captured in current models. Accurate and timely information on the spatial distribution and the temporal changes of urban areas is therefore critical to a wide array of research questions related to the effect of humans on the local, regional and global environment (Schneider et al., 2009). With the launch of TerraSAR-X, multitemporal high-resolution SAR data became available globally. These data provide excellent opportunities to develop effective and robust methods for mapping and monitoring urban environment. The overall objective of this research are two folds: 1) to evaluate multitemporal multi-resolution Terra SAR-X data for urban land cover mapping and change detection; and 2). to develop effective and robust object-based analysis and classification methods as well as change detection algorithms for improved urban mapping and monitoring. Several cities around the world are selected including Beijing, Dehli, Mexico City, SaoPaulo, Shanghai, Stockholm and Toronto. Archived multitemporal TerraSAR-X data in Spotlight, StripMap and ScanSARmode will be selected for urban extent extraction, detailed urban land cover mapping and change detection. It is anticipated that effective segmentation/classification algorithms as well as change detection methods will be developed for analysis of multitemproal multi-resolution TerraSAR-X data. It is also expected that the research will demonstrate the usefulness of TerraSAR-X data for urban mapping and monitoring.

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DLR 2004-2016