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Integrated assessment on multi-temporal and multi-sensor combinations for reducing cloud obscuration of MODIS snow cover products of the Pacific Northwest USA

机译:多时相和多传感器组合的综合评估,以减少美国西北太平洋MODIS积雪产品的云雾

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摘要

MODIS (Moderate Resolution Imaging Spectroradiometer) snow cover products, of daily, freely available, worldwide spatial extent at medium spatial resolution, have been widely applied in regional snow cover and modeling studies, although high cloud obscuration remains a concern in some applications. In this study, various approaches including daily combination, adjacent temporal deduction, fixed-day combination, flexible multi-day combination, and multi-sensor combination are assessed to remove cloud obscuration while still maintain the temporal and spatial resolutions. The performance of the resultant snow cover maps are quantitatively evaluated against in situ observations at 244 SNOTEL stations over the Pacific Northwest USA during the period of 2006-2008 hydrological years. Results indicate that daily Terra and Aqua MODIS combination and adjacent temporal deduction can reduce cloud obscuration and classification errors although an annual mean of 37% cloud coverage remains. Classification errors in snow-covered months are actually small and tend to underestimate the snow cover. Primary errors of MODIS daily, fixed and flexible multi-day combination products occur during transient months. Flexible multi-day combination is an efficient approach to maintain the balance between temporal resolution and realistic estimation of snow cover extent since it uses two thresholds to control the combination processes. Multi-sensor combinations (daily or multi-day), taking advantage of MODIS high spatial resolution and AMSR-E cloud penetration ability, provide cloud-free products but bring larger image underestimation errors as compared with their MODIS counterparts.
机译:尽管在某些应用中仍然存在高云遮盖度的问题,但MODIS(中分辨率成像光谱仪)雪覆盖产品每天在世界范围内以中等空间分辨率免费提供,在世界范围内具有中等空间分辨率,已广泛应用于区域雪覆盖和建模研究中。在这项研究中,评估了各种方法,包括每日组合,相邻时间推演,固定天组合,灵活的多天组合和多传感器组合,以消除云遮盖,同时仍保持时空分辨率。根据2006-2008年水文年期间美国西北太平洋地区244个SNOTEL站的实地观测,对所得积雪覆盖图的性能进行了定量评估。结果表明,尽管每年平均保留37%的云量,但每天将Terra和Aqua MODIS组合以及相邻的时间推断可以减少云量的模糊和分类错误。在积雪的月份中,分类错误实际上很小,并且往往会低估积雪。 MODIS每日,固定和灵活的多日组合产品的主要错误发生在过渡月份。灵活的多日组合是一种有效的方法,可以在时间分辨率和实际估计的积雪程度之间保持平衡,因为它使用两个阈值来控制组合过程。与MODIS同类产品相比,利用MODIS的高空间分辨率和AMSR-E云穿透能力的多传感器组合(每天或几天)可以提供无云产品,但带来更大的图像低估误差。

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