{"title":"结合极化sentinel-1和ALOS-2/PALSAR-2影像进行淹没植被制图","authors":"S. Plank, Martin Jussi, S. Martinis, A. Twele","doi":"10.1109/IGARSS.2017.8128303","DOIUrl":null,"url":null,"abstract":"This article presents a semi-automated methodology for mapping of flooded areas with a special focus on flooded vegetation based on polarimetric Synthetic Aperture Radar (SAR) data. C-band SAR data is well suited for mapping of open water areas, while L-band enables the extraction of detailed information of flooded vegetation. Here, dual-pol C-band data of Sentinel-1 (S-1) is combined with quad-pol L-band ALOS-2/PALSAR-2 data to enable an accurate mapping of the entire flooded area. The developed procedure combines polarimetric decomposition based unsupervised Wishart classification with object-based post-classification refinement as well as the integration of spatial contextual information and global auxiliary data. The methodology was tested at the Evros River (Greek/Turkish border region), where a flooding event occurred in spring 2015.","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"19 1","pages":"5705-5708"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Combining polarimetric sentinel-1 and ALOS-2/PALSAR-2 imagery for mapping of flooded vegetation\",\"authors\":\"S. Plank, Martin Jussi, S. Martinis, A. Twele\",\"doi\":\"10.1109/IGARSS.2017.8128303\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a semi-automated methodology for mapping of flooded areas with a special focus on flooded vegetation based on polarimetric Synthetic Aperture Radar (SAR) data. C-band SAR data is well suited for mapping of open water areas, while L-band enables the extraction of detailed information of flooded vegetation. Here, dual-pol C-band data of Sentinel-1 (S-1) is combined with quad-pol L-band ALOS-2/PALSAR-2 data to enable an accurate mapping of the entire flooded area. The developed procedure combines polarimetric decomposition based unsupervised Wishart classification with object-based post-classification refinement as well as the integration of spatial contextual information and global auxiliary data. The methodology was tested at the Evros River (Greek/Turkish border region), where a flooding event occurred in spring 2015.\",\"PeriodicalId\":6466,\"journal\":{\"name\":\"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)\",\"volume\":\"19 1\",\"pages\":\"5705-5708\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IGARSS.2017.8128303\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS.2017.8128303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combining polarimetric sentinel-1 and ALOS-2/PALSAR-2 imagery for mapping of flooded vegetation
This article presents a semi-automated methodology for mapping of flooded areas with a special focus on flooded vegetation based on polarimetric Synthetic Aperture Radar (SAR) data. C-band SAR data is well suited for mapping of open water areas, while L-band enables the extraction of detailed information of flooded vegetation. Here, dual-pol C-band data of Sentinel-1 (S-1) is combined with quad-pol L-band ALOS-2/PALSAR-2 data to enable an accurate mapping of the entire flooded area. The developed procedure combines polarimetric decomposition based unsupervised Wishart classification with object-based post-classification refinement as well as the integration of spatial contextual information and global auxiliary data. The methodology was tested at the Evros River (Greek/Turkish border region), where a flooding event occurred in spring 2015.
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