{"title":"基于离散莫尔斯理论的改进路网重建","authors":"T. Dey, Jiayuan Wang, Yusu Wang","doi":"10.1145/3139958.3140031","DOIUrl":null,"url":null,"abstract":"With the rapid growth of publicly available GPS traces, robust and efficient automatic road network reconstruction has become a crucial task in GIS data analysis and applications. In [20], an effective and robust road network reconstruction algorithm was developed based on the discrete Morse theory, which has the state-of-the-art performance in automatic road-network reconstruction. Based on a discrete Morse-based graph reconstruction framework, we provide two improvements of the previous algorithm [20]: (1) we further simplify it and obtain a better empirical time performance; and (2) we develop a simple but effective editing strategy that helps adding missing road segments in the output reconstruction.","PeriodicalId":270649,"journal":{"name":"Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"1 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Improved Road Network Reconstruction using Discrete Morse Theory\",\"authors\":\"T. Dey, Jiayuan Wang, Yusu Wang\",\"doi\":\"10.1145/3139958.3140031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid growth of publicly available GPS traces, robust and efficient automatic road network reconstruction has become a crucial task in GIS data analysis and applications. In [20], an effective and robust road network reconstruction algorithm was developed based on the discrete Morse theory, which has the state-of-the-art performance in automatic road-network reconstruction. Based on a discrete Morse-based graph reconstruction framework, we provide two improvements of the previous algorithm [20]: (1) we further simplify it and obtain a better empirical time performance; and (2) we develop a simple but effective editing strategy that helps adding missing road segments in the output reconstruction.\",\"PeriodicalId\":270649,\"journal\":{\"name\":\"Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems\",\"volume\":\"1 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3139958.3140031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3139958.3140031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved Road Network Reconstruction using Discrete Morse Theory
With the rapid growth of publicly available GPS traces, robust and efficient automatic road network reconstruction has become a crucial task in GIS data analysis and applications. In [20], an effective and robust road network reconstruction algorithm was developed based on the discrete Morse theory, which has the state-of-the-art performance in automatic road-network reconstruction. Based on a discrete Morse-based graph reconstruction framework, we provide two improvements of the previous algorithm [20]: (1) we further simplify it and obtain a better empirical time performance; and (2) we develop a simple but effective editing strategy that helps adding missing road segments in the output reconstruction.