基于哨兵、OpenStreetMap和ArcticDEM的北极圈人造不透水区精细分辨率制图

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Big Earth Data Pub Date : 2022-02-02 DOI:10.1080/20964471.2022.2025663
Xiaoqing Xu, C. Liu, Caixia Liu, F. Hui, Xiao Cheng, Huabing Huang
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引用次数: 4

摘要

由于不透水区域被认为是城市化的关键指标,特别是环极北极地区,因此在环境和城市化研究中,人工不透水区域地图的需求很大。然而,迄今为止,在北极地区,更精细的分辨率和空间连续的不透水区域信息仍然很少。本研究利用Google Earth Engine平台,结合Sentinel-1 c波段合成孔径雷达、Sentinel-2多光谱图像、OpenStreetMap和ArcticDEM,绘制了精确完整的10 m分辨率的环极北极人造不透水区(CAMI)地图。训练随机森林分类器模型,生成相应的2020年不透水区域图。评价结果表明,与现有的3种不透水区域产品相比,CAMI的总体精度为86.36%,kappa系数为70.73%,是最准确的。基于生成的地图和OpenStreetMap,我们估计北极地区总不透水区域面积达到807.80,其中道路、工业和居民用地是三种主要的土地利用类型,分别占54.08%、17.85%和10.34%。CAMI地图将支持新的应用,并为北极基础设施脆弱性评估和环境可持续性提供先进的见解。
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Fine-resolution mapping of the circumpolar Arctic Man-made impervious areas (CAMI) using sentinels, OpenStreetMap and ArcticDEM
ABSTRACT Man-made impervious areas map is of great demand in environmental and urbanization studies since impervious areas are considered as a key indication of urbanization, especially for circumpolar Arctic. However, to date, finer resolution and spatially continuous impervious areas information remains scarce in the Arctic. In this study, we developed an accurate and complete circumpolar Arctic Man-made impervious areas (CAMI) map at a resolution of 10 m by combining Sentinel-1 C-band Synthetic Aperture Radar, Sentinel-2 multispectral images, OpenStreetMap, and ArcticDEM via Google Earth Engine platform. A random forest classifier model was trained and used to generate corresponding impervious areas map for the year 2020. The evaluation results suggested that CAMI was the most accurate with an overall accuracy of 86.36% and kappa coefficient of 70.73% as against the three existing impervious areas products. Based on the generated map and OpenStreetMap, we estimated that total impervious areas area in the Arctic has achieved 807.80 , of which roads, industrial and resident land were three major land use types, accounting for 54.08%, 17.85% and 10.34%, respectively. The CAMI map will support for new application and provide advanced insight into the infrastructure vulnerability evaluation and environmental sustainability in the Arctic.
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来源期刊
Big Earth Data
Big Earth Data Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
7.40
自引率
10.00%
发文量
60
审稿时长
10 weeks
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