Automated damage analysis
Automated damage analysis
Credit:
xView2 data, processed by DLR
Automated damage analysis
After a natural disaster it is important to record the damage quickly. In DLR's 'Data4Human' project, the damage to buildings is to be recorded automatically – using intelligent methods to process data acquired using remote sensing. The example here shows damage analyses for several natural disasters in the USA – before and after Hurricanes Florence and Matthew, a flood disaster in the Midwest and the bush fire in Santa Rosa. DLR experts used the public xView2 data set for the analysis.After a natural disaster it is important to record the damage quickly. In DLR's 'Data4Human' project, the damage to buildings is to be recorded automatically – using intelligent methods to process data acquired using remote sensing. The example here shows damage analyses for several natural disasters in the USA – before and after Hurricanes Florence and Matthew, a flood disaster in the Midwest and the bush fire in Santa Rosa. DLR experts used the public xView2 data set for the analysis.
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