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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Global Multisensor Automated satellite-based Snow and Ice Mapping System (GMASI) for cryosphere monitoring
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Global Multisensor Automated satellite-based Snow and Ice Mapping System (GMASI) for cryosphere monitoring

机译:全球多传感器自动化卫星的雪和冰映射系统(GMASI),用于冷冻圈监测

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摘要

Synergy of satellite observations in the visible infrared and microwave spectral bands presents an attractive and powerful approach to improve monitoring of the Earth's snow and ice cover. This approach is implemented in the Global Multisensor Automated Snow and Ice Mapping System (GMASI) operated by NOAA NESDIS since 2006. Combined observations in the visible and infrared from the AVHRR sensor onboard METOP satellites and in the microwave spectral bands from SSMIS onboard DMSP satellites allows for providing spatially continuous characterization of the snow and ice distribution on a daily basis. The paper presents a basic description of techniques and algorithms implemented in the system and examines the system performance in the course of the last ten years. It is demonstrated that the GMASI product adequately reproduces spatial patterns of the snow and ice distribution and their seasonal variations. Validation of GMASI daily snow retrievals over the Northern Hemisphere has demonstrated their close correspondence to surface observations of the snow cover with the yearly mean rate of over 94%. Automated maps are found to agree even better to the daily snow and ice cover map produced interactively at NOAA. In this latter case the agreement rates on the snow cover and ice cover distribution amounted correspondingly to 96% and 98%. A larger part of mismatches was due to underestimated snow and ice extent in the automated maps as compared to in situ data and interactive analysis. (C) 2017 Elsevier Inc. All rights reserved.
机译:可见红外和微波谱带中卫星观测的协同作用具有吸引力和强大的方法,以改善地球雪和冰盖的监控。自2006年以来,这种方法在全球多用户自动雪和冰映射系统(GMASI)中实施。自2006年以来由NOAA NESDIS运营的冰映射系统用于每天提供雪和冰分布的空间连续表征。本文介绍了系统中实现的技术和算法的基本描述,并在过去十年中检查了系统性能。结果表明,GMASI产品充分地再现了冰雪和冰分布的空间模式及其季节性变化。在北半球验证GMASI日常雪中检索已经证明了它们对雪覆盖的表面观察的密切对应,每年平均速度超过94%。发现自动化地图甚至相应到NOAA交互作用的日常雪和冰盖地图更好。在后一种情况下,雪覆盖和冰盖分布的协议率相应地达到96%和98%。与原位数据和交互式分析相比,较大部分的不匹配是由于自动贴图中低估的雪和冰范围。 (c)2017年Elsevier Inc.保留所有权利。

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