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Burn area mapping in Google Earth Engine (GEE) cloud platform: 2019 forest fires in eastern Australia

机译:谷歌地球发动机(Gee)云平台烧毁区域映射:2019年澳大利亚东部的森林火灾

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Forest fires occur throughout the year in rainforests and deserts of Australia. The disastrous bush fire event occurred during November 2019, and lasted until February 2020, destroying more than 46 million acres of land. Burn area mapping is a major parameter in carrying out mitigation measures and regrowth activities by forest officials or fire managers post fire event. In this study, multi-temporal satellite datasets such as images acquired from Sentinel-2 (S2) and Landsat-8 (L8) missions are used to map the burn areas. Two thematic indices such as Differenced Normalized Burn Ratio (dNBR) and Relativized Burn Ratio (RBR) are implemented on the study area. The entire analysis, i.e., accessing the datasets, preprocessing, and calculation of indices for brunt area mapping is carried out on Google Earth Engine cloud platform. Rather than ground survey, the active fire product VIIRS product (VNP14IMGTDL) is used as a proxy for the actual fire indices in accuracy assessment. Results revealed that RBR showed better accuracy than dNBR for both the datasets (S2 and L8). S2 burn severity maps of dNBR and RBR showed better accuracy than L8 burn severity maps because of S2 having a higher spatial resolution. Thus, S2 datasets can be useful for rapid mapping of burn areas with improved spatial as well as temporal resolution.
机译:森林火灾全年在雨林和澳大利亚沙漠中发生。灾难性的丛林火灾活动发生在2019年11月期间,并持续到2020年2月,摧毁了超过4600万英亩的土地。烧伤区映射是森林官员或消防经理在火灾活动中进行缓解措施和再生活动的主要参数。在该研究中,使用来自Sentinel-2(S2)和Landsat-8(L8)任务获取的图像的多时间卫星数据集用于映射烧伤区域。在研究区域中实施了两个主题指数,例如差异归一化烧伤比(DNBR)和相对烧伤比(RBR)。在Google地球发动机云平台上执行整个分析,即访问数据集,预处理,预处理和交立区域映射指数计算。 Active Fire Product Viirs产品(VNP14IMGTDL)而不是地面调查,而不是地面调查,用作准确性评估中实际消防指标的代理。结果表明,RBR显示比DNBR的准确性更好(S2和L8)。由于S2具有更高的空间分辨率,S2 DNBR和RBR的烧伤严重性地图显示比L8烧伤严重性映射更好。因此,S2数据集可用于快速映射燃烧区域,其具有改进的空间以及时间分辨率。

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