Using Google Earth Engine to Assess the Current State of Thermokarst Terrain on Arga Island (the Lena Delta)

Q4 Earth and Planetary Sciences Earth Pub Date : 2024-06-12 DOI:10.3390/earth5020012
A. Kartoziia
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Abstract

The mapping of thermokarst landscapes and the assessment of their conditions are becoming increasingly important in light of a rising global temperature. Land cover maps provide a basis for quantifying changes in landscapes and identifying areas that are vulnerable to permafrost degradation. The study is devoted to assessing the current state of thermokarst terrain on Arga Island. We applied a random forests algorithm using the capabilities of the Google Earth Engine cloud platform for the supervised classification of the composite image. The analyzed composite consists of a Sentinel-2 image and a set of calculated indices. The study found that thermokarst-affected terrains occupy 35% of the total area, and stable terrains cover 29% at the time of image acquisition. The classifier has also mapped water bodies, slopes, and blowouts. The accuracy assessment revealed that the overall accuracy for all the different land cover classes was 98.34%. A set of other accuracy metrics also demonstrated a high level of performance. This study presents significant findings for assessing landscape changes in a region with unique environmental features. It also provides a potential basis for future interdisciplinary research and for predicting future thermokarst landscape changes in the Lena Delta area.
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利用谷歌地球引擎评估阿尔加岛(勒拿河三角洲)的热砾岩地形现状
鉴于全球气温不断升高,绘制恒温地貌图和评估其状况变得越来越重要。土地覆盖图为量化地貌变化和确定易受永冻土退化影响的地区提供了依据。本研究致力于评估阿尔加岛热喀斯特地形的现状。我们利用谷歌地球引擎云平台的功能,采用随机森林算法对合成图像进行监督分类。分析的合成图像由哨兵-2 图像和一组计算指数组成。研究发现,在采集图像时,受热卡斯特影响的地形占总面积的 35%,稳定地形占 29%。该分类器还绘制了水体、斜坡和井喷图。精度评估显示,所有不同土地覆被等级的总体精度为 98.34%。其他一系列准确度指标也显示出较高的性能水平。这项研究为评估具有独特环境特征的地区的景观变化提供了重要发现。它还为未来的跨学科研究和预测勒拿河三角洲地区未来的热卡地貌变化提供了潜在的基础。
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Earth
Earth Earth and Planetary Sciences-Earth and Planetary Sciences (all)
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