期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 8
页码：361-365
出版社：Copernicus Publications
摘要：The unprecedented snowfall during early February 2010 in the Baltimore/Washington area provided a unique opportunity to map, monitor and measure snowfall, snow cover extent, snow water equivalent (SWE), and snow melt using a suite of remote sensing instruments. Because snow cover in the Middle Atlantic area is in most years patchy and a true multi-layered snow pack is rarely established, utilizing a remote sensing approach to observe snow parameters is more challenging than in regions where falling snow and snow packs are more reliable. The Advanced Microwave Scanning Radiometer (AMSR-E) and Scanning Microwave/Instrument (SSM/I) data were used to assess SWE and the onset of melt. For this investigation, the Advanced Microwave Sounding Unit-B (AMSU-B) images were employed to detect falling snow. Snowfall observations and retrievals show that indeed falling snow signatures can be seen in high frequency brightness temperatures. Detection of falling snow is performed operationally, while retrieving falling snow rates is a new area of scientific research and still requires additional investigation. However, it is encouraging that, in general, where falling snow is occurring, on the surface below, snow cover is present. Pixels that are mixed with water seriously compromise the efficacy of snow pack observing sensors operating in the microwave portion of the electromagnetic spectrum. The Chesapeake Bay and its wide mouthed, tidewater tributaries thus negatively impacts efforts to derive SWE and snowmelt. Furthermore, the average daytime maximum temperatures in this region are well above freezing, and on occasion even the daily minimum temperatures may remain above 0o C, confounding the passive microwave algorithms used to derive SWE, which assume dry snowpack conditions. Although the passive microwave signatures illustrated in this study are clearly related to snow, it's not straightforward whether or not the signatures are due to variations in SWE or to snowpack metamorphism or to a combination of both
