Multi-level geospatial modeling of human exposure patterns and vulnerability indicators

Natural Hazards

Volumn 68, Issue 1, 2013, Pages 147-163

  Aubrecht, Christoph ^a   Özceylan, Dilek ^b   Steinnocher, Klaus ^a   Freire, Sérgio ^c  

^a AIT AUSTRIAN INSTITUTE OF TECHNOLOGY   (Austria)

^b SAKARYA UNIVERSITY   (Turkey)

^c UNIVERSIDADE NOVA DE LISBOA   (Portugal)

Author keywords

Human exposure; Multi level geospatial information; Population grid; Risk reduction; Socio economic vulnerability index; Spatial disaggregation

Indexed keywords

DISASTER MANAGEMENT; EARTHQUAKE; MODELING; RISK ASSESSMENT; SEISMIC HAZARD; SOCIAL STRUCTURE; SPATIAL ANALYSIS; URBAN AREA;

TURKEY; UNITED STATES;

EID: 84880607016     PISSN: 0921030X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11069-012-0389-9     Document Type: Article

References (63)

1. Aubrecht C, Steinnocher K, Hollaus M, Wagner W (2009) Integrating earth observation and GIScience for high resolution spatial and functional modeling of urban land use. Comput Environ Urban Syst 33: 15-25.
2. Aubrecht C, Köstl M, Steinnocher K (2010a) Population exposure and impact assessment: benefits of modeling urban land use in very high spatial and thematic detail. In: Tavares JMRS, Natal Jorge RM (eds) Computational vision and medical image processing: recent trends. computational methods in applied sciences. Springer, Berlin, vol 19, pp 75-89.
3. Aubrecht C, Yetman G, Balk D, Steinnocher K (2010b) What is to be expected from broad-scale population data?-showcase accessibility model validation using high-resolution census information. In: Painho M, Santos MY, Pundt H (eds) Proceedings of AGILE 2010-The 13th AGILE international conference on geographic information science.
4. Aubrecht C, Steinnocher K, Köstl M, Züger J, Loibl W (2011a) Spatially modeled high detail population and climate prospects for a European transect-an outlook to future patterns of vulnerability. In: Guarascio M, Reniers G, Brebbia CA, Garzia F (eds) Safety and security engineering IV. WIT Transactions on the Built Environment. WIT Press, Ashurst, vol 117, pp 219-232.
5. Aubrecht C, Ungar J, Freire S (2011b) Exploring the potential of volunteered geographic information for modeling spatio-temporal characteristics of urban population: a case study for Lisbon Metro using foursquare check-in data. In: Proceedings of the 7th international conference on virtual cities and territories, Lisbon, pp 57-60.
6. Aubrecht C, Freire S, Loibl W, Steinnocher K, Ungar J (2012a) The contribution of multi-level geospatial information to assessing urban social vulnerability to earthquakes. In: Joint conference proceedings 9th international conference on urban earthquake engineering (9CUEE) & 4th Asia conference on earthquake engineering (4ACEE). Center for Urban Earthquake Engineering, Tokyo Institute of Technology, Japan, 1867-1875.
7. Aubrecht C, Freire S, Neuhold C, Curtis A, Steinnocher K (2012b) Introducing a temporal component in spatial vulnerability analysis. Disaster Adv 5(2): 48-53.
8. Balk D (2009) More than a name: why is global urban population mapping a GRUMPy proposition? In: Gamba P, Herold M (eds) Global mapping of human settlement: experiences, data sets, and prospects. Taylor & Francis series in remote sensing applications. CRC Press, Boca Raton.
9. Balk D, Brickmann M, Anderson B, Pozzi F, Yetman G (2005a). Mapping global urban and rural population distributions. Annex estimates of future global population distribution to 2015. Environmental and natural resources working paper 24, FAO, Rome, Italy.
10. Balk D, Pozzi F, Yetman G, Deichmann U, Nelson A (2005b) The distribution of people and the dimension of place: methodologies to improve the global estimation of urban extents. In: Proceedings of the 5th international symposium remote sensing of urban areas (URS 2005), Tempe, AZ, USA.
