Abstract
Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types). At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free- and open-source basis and aim at being transparent, usable and transferable.
Highlights
A standard seismic risk model is composed of hazard, exposure and vulnerability modules [1].Exposure within the context of seismic risk assessment refers to the assets or population that is at risk when an earthquake occurs
With 77% of the building stock (86,842 buildings), 1–2 storey masonry, brick individual houses are clearly the dominating building type in the study area. 3–6 storey brick, concrete, panel multi-family building-blocks account for 8% of the building stock (8,469 buildings) and form the second most widespread residential building type followed by 7–9 storey concrete panel, frame and monolithic building-blocks with 2% of the total building stock (2,271 buildings)
This paper proposes an approach to analyze an urban environment with respect to its composition and temporal evolution patterns and to extract structures, together with their main characteristics, based on multi-sensor/multi-resolution satellite imagery
Summary
A standard seismic risk model is composed of hazard, exposure and vulnerability modules [1].Exposure within the context of seismic risk assessment refers to the assets or population that is at risk when an earthquake occurs. Due to the high spatio-temporal variability in many present-day cities, local governments are often unable to keep track of the exposed building stock and its population in order to adjust disaster risk reduction efforts . This is especially the case in developing countries where rapid urban growth is often accompanied by unplanned settlements, which rapidly change over short periods and are often highly vulnerable to natural hazards in terms of both structural and social aspects. Satellite remote sensing is increasingly being recognized as a valuable addition to established, but time- and cost-intensive, ground-based screening procedures [3]
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