RESEARCH ON OPTIMAL OBSERVATION SCALE FOR DAMAGED BUILDINGS AFTER EARTHQUAKE BASED ON OPTIMAL FEATURE SPACE

Chen, J.; Chen, W.; Dou, A.; Li, W.; Sun, Y.

A new information extraction method of damaged buildings rooted in optimal feature space is put forward on the basis of the traditional object-oriented method. In this new method, ESP (estimate of scale parameter) tool is used to optimize the segmentation of image. Then the distance matrix and minimum separation distance of all kinds of surface features are calculated through sample selection to find the optimal feature space, which is finally applied to extract the image of damaged buildings after earthquake. The overall extraction accuracy reaches 83.1 %, the kappa coefficient 0.813. The new information extraction method greatly improves the extraction accuracy and efficiency, compared with the traditional object-oriented method, and owns a good promotional value in the information extraction of damaged buildings. In addition, the new method can be used for the information extraction of different-resolution images of damaged buildings after earthquake, then to seek the optimal observation scale of damaged buildings through accuracy evaluation. It is supposed that the optimal observation scale of damaged buildings is between 1 m and 1.2 m, which provides a reference for future information extraction of damaged buildings.

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Chen, J. / Chen, W. / Dou, A. / et al: RESEARCH ON OPTIMAL OBSERVATION SCALE FOR DAMAGED BUILDINGS AFTER EARTHQUAKE BASED ON OPTIMAL FEATURE SPACE. 2018. Copernicus Publications.

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