Sentence examples for damage proportions from inspiring English sources
Damage proportion For different hazard intensities, buildings of different structure types always have different damage proportions for each damage state.
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).
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.
Finally, the damage proportion matrix of these hazard-affected elements within selected monitoring areas can be calculated.
The important issues for post-disaster remote sensing monitoring are choice of typical disaster area, spatial resolution, damage state determination, and damage proportion calculation.
Remote sensing monitoring of selected disaster-affected areas involves four steps: remote sensing monitoring, construction of interpretation keys, damage state assignment, and damage proportion calculation.
The damage proportion matrix of buildings with various structure types within the VII-degree seismic intensity line was then obtained, as shown in Table 5.
