Land cover change across the major proglacial regions of the sub-Antarctic islands, Antarctic Peninsula, and McMurdo Dry Valleys, during the 21^st century

Land cover information is essential for understanding Earth surface processes and ecosystems. Here, we use <i>K</i>-means clustering to classify Landsat 8 Operational Land Imager (OLI) images covering six proglacial sites of sub-Antarctic islands, the Antarctic Peninsula, and the McMurdo Dry Valleys at 30-m resolution. We quantify spatial patterns of water, bedrock, vegetation, and sediments to an accuracy of 77 percent. Vegetation is most abundant on South Georgia (7 percent of the proglacial area) and the South Shetland Islands (1 to 2 percent). Furthermore, we use change vector analysis (CVA) to discriminate landcover change in the twenty-first century. A latitudinal pattern is evident in ice loss and proglacial landscape change; for example, loss of ice on South Georgia and proglacial landcover change is two orders of magnitude greater than in the McMurdo Dry Valleys. Four of the studied sites had similar landscape stability (64 to 68 percent unchanged), with Alexander Island an exception (50 percent change) due to recent enhanced glacier melt. Overall, we show how landcover of proglacial regions of the climaticallysensitive sub-Antarctic and Antarctica has changed since 2000, with a CVA accuracy of 80 percent. These findings inform understanding of geomorphological activity and sediment and nutrient fluxes and hence terrestrial and marine ecosystems.

地表覆盖信息是认知地球表层过程与生态系统的关键基础。本研究采用K均值（K-means）聚类算法，对覆盖亚南极岛屿、南极半岛及麦克默多干谷共6处冰前区域、分辨率为30米的陆地卫星8号运行陆地成像仪（Operational Land Imager，OLI）影像开展分类。本研究以77%的分类精度量化了水体、基岩、植被与沉积物的空间分布格局。植被覆盖以南乔治亚岛最为丰富（占冰前区域的7%），南设得兰群岛次之（占比1%~2%）。此外，本研究借助变化向量分析（CVA）方法识别21世纪以来的地表覆盖变化。冰量损失与冰前景观变化呈现显著的纬度分布规律：例如，南乔治亚岛的冰量损失及冰前地表覆盖变化幅度较麦克默多干谷高出两个数量级。本次研究涉及的6处冰前区域中，有4处景观稳定性相近——未发生变化的区域占比为64%~68%，仅亚历山大岛例外：受近期冰川融水加剧影响，该区域的地表变化占比达50%。整体而言，本研究阐明了2000年以来气候敏感的亚南极及南极冰前区域的地表覆盖变化情况，变化向量分析（CVA）的识别精度达80%。本研究结果有助于深化对地貌活动、沉积物与营养盐通量的认知，进而为陆地与海洋生态系统的相关研究提供科学支撑。

搜集汇总

背景与挑战

背景概述

该数据集利用Landsat 8 OLI影像，通过机器学习方法对南极和亚南极六个主要冰前区域在21世纪的土地覆盖（水、基岩、植被、沉积物）进行了高精度（77%）分类和变化监测。研究发现，冰损失和景观变化存在明显的纬度差异，例如南乔治亚岛的变化量级远大于麦克默多干谷，且多数区域景观相对稳定，但亚历山大岛因冰川融化加剧而发生了显著变化。这些数据揭示了气候敏感区冰前环境的动态变化，对理解地貌过程和生态系统具有重要意义。