{"title":"开发用于校正空间数据交叉点的自动化工具并检查其性能","authors":"Kozo Watanabe, A. Okabe, Hideshi Nakamura","doi":"10.5638/THAGIS.21.57","DOIUrl":null,"url":null,"abstract":"In order to increase quality of spatial data and improve productivity of data creation, it is important to reduce the time spent handling errors during data preparation. This research considers a method of automatically correcting certain errors in spatial data as the first step of establishing a data creation method which reduces the manual correction of errors. Research shows that intersection redundancy with local dimensions of 1 to 50 cm make up over half of all errors. A correction tool was developed which recognizes the patterns of this type of error and automatically corrects them. The correction tool was used with real data to determine the effectiveness of this method. Results show that 73% of the total errors could be corrected automatically, greatly reducing the overall time required to process the spatial data.","PeriodicalId":177070,"journal":{"name":"Theory and Applications of GIS","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of an automated tool for correcting intersections in spatial data and the examination of its performance\",\"authors\":\"Kozo Watanabe, A. Okabe, Hideshi Nakamura\",\"doi\":\"10.5638/THAGIS.21.57\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to increase quality of spatial data and improve productivity of data creation, it is important to reduce the time spent handling errors during data preparation. This research considers a method of automatically correcting certain errors in spatial data as the first step of establishing a data creation method which reduces the manual correction of errors. Research shows that intersection redundancy with local dimensions of 1 to 50 cm make up over half of all errors. A correction tool was developed which recognizes the patterns of this type of error and automatically corrects them. The correction tool was used with real data to determine the effectiveness of this method. Results show that 73% of the total errors could be corrected automatically, greatly reducing the overall time required to process the spatial data.\",\"PeriodicalId\":177070,\"journal\":{\"name\":\"Theory and Applications of GIS\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theory and Applications of GIS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5638/THAGIS.21.57\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory and Applications of GIS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5638/THAGIS.21.57","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of an automated tool for correcting intersections in spatial data and the examination of its performance
In order to increase quality of spatial data and improve productivity of data creation, it is important to reduce the time spent handling errors during data preparation. This research considers a method of automatically correcting certain errors in spatial data as the first step of establishing a data creation method which reduces the manual correction of errors. Research shows that intersection redundancy with local dimensions of 1 to 50 cm make up over half of all errors. A correction tool was developed which recognizes the patterns of this type of error and automatically corrects them. The correction tool was used with real data to determine the effectiveness of this method. Results show that 73% of the total errors could be corrected automatically, greatly reducing the overall time required to process the spatial data.