{"title":"面向对象的高分辨率图像中建筑物损伤提取方法","authors":"L. Wang, Jinping Li, Yaohui Liu, T. Gan","doi":"10.1109/GEOINFORMATICS.2015.7378622","DOIUrl":null,"url":null,"abstract":"Building damage information is an important basis of earthquake disaster loss assessment, it is also one of judgement index of earthquake intensity. In the process of using remote sensing image for earthquake disaster information acquisition and earthquake emergency rescue, building damage information extraction technique is the key to get accurate disaster information. In this paper, based on the object-oriented and pixel-based method, we extract building earthquake damage information and accuracy evaluation of results. The results show that the object-oriented classification method to extract the feature of results in shape was consistent with the actual situation, and classification accuracy is higher and the effect is better.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Object-oriented method of building damage extraction from high-resolution images\",\"authors\":\"L. Wang, Jinping Li, Yaohui Liu, T. Gan\",\"doi\":\"10.1109/GEOINFORMATICS.2015.7378622\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Building damage information is an important basis of earthquake disaster loss assessment, it is also one of judgement index of earthquake intensity. In the process of using remote sensing image for earthquake disaster information acquisition and earthquake emergency rescue, building damage information extraction technique is the key to get accurate disaster information. In this paper, based on the object-oriented and pixel-based method, we extract building earthquake damage information and accuracy evaluation of results. The results show that the object-oriented classification method to extract the feature of results in shape was consistent with the actual situation, and classification accuracy is higher and the effect is better.\",\"PeriodicalId\":371399,\"journal\":{\"name\":\"2015 23rd International Conference on Geoinformatics\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 23rd International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GEOINFORMATICS.2015.7378622\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 23rd International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Object-oriented method of building damage extraction from high-resolution images
Building damage information is an important basis of earthquake disaster loss assessment, it is also one of judgement index of earthquake intensity. In the process of using remote sensing image for earthquake disaster information acquisition and earthquake emergency rescue, building damage information extraction technique is the key to get accurate disaster information. In this paper, based on the object-oriented and pixel-based method, we extract building earthquake damage information and accuracy evaluation of results. The results show that the object-oriented classification method to extract the feature of results in shape was consistent with the actual situation, and classification accuracy is higher and the effect is better.