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A Fully Automated Supraglacial lake area and volume Tracking (“FAST”) algorithm: Development and application using MODIS imagery of West Greenland

机译:一个全自动的超自然湖泊区和音量跟踪(“快速”)算法:使用West Greenland Modis Imagerery的开发和应用

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摘要

Supraglacial lakes (SGLs) on the Greenland Ice Sheet (GrIS) influence ice dynamics if they drain rapidly by hydrofracture. MODIS data are often used to investigate SGLs, including calculating SGL area changes through time, but no existing work presents a method that tracks changes to individual (and total) SGL volume in MODIS imagery over a melt season. Here, we develop such a method by first testing three automated approaches to derive SGL areas from MODIS images from the MOD09 level-2 surface-reflectance product, by comparing calculated areas for the Paakitsoq and Store Glacier regions in West Greenland with areas derived from Landsat-8 (LS8) images. Second, we apply a physically-based depth-calculation algorithm to the pixels within the SGL boundaries from the best performing area-derivation method, and compare the resultant depths with those calculated using the same method applied to LS8 imagery. Our results indicate that SGL areas are most accurately generated using dynamic thresholding of MODIS band 1 (red) MOD09 data with a 0.640 threshold value; calculated values from MODIS are closely comparable to those derived from LS8. Third, we incorporate the best performing area- and depth-detection methods into a Fully Automated SGL Tracking (“FAST”) algorithm that tracks individual SGLs between successive MODIS images. Finally, we apply the FAST algorithm to the two study regions, where it identifies 43 (Paakitsoq) and 19 (Store Glacier) rapidly draining SGLs during 2014, representing 21% and 15% of the respective total SGL populations, including some clusters of rapidly draining SGLs. The FAST algorithm improves upon existing automatic SGL tracking methods through its calculation of both SGL areas and volumes over large regions of the GrIS on a fully automatic basis. It therefore has the potential to be used for investigating statistical relationships between SGL areas, volumes and drainage events over the whole of the GrIS, and over multiple seasons, which might provide further insights into the factors that trigger rapid SGL drainage.
机译:在格陵兰冰板(GRIS)上的超透缘湖泊(SGLS)会影响冰动力学,如果它们通过水力缠结迅速排出。 MODIS数据通常用于调查SGL,包括通过时间计算SGL区域的变化,但没有现有的工作提供了一种方法,该方法跟踪MODIS图像中的单个(和总)SGL卷的变化在熔体季节。在这里,我们通过首先通过比较Paakitsoq的计算区域与Mod09电平-2表面反射产品从MOD09电平-2表面反射产品从MODIS图像推导出SGIS图像的三种自动化方法来开发这样的方法。 -8(ls8)图像。其次,我们将基于物理的深度计算算法应用于来自最佳执行区域导出方法的SGL边界内的像素,并将所得深度与应用于LS8图像的相同方法计算的那些进行比较。我们的结果表明,使用0.640阈值的MODIS频段1(红色)MOD09数据的动态阈值灵巧地,最精确地生成SGL区域;来自MODIS的计算值与来自LS8的那些密切相关。第三,我们将最佳性能的区域和深度检测方法纳入全自动的SGL跟踪(“快”)算法,其跟踪连续的MODIS图像之间的单个SGL。最后,我们将快速算法应用于两种研究区域,其中在2014年期间识别43(PaakitSoQ)和19(商店冰川)快速排出SGL,其中21%和15%的相应总SGL种群,包括迅速的一些群集排出SGL。快速算法通过计算现有的自动SGL跟踪方法,通过其计算SGL区域和GRIS的大区域,全自动地计算。因此,它有可能用于调查整个GRIS的SGL区域,卷和排水事件之间的统计关系,以及多个季节,这可能会对触发快速SGL排水的因素提供进一步的见解。

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