Remote Sensing-Based Statistical Approach for Defining Drained Lake Basins in a Continuous Permafrost Region, North Slope of Alaska
Remote Sensing-Based Statistical Approach for Defining Drained Lake Basins in a Continuous Permafrost Region, North Slope of Alaska
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DOI：
10.3390/rs13132539
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发表时间：
2021-07-01
期刊：
影响因子：
5
通讯作者：
Nitze, Ingmar
中科院分区：
文献类型：
--
作者：
Bergstedt, Helena;Jones, Benjamin M.;Nitze, Ingmar
湖泊的形成和排泄是多年冻土区普遍存在的现象。在北极地区的低地冻土区，排水湖盆（DLB）通常是最常见的地貌（占景观的50%至75%）。然而，DLB分布和丰度的详细评估是有限的。在本研究中，我们以阿拉斯加北坡为案例研究，提出了一种新颖且可扩展的基于遥感的方法来识别低地永久冻土地区的DLB。我们验证了这第一个北坡范围的DLB数据产品对几个以前公布的次区域规模的数据集和手动分类点。研究区域覆盖了> 71，000 km（2），包括现有DLB数据集以前未覆盖的> 39，000 km（2）区域。我们的方法使用Landsat-8多光谱图像和ArcticDEM数据来获得一个像素的DLB发生在不同的永冻土和冰缘景观条件的子区域的可能性，以及量化的阿拉斯加北坡的DLB的空中覆盖的像素统计评估。结果与先前发表的区域DLB数据集一致（高达87%的一致性），并显示与手动分类的随机点高度一致（DLB为64.4-95.5%，非DLB区域为83.2-95.4%）。阿拉斯加北坡的遥感为基础的统计方法的验证表明，它可能会扩展这种方法进行全面评估的DLB在泛北极低地永久冻土区。低地冻土区DLB空间分布的更好的分辨率是重要的定量研究景观多样性，野生动物栖息地，冻土，水文，岩土工程条件，高纬度碳循环。
Lake formation and drainage are pervasive phenomena in permafrost regions. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. In this study, we present a novel and scalable remote sensing-based approach to identifying DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. We validated this first North Slope-wide DLB data product against several previously published sub-regional scale datasets and manually classified points. The study area covered >71,000 km(2), including a >39,000 km(2) area not previously covered in existing DLB datasets. Our approach used Landsat-8 multispectral imagery and ArcticDEM data to derive a pixel-by-pixel statistical assessment of likelihood of DLB occurrence in sub-regions with different permafrost and periglacial landscape conditions, as well as to quantify aerial coverage of DLBs on the North Slope of Alaska. The results were consistent with previously published regional DLB datasets (up to 87% agreement) and showed high agreement with manually classified random points (64.4-95.5% for DLB and 83.2-95.4% for non-DLB areas). Validation of the remote sensing-based statistical approach on the North Slope of Alaska indicated that it may be possible to extend this methodology to conduct a comprehensive assessment of DLBs in pan-Arctic lowland permafrost regions. Better resolution of the spatial distribution of DLBs in lowland permafrost regions is important for quantitative studies on landscape diversity, wildlife habitat, permafrost, hydrology, geotechnical conditions, and high-latitude carbon cycling.