V. Kalaranjini, S. Dinesh Kumar, S. Ramakrishnan, R. Kokila Priya
{"title":"Burnt Area Detection Using Sar Data – A Case Study of May, 2020 Uttarakand Forest Fire","authors":"V. Kalaranjini, S. Dinesh Kumar, S. Ramakrishnan, R. Kokila Priya","doi":"10.1109/InGARSS48198.2020.9358979","DOIUrl":null,"url":null,"abstract":"Uttarakand constitutes 5.43% of Indian Forest cover with extremely and highly fire prone forest areas. The objective of this study is to assess the recent occurrence of forest fires in Uttarakand and to map the burnt areas with Sentinel-1 Synthetic Aperture Radar (SAR) and validate it with the Sentinel-2 as CoVID-19 hindered the field assessment and ground truth validation. The data is processed in Sentinel Application Platform (SNAP) and mapped with ArcGIS. Cross-validated with optical indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index NDWI, Normalized Burn Ratio (NBR) and the firsthand information from Forest Survey of India (FSI) for an area of 10. 83sq.Km, the results are summarized.","PeriodicalId":6797,"journal":{"name":"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)","volume":"1 1","pages":"241-245"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/InGARSS48198.2020.9358979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Uttarakand constitutes 5.43% of Indian Forest cover with extremely and highly fire prone forest areas. The objective of this study is to assess the recent occurrence of forest fires in Uttarakand and to map the burnt areas with Sentinel-1 Synthetic Aperture Radar (SAR) and validate it with the Sentinel-2 as CoVID-19 hindered the field assessment and ground truth validation. The data is processed in Sentinel Application Platform (SNAP) and mapped with ArcGIS. Cross-validated with optical indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index NDWI, Normalized Burn Ratio (NBR) and the firsthand information from Forest Survey of India (FSI) for an area of 10. 83sq.Km, the results are summarized.
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