An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

Abstract

Rapid socioeconomic development in earthquake-prone areas can cause rapid changes in seismic loss risks. These changes make it difficult to ensure that risk reduction strategies are realistic, practical and effective over time. To overcome this difficulty, ongoing changes in risk should be captured timely, definitively, and accurately and then specific and well-timed adjustments of the relevant strategies should be made. However, methods for rapidly characterizing such seismic disaster risks over a large area have not been sufficiently developed. By focusing on building loss risks, this paper presents the development of an integrated method that combines remote sensing data and local OPEN ACCESSRemote Sens. 2015, 7 2544 knowledge to resolve this problem. This method includes two key interdependent steps.(1) To extract the heights and footprint areas of a large number of buildings accurately and quickly from single high-resolution optical remote sensing images; (2) To estimate the floor areas, identify structural types, develop damage probability matrixes, and determine economic parameters for calculating monetary losses due to seismic damage to the buildings by reviewing building-relevant local knowledge based on these two parameters (i.e., the building heights and footprint areas). This method is demonstrated in the Tangshan area of China. Based on the integrated method, the total floor area of the residential and public office buildings in central Tangshan in 2009 was 3.99% lower than the corresponding area number obtained by a conventional earthquake loss estimation project. Our field-based verification indicated that the mean relative error of the method for estimating the floor areas of the assessed buildings was 2.99%. A simulation of the impacts of the 1976 Ms 7.8 Tangshan earthquake using this method indicated that the total damaged floor area of the residential and public office buildings and the associated direct monetary loses in the study area could have been 8.00 and 28.73 times greater, respectively, than in 1976 if this earthquake had recurred in 2009, which is a strong warning to the local people regarding the increasing challenges they may face.

“Internet+” approach to mapping exposure and seismic vulnerability of buildings in a context of rapid socioeconomic growth: a case study in Tangshan, China

“…To improve accuracy, a great deal of post-processing work must be performed. For a large number of buildings, applying these automatic or semiautomatic procedures is more difficult, and sometimes, even impossible (Aytekin et al 2009;Durieux et al 2008;Pittore and Wieland 2013;Su et al 2015;Wieland et al 2012). The GE images we used have only red, green, and blue bands, i.e., their spectral information is much poorer than that of commercial ones, thereby aggravating such difficulties.…”

“…Bridging such gaps is important for promoting deep and practice-aimed applications of remote sensing in broad seismic vulnerability and loss risk reduction fields. By focusing on residential and public office buildings, we proposed using buildingrelevant local knowledge (Br-LK) reviews to ''bridge'' these gaps in our previous study (Su et al 2015). However, several weaknesses exist in our previous method, which challenges its broader application.…”

“…The downloaded GE images are different from commercial ones, such as, lack of imaging geometries and projection information, low spectral resolution. To ensure the associated analysis results obtained in this current study and in our previous one comparable, the two GE images were mosaicked and then registered using the GeoEye-1 images recorded in 2009 that were purchased and used in our previous study (Su et al 2015). In this registration process, 45 ground control points were used and the overall registration accuracy reached 0.7 pixels.…”

“…In the study area, over 80 % of the main streets and small alleys are currently covered. Su et al (2015) to identify the structural types of buildings in the study area In 2009, residential and public office buildings with one floor in Tangshan could be recognized as S/B; buildings with two to six floors could be identified as B/C; buildings with seven or more floors could be determined as R/C.…”

“…(2) High-resolution remote sensing imagery contains important information (e.g., footprint areas of buildings) that can be used to characterize seismic exposures and loss risks in detail. However, the techniques for accurately extracting such information have not been sufficiently developed if a large number of objects (e.g., a large number of buildings) need to be addressed over a limited Table 1 Brief summary of studies that focused on the use of remote sensing (RS) in characterizing seismic exposures, vulnerabilities, and risks of buildings (updated based on and adapted from Su et al 2015) Study type…”