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Remote Sensing-Based Quantification of the Impact of Flash Flooding on the Rice Production: A Case Study over Northeastern Bangladesh

机译:基于遥感的山洪暴发对水稻生产影响的量化:以孟加拉国东北部为例

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摘要

The northeastern region of Bangladesh often experiences flash flooding during the pre-harvesting period of the boro rice crop, which is the major cereal crop in the country. In this study, our objective was to delineate the impact of the 2017 flash flood (that initiated on 27 March 2017) on boro rice using multi-temporal Landsat-8 OLI and MODIS data. Initially, we opted to use Landsat-8 OLI data for mapping the damages; however, during and after the flooding event the acquisition of cloud free images were challenging. Thus, we used this data to map the cultivated boro rice acreage considering the planting to mature stages of the crop. Also, in order to map the extent of the damaged boro area, we utilized MODIS data as their 16-day composites provided cloud free information. Our results indicated that both the cultivated and damaged boro area estimates based on satellite data had strong relationships while compared to the ground-based estimates (i.e., r2 values approximately 0.92 for both cases, and RMSE of 18,374 and 9380 ha for cultivated and damaged areas, respectively). Finally, we believe that our study would be critical for planning and ensuring food security for the country.
机译:孟加拉国东北地区经常在硼稻作物收获前的时期遭受山洪暴发的侵袭,该时期是该国的主要谷物作物。在这项研究中,我们的目标是使用多时相Landsat-8 OLI和MODIS数据描述2017年山洪暴发(于2017年3月27日开始)对硼米的影响。最初,我们选择使用Landsat-8 OLI数据来绘制损害图;但是,在洪水事件发生期间和之后,获取无云图像具有挑战性。因此,考虑到农作物的播种到成熟阶段,我们使用这些数据绘制了栽培的硼水稻种植面积。此外,为了绘制受损波罗区域的范围,我们利用MODIS数据作为其16天合成数据提供的无云信息。我们的结果表明,与基于地面的估计相比,基于卫星数据的耕地和受损波罗面积估计值之间具有很强的相关性(即,两种情况下的r 2 值均约为0.92,RMSE为18,374)耕地和受损地区分别为9380公顷)。最后,我们认为我们的研究对于规划和确保该国的粮食安全至关重要。

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