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An automatic water detection approach using Landsat 8 OLI and Google Earth Engine cloud computing to map lakes and reservoirs in New Zealand

机译:使用Landsat 8 OLI和Google Earth Engine云计算自动测水的方法来绘制新西兰的湖泊和水库图

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Monitoring water surface dynamics is essential for the management of lakes and reservoirs, especially those are intensively impacted by human exploitation and climatic variation. Although modern satellites have provided a superior solution over traditional methods in monitoring water surfaces, manually downloading and processing imagery associated with large study areas or long-time scales are time-consuming. The Google Earth Engine (GEE) platform provides a promising solution for this type of big data problems when it is combined with the automatic water extraction index (AWEI) to delineate multi-temporal water pixels from other forms of land use/land cover. The aim of this study is to assess the performance of a completely automatic water extraction framework by combining AWEI, GEE, and Landsat 8 OLI data over the period 2014-2018 in the case study of New Zealand. The overall accuracy (OA) of 0.85 proved the good performance of this combination. Therefore, the framework developed in this research can be used for lake and reservoir monitoring and assessment in the future. We also found that despite the temporal variability of climate duringthe period 2014-2018, the spatial areas of most of the lakes (3840) in the country remained the same at around 3742 km(2). Image fusion or aerial photos can be employed to check the areal variation of the lakes at a finer scale.
机译:监测水面动力学对于湖泊和水库的管理至关重要,尤其是那些受到人类开发和气候变化强烈影响的湖泊和水库。尽管现代卫星在监视水面方面提供了优于传统方法的出色解决方案,但是手动下载和处理与较大研究区域或长时间尺度相关的图像非常耗时。 Google Earth Engine(GEE)平台与自动水提取指数(AWEI)结合使用,可以将多时相水像素与其他形式的土地利用/土地覆盖物区分开来,为此类大数据问题提供了一个有前途的解决方案。这项研究的目的是通过结合AWEI,GEE和Landsat 8 OLI数据(在新西兰案例研究中)评估全自动水提取框架的性能,该数据在2014-2018年期间进行了评估。 0.85的整体精度(OA)证明了这种组合的良好性能。因此,本研究开发的框架可用于将来的湖泊和水库监测与评估。我们还发现,尽管2014-2018年期间气候随时间变化,该国大多数湖泊(3840)的空间面积仍保持在3742 km(2)左右。可以使用图像融合或航拍照片以更精细的比例检查湖泊的面积变化。

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