Quantifying the building stock from optical high-resolution satellite imagery for assessing disaster risk

Abstract

This study uses high-resolution (HR) satellite imagery to quantify the stock of buildings, referred herein as building stock. The risk assessment requires information on the natural hazards and on the element at risk, that is the building stock in this article. This study combines (1) texture-based image processing to map built-up areas, (2) statistical sampling that allows locating the building samples and (3) photo-interpretation to encoding building footprints. Statistical inference is then used to quantify the building stock per class of building size. Legaspi in the Philippines is used as a case study. The results show that texture-based computer algorithms provide accurate area estimations of the built-up, that the detail of HR imagery allows the mapping of single buildings using photo-interpretation, and that a systematic sampling approach that uses building encoding and built-up maps can be used to quantify the building stock.

Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

“…Sampling has the advantage that only small subset areas of an image need to be analyzed in detail to allow for estimating summary statistics for the entire city or for well defined strata, if a stratified sampling is used [4]. Ehrlich et al [5] use a combination of texture-based image processing, statistical sampling and photo-interpretation to quantify a building stock in terms of the number of buildings, the distribution of built-up areas and building size. Full enumeration from satellite imagery refers to the detection and definition of every building within a study area.…”

Multimodal method for landslide risk analysis

“…In disaster risk management, building stock data has the advantage of identifying individual structures at risk and associating them with unique attributes such as material, height, physical vulnerability, or number of residents. However, developing such inventories is costly and time-consuming, infeasible at greater than city scale [43]. Although built-up area does not allow for delineation of individual elements at risk, it does provide the location, extent, and density of human settlement in an automated, and consistent fashion, which makes it practical tool for risk analyses when large areas or rapid assessments are needed, such as in crisis management or tracking transient displaced peoples [40,43].…”

Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period

“…The aforementioned assessment methods are mainly based on single-hazard risk analysis that generally contains three ingredients: hazard, vulnerability, and exposure of elements at risk (Cardona 2003;Crichton 1999). From a very general perspective, risk can be described as expected losses from a given hazard for a given element at risk that is denoted by a function of hazard, exposure, and vulnerability and assessed using information on these aspects (Ehrlich et al 2010).…”