Details zur Publikation

Kategorie Textpublikation
Referenztyp Tagungsbeiträge
Titel (primär) Urban social vulnerability assessment using object-oriented analysis of remote sensing and GIS data. A case study for Tegucigalpa, Honduras
Titel (sekundär) Proceedings of the XXI ISPRS Congress: Silk road for information from imagery, 3-11 July 2008, Beijing, China. Technical Commission VII, WG VII/7
Autor Ebert, A.; Kerle, N.
Herausgeber Chen, J.; Jiang, J.; van Genderen, J.
Quelle The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Erscheinungsjahr 2008
Department SUSOZ
Band/Volume XXXVII Part B7
Seite von 1307
Seite bis 1311
Sprache englisch
Keywords Social vulnerability assessment, Remote sensing, Object-oriented analysis, Proxy variables, Tegucigalpa
Abstract

This paper deals with the assessment of social vulnerability (SV) as a critical component of comprehensive disaster risk assessment. Indicators for SV relate to aspects on different scales. Individual characteristics, such as gender, age and education level, have to be assessed on a very local (individual) scale, whereas indicators such as living conditions, economic development and location of the household can be assessed on the scale of a building, building block, an administrative neighbourhood or city district. In turn, measures to reduce SV and thereby the disaster risk are taken on different levels. Information on SV is notoriously difficult to obtain, and traditionally either detailed field studies or census data have been used.This research, which was done in Tegucigalpa, Honduras, is not focused on individual people, but on the level of buildings and administrative neighbourhoods in the city, with the intention to analyse SV for a central area of 3*3 km as a potential starting point for more detailed analysis if needed. The central novelty is the use of image-based contextual, object-oriented analysis and the focus on physical proxies as indicators for SV, whereby we focus on landslide and flood hazards.Very high resolution remote sensing data, as well as GIS data and city maps were applied to delineate proxy variables with the goal to analyse four indicators for social vulnerability: (i) socio-economic status, (ii) commercial and industrial development of a neighbourhood, (iii) abundance of infrastructure/lifelines, (iv) and distance to those. The validation of the results was done using a Social Vulnerability Index (SVI) created based on census data. A subsequent stepwise regression analysis showed that eight out of 47 proxy variables were significant and could explain almost 60 % of the variation of the SVI, whereby the slope position (i.e. location of a building) and the proportion of built-up area in a neighbourhood (i.e. neighbourhood composition) were found to be the most valuable proxies. To make the approach transferable to other study areas with different data availability we also indicate where data can potentially be substituted with lower quality information than applied in this study. This work shows that contextual segmentation-based analysis of geospatial data can substantially aid in SV assessment, and, when combined with fieldbased information, leads to an optimisation of the assessment in terms of assessment frequency and costs.

dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=11119
Ebert, A., Kerle, N. (2008):
Urban social vulnerability assessment using object-oriented analysis of remote sensing and GIS data. A case study for Tegucigalpa, Honduras
In: Chen, J., Jiang, J., van Genderen, J. (eds.)
Proceedings of the XXI ISPRS Congress: Silk road for information from imagery, 3-11 July 2008, Beijing, China. Technical Commission VII, WG VII/7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XXXVII Part B7
International Society for Photogrammetry and Remote Sensing (ISPRS), 1307 - 1311