{"title":"面向DMC微卫星在森林火灾遥感中的应用:基于Alsat-1产品的虚警率评估案例","authors":"Mustapha Rebhi, A. Belghoraf","doi":"10.1109/RAST.2011.5966814","DOIUrl":null,"url":null,"abstract":"In this paper, we studied the contribution of the Algerian Alsat-1 satellite image and its effects on reducing false alarm rates when detecting or monitoring forest fires. We used the classical Support Vector Machines classification method which required positive and negative database training sets. Experiments demonstrate that, such Alsat-1 images, similar products of nearest characteristics satellites ensure very lower rates of false alarm rates without treating about detecting rates.","PeriodicalId":285002,"journal":{"name":"Proceedings of 5th International Conference on Recent Advances in Space Technologies - RAST2011","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards DMC microsatellites use in forest fire remote sensing: Case of Alsat-1 product-based false alarm rate assessment\",\"authors\":\"Mustapha Rebhi, A. Belghoraf\",\"doi\":\"10.1109/RAST.2011.5966814\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we studied the contribution of the Algerian Alsat-1 satellite image and its effects on reducing false alarm rates when detecting or monitoring forest fires. We used the classical Support Vector Machines classification method which required positive and negative database training sets. Experiments demonstrate that, such Alsat-1 images, similar products of nearest characteristics satellites ensure very lower rates of false alarm rates without treating about detecting rates.\",\"PeriodicalId\":285002,\"journal\":{\"name\":\"Proceedings of 5th International Conference on Recent Advances in Space Technologies - RAST2011\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 5th International Conference on Recent Advances in Space Technologies - RAST2011\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RAST.2011.5966814\",\"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 5th International Conference on Recent Advances in Space Technologies - RAST2011","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAST.2011.5966814","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards DMC microsatellites use in forest fire remote sensing: Case of Alsat-1 product-based false alarm rate assessment
In this paper, we studied the contribution of the Algerian Alsat-1 satellite image and its effects on reducing false alarm rates when detecting or monitoring forest fires. We used the classical Support Vector Machines classification method which required positive and negative database training sets. Experiments demonstrate that, such Alsat-1 images, similar products of nearest characteristics satellites ensure very lower rates of false alarm rates without treating about detecting rates.