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Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece

机译:评估和比较Sentinel 2A和Landsat-8操作性陆地成像仪(OLI)光谱指数,以估计希腊地中海松树生态系统中的火灾严重性

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The main purpose of this study is to explore the relationship between three field-based fire severity indices (Composite Burn Index-CBI, Geometrically structure CBI, weighted CBI) and spectral indices derived from Sentinel 2A and Landsat-8 OLI imagery on a recent large fire in Thasos, Greece. We employed remotely sensed indices previously used from the remote sensing fire community (Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), differenced NDVI, differenced NBR, relative differenced NBR, Relativized Burn Ratio) and seven Sentinel 2A-specific indices considering the availability of spectral information recorded in the red-edge spectral region. The statistical correlation indicated a slightly stronger relationship between the differenced NBR and the GeoCBI for both Sentinel 2A (r=0.872) and Landsat-8 OLI (r=0.845) imagery. Predictive local thresholds of dNBR values showed slightly higher classification accuracy for Sentinel 2A (73.33%) than Landsat-8 OLI (71.11%), suggesting the adequacy of Sentinel 2A for forest fire severity assessment and mapping in Mediterranean pine ecosystems. The evaluation of the classification thresholds calculated in this study over other fires with similar pre-fire conditions could contribute in the operational mapping and reconstruction of the historical patterns of fire severity over the Eastern Mediterranean region.
机译:这项研究的主要目的是在最近一个大型卫星上探索三个基于现场的火灾严重性指数(复合燃烧指数CBI,几何结构CBI,加权CBI)与从Sentinel 2A和Landsat-8 OLI图像得出的光谱指数之间的关系。希腊萨索斯岛大火。我们采用了以前从遥感火灾社区使用的遥感指数(归一化植被指数(NDVI),归一化燃烧比(NBR),差异化NDVI,差异化NBR,相对差异化NBR,相对燃烧率)和七个Sentinel 2A特定指标考虑到记录在红边光谱区域中的光谱信息的可用性。统计相关性表明,对于Sentinel 2A(r = 0.872)和Landsat-8 OLI(r = 0.845)图像,差异的NBR和GeoCBI之间的关系稍强。预测的dNBR值的局部阈值显示Sentinel 2A的分类准确度(73.33%)比Landsat-8 OLI的分类准确度(71.11%)略高,这表明Sentinel 2A在森林火灾严重性评估和地中海松树生态系统测绘方面具有足够的优势。在本研究中对类似火灾前条件的其他火灾的分类阈值进行评估,可能有助于在操作上绘制和重建东地中海地区火灾严重程度的历史模式。

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