P. T. Dung, Man Duc Chuc, N. T. Thanh, Bui Quang Hung, D. M. Chung
{"title":"Comparison of Resampling Methods on Different Remote Sensing Images for Vietnam’s Urban Classification","authors":"P. T. Dung, Man Duc Chuc, N. T. Thanh, Bui Quang Hung, D. M. Chung","doi":"10.32913/RD-ICT.VOL2.NO15.663","DOIUrl":null,"url":null,"abstract":"Remotely-sensed data for urban classification is very diverse in data type, acquisition time, and spatial resolution. Therefore, preprocessing is needed for input data, in which the spatial resolution must be changed by different resampling methods. However, data transformations during resampling have many effects on classification results. In this research, resampling methods were evaluated. The results showed that mean aggregation and bicubic interpolation methods performed better than the rest on a variety of data types. Besides, the highest overall accuracy and the F1 score for urban classification maps were 98.47% and 0.9842, respectively. DOI: 10.32913/rd-ict.vol2.no15.663","PeriodicalId":432355,"journal":{"name":"Research and Development on Information and Communication Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research and Development on Information and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32913/RD-ICT.VOL2.NO15.663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Remotely-sensed data for urban classification is very diverse in data type, acquisition time, and spatial resolution. Therefore, preprocessing is needed for input data, in which the spatial resolution must be changed by different resampling methods. However, data transformations during resampling have many effects on classification results. In this research, resampling methods were evaluated. The results showed that mean aggregation and bicubic interpolation methods performed better than the rest on a variety of data types. Besides, the highest overall accuracy and the F1 score for urban classification maps were 98.47% and 0.9842, respectively. DOI: 10.32913/rd-ict.vol2.no15.663
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
