{"title":"基于DInSAR的表面变形自动检测","authors":"Karima Hadj-rabah, F. Hocine, A. B. Aissa","doi":"10.1145/3152808.3152819","DOIUrl":null,"url":null,"abstract":"Due to the noise of various sources present in the interferograms and the differential interferograms, the detection of surface deformations by differential interferometry (DInSAR) is thereby a difficult and complicated task. However, the adoption of a visual inspection method for the measured results interpretation can lead to false interpretations, more often in the case of small deformations; that is due to the total dependence to the detection model conceiver. In this context, the work that we present is a contribution to the methods of surface deformation detection by DInSAR, the automatic process that we propose is based on a multi-scale analysis by the discrete wavelet transform. In order to establish this latter, we generated deformation signatures by simulating a surface subsidence and integrating them into pairs of ERS1 / ERS2 sensors images acquired in the region of Ouargla in Algeria.","PeriodicalId":325654,"journal":{"name":"Proceedings of the 6th International Conference on Telecommunications and Remote Sensing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Automatic Detection of Surface Deformations by DInSAR\",\"authors\":\"Karima Hadj-rabah, F. Hocine, A. B. Aissa\",\"doi\":\"10.1145/3152808.3152819\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the noise of various sources present in the interferograms and the differential interferograms, the detection of surface deformations by differential interferometry (DInSAR) is thereby a difficult and complicated task. However, the adoption of a visual inspection method for the measured results interpretation can lead to false interpretations, more often in the case of small deformations; that is due to the total dependence to the detection model conceiver. In this context, the work that we present is a contribution to the methods of surface deformation detection by DInSAR, the automatic process that we propose is based on a multi-scale analysis by the discrete wavelet transform. In order to establish this latter, we generated deformation signatures by simulating a surface subsidence and integrating them into pairs of ERS1 / ERS2 sensors images acquired in the region of Ouargla in Algeria.\",\"PeriodicalId\":325654,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Telecommunications and Remote Sensing\",\"volume\":\"88 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Telecommunications and Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3152808.3152819\",\"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 6th International Conference on Telecommunications and Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3152808.3152819","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Detection of Surface Deformations by DInSAR
Due to the noise of various sources present in the interferograms and the differential interferograms, the detection of surface deformations by differential interferometry (DInSAR) is thereby a difficult and complicated task. However, the adoption of a visual inspection method for the measured results interpretation can lead to false interpretations, more often in the case of small deformations; that is due to the total dependence to the detection model conceiver. In this context, the work that we present is a contribution to the methods of surface deformation detection by DInSAR, the automatic process that we propose is based on a multi-scale analysis by the discrete wavelet transform. In order to establish this latter, we generated deformation signatures by simulating a surface subsidence and integrating them into pairs of ERS1 / ERS2 sensors images acquired in the region of Ouargla in Algeria.