Title :
A Soft Computing Method for Damage Mapping Using VHR Optical Satellite Imagery
Author :
Mansouri, Babak ; Hamednia, Yaser
Author_Institution :
Dept. of Emergency Manage., Int. Inst. of Earthquake Eng. & Seismol., Tehran, Iran
Abstract :
In this research, the feasibility of a method based on some soft computing algorithms for earthquake damage mapping is sought. The idea is to classify different patterns of change associated with building footprints and to detect distinct damage levels. A fuzzy inference methodology is employed to determine the damage grade for individual building roofs by the means of evaluating the contribution of different patterns of changes. For implementation, satellite images of before and after the 2003 Bam, Iran earthquake, are used in addition to some available ancillary data. Building footprint pixels were extracted from pre- and postimages using the ancillary building mask. Haralick second-order textural features were computed for the building objects and an optimum set of such features was selected using genetic algorithm (GA). Considering optimal indices, different parts of roofs were classified into three change patterns as “low change,” “moderate change,” and “severe change” employing a support vector machine (SVM) algorithm. For each building footprint, the contribution of each class was calculated as the input of a fuzzy inference system (FIS). Mamdani fuzzy engine was used to determine the damage grade of each building. The proposed algorithm was evaluated by comparing the produced damage map with a reference damage map (ground truth). The results demonstrated the efficacy of the method showing overall accuracies of 76% for detecting three levels of structural damage (no to slight, moderate, and heavy to destruction) and 89% for determining binary damage levels (no-collapsed, and collapsed) as suitable for such overall monitoring process.
Keywords :
buildings (structures); earthquakes; feature extraction; fuzzy logic; genetic algorithms; geophysical image processing; image texture; pattern classification; remote sensing; support vector machines; AD 2003; Bam; Haralick second-order textural feature; Iran earthquake; Mamdani fuzzy engine; VHR optical satellite imagery; ancillary building mask; building footprint pixel; building roof; damage level; earthquake damage mapping; ferature extraction; fuzzy inference methodology; fuzzy inference system; genetic algorithm; reference damage map; satellite images; soft computing algorithm; support vector machine algorithm; Feature extraction; Fuzzy logic; Genetic algorithms; Image texture analysis; Optical imaging; Support vector machines; Urban areas; Fuzzy logic; genetic algorithm (GA); image texture analysis; satellite applications; urban areas;
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2015.2493342