{"title":"SWRO-DDPM:一种用于灾害过程动态监测的传感器Web资源本体","authors":"Nengcheng Chen, Yingbing Liu, Chao Wang, Chang Xiong, Zeqiang Chen, C. Xiao","doi":"10.1109/GEOINFORMATICS.2018.8557157","DOIUrl":null,"url":null,"abstract":"Due to the lack of a unified and comprehensive description of the dynamic disaster process monitoring, it is a great challenge to quickly and effectively share and discover more linked information resources in sensor web for the improvement of decision-making efficiency. A sensor web resource ontology for the dynamic disaster process monitoring was proposed in this paper, which can focus on the characteristics of the observation resources for diverse applications during different monitoring processes. To verify the feasibility of the method, case studies were conducted, including the semantic modeling of the in-situ monitoring and the remote sensing monitoring for flood disaster processes. The results demonstrated the effective sharing of various observation resources with different processes for environmental monitoring.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"SWRO-DDPM: A Sensor Web Resource Ontology for the Dynamic Disaster Process Monitoring\",\"authors\":\"Nengcheng Chen, Yingbing Liu, Chao Wang, Chang Xiong, Zeqiang Chen, C. Xiao\",\"doi\":\"10.1109/GEOINFORMATICS.2018.8557157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the lack of a unified and comprehensive description of the dynamic disaster process monitoring, it is a great challenge to quickly and effectively share and discover more linked information resources in sensor web for the improvement of decision-making efficiency. A sensor web resource ontology for the dynamic disaster process monitoring was proposed in this paper, which can focus on the characteristics of the observation resources for diverse applications during different monitoring processes. To verify the feasibility of the method, case studies were conducted, including the semantic modeling of the in-situ monitoring and the remote sensing monitoring for flood disaster processes. The results demonstrated the effective sharing of various observation resources with different processes for environmental monitoring.\",\"PeriodicalId\":142380,\"journal\":{\"name\":\"2018 26th International Conference on Geoinformatics\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 26th International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GEOINFORMATICS.2018.8557157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 26th International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SWRO-DDPM: A Sensor Web Resource Ontology for the Dynamic Disaster Process Monitoring
Due to the lack of a unified and comprehensive description of the dynamic disaster process monitoring, it is a great challenge to quickly and effectively share and discover more linked information resources in sensor web for the improvement of decision-making efficiency. A sensor web resource ontology for the dynamic disaster process monitoring was proposed in this paper, which can focus on the characteristics of the observation resources for diverse applications during different monitoring processes. To verify the feasibility of the method, case studies were conducted, including the semantic modeling of the in-situ monitoring and the remote sensing monitoring for flood disaster processes. The results demonstrated the effective sharing of various observation resources with different processes for environmental monitoring.
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