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首页> 外文期刊>Irish Journal of Agricultural and Food Research >The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery
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The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery

机译:2015-2016洪水在爱尔兰洪水的农业影响为通过Sentinel 1卫星图像映射

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The capability of Sentinel 1 C-band (5 cm wavelength) synthetic aperture radio detection and ranging (RADAR) (abbreviated as SAR) for flood mapping is demonstrated, and this approach is used to map the extent of the extensive floods that occurred throughout the Republic of Ireland in the winter of 2015–2016. Thirty-three Sentinel 1 images were used to map the area and duration of floods over a 6-mo period from November 2015 to April 2016. Flood maps for 11 separate dates charted the development and persistence of floods nationally. The maximum flood extent during this period was estimated to be ~24,356 ha. The depth of rainfall influenced the magnitude of flood in the preceding 5 d and over more extended periods to a lesser degree. Reduced photosynthetic activity on farms affected by flooding was observed in Landsat 8 vegetation index difference images compared to the previous spring. The accuracy of the flood map was assessed against reports of flooding from affected farms, as well as other satellite-derived maps from Copernicus Emergency Management Service and Sentinel 2. Monte Carlo simulated elevation data (20 m resolution, 2.5 m root mean square error [RMSE]) were used to estimate the flood’s depth and volume. Although the modelled flood height showed a strong correlation with the measured river heights, differences of several metres were observed. Future mapping strategies are discussed, which include high–temporal-resolution soil moisture data, as part of an integrated multisensor approach to flood response over a range of spatial scales.
机译:对洪水映射进行哨声1 C波段(5cm波长)合成孔径无线电检测和测距(雷达)(缩写为SAR)的能力,这种方法用于绘制整个洪水的广泛洪水的程度爱尔兰共和国在2015-2016冬天。三十三个哨兵1张图片用于映射2015年11月至2016年4月的60期洪水的面积和持续时间。11个单独日期的洪水地图绘制了全国洪水的发展和持久性。在此期间的最大洪水范围估计为约24,356公顷。降雨深度影响了前面的5 d洪水的大小,并在更长的时间内到较小程度。与前一个春天相比,在Landsat 8植被指数差异图像中观察到受洪水影响的农场的光合活性降低。评估洪水图的准确性,评估了受影响的农场的洪水的报告,以及来自Copernicus紧急管理服务和Sentinel的其他卫星衍生的地图2. Monte Carlo模拟高程数据(20米分辨率,2.5米根均线误差[ RMSE]用于估计洪水的深度和体积。虽然模型洪水高度与测量的河高度表现出强烈的相关性,但观察到几米的差异。讨论了未来的映射策略,包括高时分辨率的土壤湿度数据,作为集成多传感器的一部分在一系列空间尺度上泛洪响应的一部分。

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