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Finally, the damage proportion matrix is obtained using GIS tools.
Field survey damage proportion matrices can be used to calibrate damage proportion matrices derived from remote sensing assessment results based on Bayesian principles (Booth et al. 2011).
A calibrated damage proportion matrix was then obtained, as shown in Table 6.
By taking the expected value of various posterior beta-distributions as the damage proportion of buildings with various structure types in different disaster-affected areas, a new and calibrated damage proportion matrix is obtained.
Damage proportion For different hazard intensities, buildings of different structure types always have different damage proportions for each damage state.
Finally, the damage proportion matrix of these hazard-affected elements within selected monitoring areas can be calculated.
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Damage proportions of buildings with various structure types within areas with different disaster damage states obtained from remote sensing assessment are fitted by earthquake vulnerability probability density distribution functions as prior probability density functions.
Forest stock volume damage can be estimated using a similar process as for farmland, and, using Thematic Mapper (TM) and other satellite data, the forest stock volume of selected monitoring areas can be estimated (Tomppo et al. 2002) and the damage proportions then can be obtained (Wang et al. 2010; Zhao et al. 2014).
The statistically significant coefficients are reported for GDP, economic damages, proportion of people aged 65 and over, the political makeup of the U.S. Senate (Republican versus Democrat), and time trend.
These impact thresholds can in turn inform damage ratios, which express the economic cost required to restore infrastructure (i.e. absolute damage) by indicating the damaged proportion of the infrastructure (i.e. relative loss) (Reese and Ramsay 2010, Tarbotton et al. 2015).
We used as a surrogate measure of tract damage the proportion of the tract that was intersected by the lesion.
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