C. McLaughlin, A. Woodley, S. Geva, Timothy Chappell, W. Kelly, W. Boles, Lance De Vine, Holly Hutson
{"title":"利用哨兵数据的基于对象的遥感","authors":"C. McLaughlin, A. Woodley, S. Geva, Timothy Chappell, W. Kelly, W. Boles, Lance De Vine, Holly Hutson","doi":"10.1109/DICTA51227.2020.9363427","DOIUrl":null,"url":null,"abstract":"Identifying changes on the Earth's surface is one of the most fundamental aspects of Earth observation from satellite images. Historically, the predominant form of analysis has measured change at a pixel level. Here, we present a new strategy that conducts the analysis based on objects. The objects are placed inside a random forest regressor. We have tested our approach in Queensland, Australia using Sentinel data. We find that the use of object-based approach either outperforms or is comparable to alternative approaches.","PeriodicalId":348164,"journal":{"name":"2020 Digital Image Computing: Techniques and Applications (DICTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Object Based Remote Sensing Using Sentinel Data\",\"authors\":\"C. McLaughlin, A. Woodley, S. Geva, Timothy Chappell, W. Kelly, W. Boles, Lance De Vine, Holly Hutson\",\"doi\":\"10.1109/DICTA51227.2020.9363427\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identifying changes on the Earth's surface is one of the most fundamental aspects of Earth observation from satellite images. Historically, the predominant form of analysis has measured change at a pixel level. Here, we present a new strategy that conducts the analysis based on objects. The objects are placed inside a random forest regressor. We have tested our approach in Queensland, Australia using Sentinel data. We find that the use of object-based approach either outperforms or is comparable to alternative approaches.\",\"PeriodicalId\":348164,\"journal\":{\"name\":\"2020 Digital Image Computing: Techniques and Applications (DICTA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Digital Image Computing: Techniques and Applications (DICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA51227.2020.9363427\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Digital Image Computing: Techniques and Applications (DICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA51227.2020.9363427","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying changes on the Earth's surface is one of the most fundamental aspects of Earth observation from satellite images. Historically, the predominant form of analysis has measured change at a pixel level. Here, we present a new strategy that conducts the analysis based on objects. The objects are placed inside a random forest regressor. We have tested our approach in Queensland, Australia using Sentinel data. We find that the use of object-based approach either outperforms or is comparable to alternative approaches.