Full text: Proceedings; XXI International Congress for Photogrammetry and Remote Sensing (Part B7-3)

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
neighbourhood composition, construction material and building 
location. 
Efficiency, transferability and repetition rate are important 
points that need to be considered, i.e. methods are needed that 
allow the assessment of SV in a sufficiently comprehensive way 
and that can be broadly applied in a sustainable fashion. A 
solution could be the combination of different traditional 
approaches with new methods, such as the analysis of remote 
sensing data. 
REFERENCES 
Angel, S., Bartley, K., Derr, M., et al.,2004. Rapid Urbanization 
in Tegucigalpa, Honduras. Preparing for the doubling of the 
City's Population in the next twenty-five years. Woodrow 
Wilson School of Public and International Affairs, Princeton 
University. 
Azar, D., Rain, D.,2007. Identifying population vulnerable to 
hydrological hazards in San Juan, Puerto Rico. GeoJournal. 69: 
23-43. 
Birkmann, J.,2005. Measuring Vulnerability. Report on the 1st 
meeting of the expert working group "Measuring Vulnerability" 
of the United Nations University Institute for Environment and 
Human Security (UNU-EHS). Bonn. 
Clark, G.E. et al.,1998. Assessing the vulnerability of coastal 
communities to extreme storms: the case of Revere, MA., USA. 
Mitigation and Adaptation Strategies for Global Change, 3(1): 
59-82. 
Cutter, S. L., Boruff, B. J., Shirley, W. L.,2003. Social 
Vulnerability to Environmental Hazards. Social Science 
Quarterly 82 (2): 242-260. 
Dwyer, A., Zoppou, C., Nielsen, O., Day, S., Roberts, S.,2004. 
Quantifying Social Vulnerability: A methodology for 
identifying those at risk to natural hazards. Geoscience 
Australia. 
Ebert, A., Kerle, N. Stein, A.,2007. Remote sensing based 
assessment of social vulnerability. In: Proceedings of the 5th 
international workshop on remote sensing applications to 
natural hazards, 10-11 September 2007, Washington, D.C. 
Washington, D.C. : George Washington University : The Space 
Policy Institute, 2007. art. 12. 7 p. 
Fraser, C., Baltsavias, E., Gruen, A.,2002. Processing of Ikonos 
images for submetre 3D positioning and building extraction. 
ISPRS Journal of Photogrammetry & Remote Sensing, 56, 177— 
194. 
Haki, Z., Akyuerek, Z., Duezguen, S.,2004. Assessment of 
Social Vulnerability Using Geographic Information Systems: 
Pendik, Istanbul Case Study. In Proceedings of the 7th AGILE 
Conference on Geographic Information Science. Heraklion, 
Greece. 
Herold, M., Liu, X., Clarke, K. C.,2003. Spatial Metrics and 
Image Texture for Mapping Urban Land Use. Photogrammetric 
Engineering & Remote Sensing 69 (9): 991-1001. 
Jain, S.,2005. System evolution using high resolution satellite 
data for urban regimes. Indian Institute of Technology Roorkee, 
Department of Architecture and Planning. PhD thesis. 
Kienberger, S., Steinbruch, F.2005. P-GIS and disaster risk 
management: Assessing vulnerability with P-GIS methods - 
Experiences from Büzi, Mozambique. International Conference 
on Participatory Spatial Information Management and 
Communication. PGIS '05. 
Mueller, M., Segl, K., Heiden, U., Kaufmann, H.,2006. 
Potential of High-Resolution Satellite Data in the Context of 
Vulnerability of Buildings. Natural Hazards 38: 247-258. 
Palmiano-Reganit, M.,2005. Analysis of Community's Coping 
Mechanisms in Relation to Floods: A Case Study in Naga City, 
Philippines. International Institute for Geo-Information Science 
and Earth Observation. MSc thesis. 
Rashed, T., & Weeks, J.,2003b. Exploring the spatial 
association between measures from satellite imagery and 
patterns of urban vulnerability to earthquake hazards. 
International Archives of the Photogrammetry, Remote Sensing 
and Spatial Information Sciences, XXXIV-7/W9, 144-152. 
Saaty, T. L.,1980. The analytic hierarchy process. McGraw-Hill 
International Book Company. 
Tuceryan, M., Jain, A. K.,1998. The Handbook of Pattern 
Recognition and Computer Vision. Chen, C.H., Pau, L. F., 
Wang, P. S. P. (ed.), World Scientific Publishing Co. 207-248. 
Wu, S.Y., Yamal, B., and Fisher, A.,2002, Vulnerability of 
coastal communities to sea-level rise: a case study of Cape May 
County, New Jersey, USA: Climate Research, 22: 255-270.
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.