11. Balk DL, Deichmann U, Yetman G, Pozzi F, Hay SI, Nelson A (2006) Determining global population distribution: methods, applications and data. In: Hay SI, Graham AJ, Rogers DJ (eds) Global mapping of infectious diseases: methods, examples and emerging applications. Advances in parasitology. Academic Press, London, vol 62, pp 119-156.
12. Bhaduri B, Bright E, Coleman P, Dobson J (2002) LandScan: locating people is what matters. Geoinformatics 5(2): 34-37.
13. Bhaduri B, Bright E, Coleman P, Urban M (2007) LandScan USA: a high-resolution geospatial and temporal modeling approach for population distribution and dynamics. GeoJournal 69(1): 103-117.
14. Birkmann J (2007) Risk and vulnerability indicators at different scales: applicability, usefulness and policy implications. Environ Hazards 7: 20-31.
15. Buehler YA, Kellenberger TW, Small D, Itten KI (2006) Rapid mapping with remote sensing data during flooding 2005 in Switzerland by object-based methods: a case study. In: Martin-Duque JF, Brebbia CA, Emmanouloudis DE, Mander U (eds) Geo-environment and landscape evolution II. WIT Press, Ashurst.
16. Center for International Earth Science Information Network (CIESIN), and Centro Internacional de Agricultura Tropical (CIAT) (2004) Gridded population of the world, version 3 (GPWv3) and the global rural-urban mapping project, version 1 (GRUMPv1). Columbia University, Palisades, NY. Available at http://sedac. ciesin. columbia. edu/gpw. Accessed 12 July 2012.
17. Cheng Z, Caverlee J, Lee K, Sui DZ (2011) Exploring millions of footprints in location sharing services. In: Fifth international AAAI conference on weblogs and social media (ICWSM-11), Barcelona.
18. Cutter S (2003) GI science, disasters, and emergency management. Trans GIS 7(4): 439-445.
19. Deichmann U (1996) Asia medium resolution population database documentation. NCGIA, UC Santa Barbara and UNEP/GRID Geneva.
20. Deichmann U (1997) Accessibility indicators in GIS. United Nations Statistics Division, Department for Economic and Policy Analysis, New York, NY, USA.
21. Deichmann U (1998) Africa medium resolution population database documentation. NCGIA, UC Santa Barbara, UNEP/GRID Sioux Falls and World Resources Institute.
22. Deichmann U, Balk D, Yetman G (2001) Transforming population data for interdisciplinary usages: from census to grid. GPWv2 working paper. CIESIN, Columbia University, Palisades, NY, USA.
23. Dobson JE, Bright EA, Coleman PR, Durfee RC, Worley BA (2000) LandScan: a global population database for estimating populations at risk. Photogramm Eng Remote Sens 66(7): 849-857.
24. EEA European Environment Agency (2008) LMCS high resolution soil sealing layer. EIONET European topic centre on spatial information and analysis. Available at http://sia. eionet. europa. eu/CLC2006/FTSP/built-up_areas. Accessed 12 July 2012.
25. EEA European Environment Agency (2010) Mapping the impacts of natural hazards and technological accidents in Europe. Technical report 13/2010, Copenhagen, Denmark.
26. Eicher CL, Brewer CA (2001) Dasymetric mapping and areal interpolation: implementation and evaluation. Cartogr Geogr Inf Sci 28(2): 125-138.
27. Elnashai AS, Cleveland LJ, Jefferson T, Harrald JR et al (2009) Impact of new Madrid seismic zone earthquakes on the central USA, vol 2. Mid-America Earthquake Center Report 09-03, Urbana-Champaign, Illinois, USA.
28. Freire S (2010) Modeling of spatio-temporal distribution of urban population at high resolution-value for risk assessment and emergency management. In: Konecny M, Brandova TL, Zlatanova S (eds) Geographic information and cartography for risk and crisis management, Lecture notes in geoinformation and cartography. Springer, Berlin, vol 1, pp 53-67.
