Sentinel-1 EW mode dataset for Antarctica from 2014–2020 produced by the CASEarth Cloud Service Platform

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Big Earth Data Pub Date : 2021-10-15 DOI:10.1080/20964471.2021.1976706
Dong Liang, Huadong Guo, Lu Zhang, Haipeng Li, Xuezhi Wang
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引用次数: 12

Abstract

ABSTRACT Antarctica plays an important role in research on global change, and its unique geography, ocean, climate, and environment provide an ideal place for humankind to understand Earth’s evolution. Remote sensing provides an effective means to monitor and observe large-scale processes on the continent. Synthetic aperture radar (SAR) in particular provides the capability for all-weather Earth observation. The Sentinel-1A and Sentinel-1B SAR satellites have ideal ground coverage and imaging frequency for observing Antarctica. This study developed a dataset of 69,586 Sentinel-1 EW mode satellite images of the Antarctic ice sheet from October 2014 to December 2020. The dataset was processed with the European Space Agency Sentinel Application Platform (SNAP) and a Python batch scheduling tool on the Big Earth Data Cloud Service Platform of the Chinese Academy of Sciences Big Earth Data Science Engineering Program (CASEarth). Several data processing operations were implemented to process the raw dataset, including radiometric calibration, invalid edge removal, geocoding, data re-projection to an Antarctic projection, data compression to TIFF format, and construction of image pyramids. The dataset is available at http://www.doi.org/10.11922/sciencedb.j00076.00085.
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CASEarth云服务平台制作的2014-2020年南极Sentinel-1 EW模式数据集
南极洲在全球变化研究中占有重要地位,其独特的地理、海洋、气候和环境为人类了解地球演化提供了理想的场所。遥感为监测和观察非洲大陆的大规模进程提供了有效手段。特别是合成孔径雷达(SAR)提供了全天候对地观测的能力。Sentinel-1A和Sentinel-1B SAR卫星具有观测南极洲理想的地面覆盖和成像频率。该研究开发了2014年10月至2020年12月南极冰盖的69,586张Sentinel-1 EW模式卫星图像数据集。数据集利用欧洲航天局哨兵应用平台(SNAP)和中国科学院大地球数据科学工程项目大地球数据云服务平台(CASEarth)上的Python批调度工具进行处理。对原始数据集进行了几种数据处理操作,包括辐射校准、无效边缘去除、地理编码、数据重新投影到南极投影、数据压缩到TIFF格式以及构建图像金字塔。该数据集可在http://www.doi.org/10.11922/sciencedb.j00076.00085上获得。
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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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