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Burnt Area Detection Using Sar Data – A Case Study of May, 2020 Uttarakand Forest Fire

机译:使用SAR数据的烧焦区域检测 - 以2020年5月乌塔塔拉克森林火灾的案例研究

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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.
机译:Uttarakand构成5.43%的印度森林覆盖,具有极其高度的火灾森林地区。本研究的目的是评估伊塔塔克康的最近森林火灾发生,并用哨兵-1合成孔径雷达(SAR)映射烧焦的区域,并用Sentinel-2验证,因为Covid-19阻碍了场评估和地面真理验证。数据在Sentinel应用程序平台(Snap)中处理并使用ArcGIS映射。通过光学指标交叉验证,例如归一化差异植被指数(NDVI),归一化差异水指数NDWI,标准化烧伤比(NBR)和印度森林调查的第一手信息,为10.83平方米的区域,结果总结了。

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