29. Freire S, Aubrecht C (2010) Towards improved risk assessment-mapping spatio-temporal distribution of human exposure to earthquake hazard in the Lisbon Metropolitan Area. In: Proceedings of Gi4DM 2010, international symposium on geoinformation for disaster management, Torino.
30. Freire S, Aubrecht C (2011) Assessing spatio-temporal population exposure to tsunami hazard in the lisbon metropolitan area. In: Proceedings of ISCRAM 2011, 8th international conference on information systems for crisis response and management, Lisbon, pp 5.
31. Freire S, Aubrecht C, Wegscheider S (2011) Spatio-temporal population distribution and evacuation modeling for improving tsunami risk assessment in the Lisbon metropolitan area. In: Proceedings of Gi4DM 2011, international symposium on geoinformation for disaster management, Antalya, pp 6.
32. Freire S, Aubrecht C, Wegscheider S (2012) When the tsunami comes to town-improving evacuation modeling by integrating high-resolution population exposure. In: Rothkrantz, Ristvej, Franco (eds) Proceedings of ISCRAM 2012, 9th international conference on information systems for crisis response and management. Vancouver, Canada, April 22-25, 2012 (in press).
33. Gallego FJ (2010) A population density grid of the European Union. Popul Environ 31(6): 460-473.
34. Goodall B (1987) Dictionary of human geography. Penguin, Harmondsworth.
35. Goodchild MF (2007) Citizens as sensors: the world of volunteered geography. GeoJournal 69(4): 211-221.
36. Gutiérrez J, Condeço-Melhorado A, Martín JC (2010) Using accessibility indicators and GIS to assess spatial spillovers of transport infrastructure investment. J Transp Geogr 18(1): 141-152.
37. Halden D (2003) Accessibility analysis concepts and their application to transport policy, programme and project evaluation. In: Pearman A, Mackie P, Nellthorp J (eds) Transport projects, programmes and policies: evaluation needs and capabilities. Ashgate Publishing Ltd, Hampshire, pp 227-242.
38. Havlik D, Zeug G, Aubrecht C, Steinnocher K (2011) Data sharing and integration initiatives for crisis management-what are the benefits of INSPIRE, GEOSS, SEIS and Co.?: In Knezic, Poudyal Chhetri, Ozunu (eds) Proceedings of the international emergency management society (TIEMS) 18th annual conference, Bucharest, Romania, pp 407-418.
39. Ingram JC, Franco G, Rio CR, Khazai B (2006) Post-disaster recovery dilemmas: challenges in balancing short-term and long-term needs for vulnerability reduction. Environ Sci & Policy 9(7-8): 607-613.
40. Koenig JG (1980) Indicators of urban accessibility: theory and application. Transportation 9(2): 145-172.
41. Langford M (2007) Rapid facilitation of dasymetric-based population interpolation by means of raster pixel maps. Comput Environ Urban Syst 31(1): 19-32.
42. Langford M, Higgs G, Radcliffe J, White S (2008) Urban population distribution models and service accessibility estimation. Comput Environ Urban Syst 32(1): 66-80.
43. Loibl W, Peters-Anders J (2012) Mobile phone data as source to discover spatial activity and motion patterns. In: Jekel T, Car A, Strobl J, Griesebner G (eds) G1_Forum 2012: geovizualisation, society and learning. Herbert Wichmann, VDE, Berlin/Offenbach, pp 524-533.
44. McPherson TN, Rush JF, Khalsa H, Ivey A, Brown MJ (2006) A day-night population exchange model for better exposure and consequence management assessments. In: Proceedings of the 86th AMS annual meeting, sixth symposium on the urban environment, Atlanta, GA.
45. Mennis J, Hultgren T (2006) Intelligent dasymetric mapping and its application to areal interpolation. Cartogr Geogr Inf Sc 33(3): 179-194.
