归一化雷达烧蚀比:地中海森林烧蚀面积测绘的案例研究

IF 4.4
Yonatan Tarazona;M. A. Tanase;Vasco Mantas
{"title":"归一化雷达烧蚀比:地中海森林烧蚀面积测绘的案例研究","authors":"Yonatan Tarazona;M. A. Tanase;Vasco Mantas","doi":"10.1109/LGRS.2025.3592093","DOIUrl":null,"url":null,"abstract":"This research introduces the normalized radar burn ratio (NRBR), an index designed to enhance burned area detection using Sentinel-1 C-band radar imagery. The research utilizes postfire to prefire ratios of VV and VH backscatter coefficient to compute the NRBR, thus optimizing the contrast between the burned and unburned areas. The 2017 wildfires in Portugal were used to validate the methodology. Using the U-Net architecture, the NRBR-based model outperforms previous ratio-based indices in metrics, such as overall accuracy (OA), omission error (OE), and intersection over union, among other metrics. Additionally, high correlations (<inline-formula> <tex-math>$r \\gt 0.7$ </tex-math></inline-formula>) between NRBR and the optical indices NDVI (postfire) and dNBR were observed. This approach has promising implications for improving burned area mapping, particularly for periods with cloud cover or occlusion from fire smoke.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Normalized Radar Burn Ratio: A Case Study for Burned Area Mapping in Mediterranean Forests\",\"authors\":\"Yonatan Tarazona;M. A. Tanase;Vasco Mantas\",\"doi\":\"10.1109/LGRS.2025.3592093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research introduces the normalized radar burn ratio (NRBR), an index designed to enhance burned area detection using Sentinel-1 C-band radar imagery. The research utilizes postfire to prefire ratios of VV and VH backscatter coefficient to compute the NRBR, thus optimizing the contrast between the burned and unburned areas. The 2017 wildfires in Portugal were used to validate the methodology. Using the U-Net architecture, the NRBR-based model outperforms previous ratio-based indices in metrics, such as overall accuracy (OA), omission error (OE), and intersection over union, among other metrics. Additionally, high correlations (<inline-formula> <tex-math>$r \\\\gt 0.7$ </tex-math></inline-formula>) between NRBR and the optical indices NDVI (postfire) and dNBR were observed. This approach has promising implications for improving burned area mapping, particularly for periods with cloud cover or occlusion from fire smoke.\",\"PeriodicalId\":91017,\"journal\":{\"name\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"volume\":\"22 \",\"pages\":\"1-5\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11096539/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11096539/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究引入了归一化雷达燃烧比(NRBR),这是一种利用Sentinel-1 c波段雷达图像增强烧伤区域检测的指标。利用火灾前后VV和VH背向散射系数的比值来计算NRBR,从而优化燃烧区域和未燃烧区域的对比。2017年葡萄牙的野火被用来验证该方法。使用U-Net体系结构,基于nrbr的模型在指标方面优于以前基于比率的指标,例如总体精度(OA)、遗漏误差(OE)和交集/联合等指标。此外,NRBR与光学指数NDVI(火灾后)和dNBR之间存在高相关性($r \gt 0.7$)。这种方法有希望改善烧伤区域的测绘,特别是在有云覆盖或火灾烟雾遮挡的时期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Normalized Radar Burn Ratio: A Case Study for Burned Area Mapping in Mediterranean Forests
This research introduces the normalized radar burn ratio (NRBR), an index designed to enhance burned area detection using Sentinel-1 C-band radar imagery. The research utilizes postfire to prefire ratios of VV and VH backscatter coefficient to compute the NRBR, thus optimizing the contrast between the burned and unburned areas. The 2017 wildfires in Portugal were used to validate the methodology. Using the U-Net architecture, the NRBR-based model outperforms previous ratio-based indices in metrics, such as overall accuracy (OA), omission error (OE), and intersection over union, among other metrics. Additionally, high correlations ( $r \gt 0.7$ ) between NRBR and the optical indices NDVI (postfire) and dNBR were observed. This approach has promising implications for improving burned area mapping, particularly for periods with cloud cover or occlusion from fire smoke.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信