46. Montgomery MR, Stern R, Cohen B, Reed H (2003) Cities transformed: demographic change and its implications in the developing world. NRC, Washington, DC.
47. Müller R, Krauß T, Lehner M, Reinartz P, Forsgren J, Rönnbäck G, Karlsson Å (2009) IMAGE2006 European coverage-methodology and results. GMES fast track land service 2006-2008, German Aerospace Center (DLR). (further information on ESA Earthnet Online, https://earth. esa. int/web/guest/content?p_r_p_564233524_assetIdentifier=esa-datasets-6287, Accessed 12 July 2012).
48. OECD Organisation for Economic Co-Operation and Development (2004). Large-scale disasters: lessons learned. Paris, France.
49. Özceylan D (2011) Social and economic vulnerability index development for disasters: an application on cities in Turkey. PhD Thesis, Social Science Institute, Sakarya University (in Turkish).
50. Özceylan D, Coşkun E (2012) The relationship between Turkey's Provinces' development levels and social and economic vulnerability to disasters. J Homel Secur Emerg Manag 9(1), Article 11.
51. Pelling M (2004) Visions of risk: a review of international indicators of disaster risk and its management. UNDP Bureau for Crisis Prevention and Recovery, Geneva.
52. Steinnocher K, Köstl M (2007) Mapping urban functions by integrating socioeconomic information, address data, and remote sensing. 2007 urban remote sensing joint event. Paris, France, April 11-13, 2007.
53. Steinnocher K, Weichselbaum J, Köstl M (2006) Linking remote sensing and demographic analysis in urbanised areas. In: Hostert P, Damm A, Schiefer S (eds) 1st EARSeL workshop of the SIG urban remote sensing, Berlin.
54. Steinnocher K, Köstl M, Weichselbaum J (2011) Grid-based population and land take trend indicators-new approaches introduced by the geoland2 core information service for spatial planning. New Techniques and Technologies for Statistics, NTTS 2011, Brussels.
55. Tobler W (1979) Smooth pycnophylactic interpolation for geographical regions. J Am Stat As 74(367): 519-530.
56. Tsubokawa H (2006) Insurance issues of catastrophic disasters in Japan: lessons from the 2005 Hurricane Katrina disaster. In Ikeda S, Fukuzono T, Sato T (eds) A better integrated management of disaster risks: toward resilient society to emerging disaster risks in mega-cities. TERRAPUB Terra Scientific Publishing Company, Tokyo, Japan, pp 193-198.
57. UNDP United Nations Development Program (2004) Reducing disaster risk: a challenge for development. UNDP Bureau for Crisis Prevention and Recovery, New York.
58. UNISDR United Nations International Strategy for Disaster Reduction (2004) Living with risk: a global review of disaster reduction initiatives, Geneva, Switzerland.
59. UNISDR United Nations International Strategy for Disaster Reduction (2009) Terminology on disaster risk reduction, Geneva, Switzerland.
60. United Nations (2006) World population prospects: the 2006 revision. Newest releases (currently 2010 revision). Available at http://esa. un. org/unpd/wpp and http://unstats. un. org. Accessed 12 July 2012.
61. Vogel C, Moser SC, Kasperson RE, Dabelko GD (2007) Linking vulnerability, adaptation, and resilience science to practice: pathways, players, and partnerships. Glob Environ Change 17: 349-364.
62. Xanthopoulos G (2007) Forest fire policy scenarios as a key element affecting the occurrence and characteristics of fire disasters. In: Proceedings of the 4th international wildland fire conference, Sevilla.
63. Yeletaysi S, Özceylan D, Fiedrich F, Harrald JR, Jefferson T (2009) A framework to integrate social vulnerability into catastrophic natural disaster preparedness planning. In: Proceedings of TIEMS 2009 annual conference, Istanbul, Turkey, pp 380-389.