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Monitoring snow parameters in boreal forest using multi-frequency SAR data

机译:使用多频SAR数据监测北方森林中的雪参数

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The northern hemisphere is characterized by the presence of boreal forest, a nearly continuous belt of coniferous trees across North America and Eurasia. This region is characterized by a subarctic and cold continental climate, showing severe winters and short summers. Precipitation varies, from about 20 cm of precipitation per year to over 200 cm and for the higher percentage is in the form of snow. Recent studies, which were carried out within the framework of ESA's CoReH2O Phase-A mission, demonstrate that multi-frequency SAR data are able to quantify the amount of snow mass (SWE) on land or glaciers. On the other-hand the presence of forest has a significant impact on the propagation of the radar signal, depending on its structure, biomass, water content and cover fraction. In particular for dense forest scattering of vegetation strongly hides the signal from snow and, consequently, compromises the sensitivity to snow parameters. A method to compensate the vegetation effect and then to retrieve snow in forested areas is presented here. The method is based on the development of an e.m. model for a snow-covered vegetated terrain and the availability of some ancillary data about forest characteristics. An example of the SWE retrieval is provided using SAR airborne data collected over a boreal test site in Finland.
机译:北半球的特点是北方森林的存在,北美北美和欧亚大陆的几乎连续的针叶树带。该地区的特点是亚科尔和寒冷的大陆气候,显示出严重的冬天和夏季。降水变化,每年约20厘米的沉淀到200厘米,较高的百分比是雪的形式。最近的研究是在ESA CoreH2O阶段的框架内进行的,证明了多频SAR数据能够量化陆地或冰川上的雪质量(SWE)。另一方面,根据其结构,生物质,含水量和覆盖部分,森林的存在对雷达信号的传播产生了重大影响。特别是对于植被的密集森林散射强烈隐藏来自雪的信号,因此,损害雪参数的敏感性。这里提出了一种弥补植被效果的方法,然后在森林地区检索雪地区。该方法基于e.m.的开发用于积雪覆盖的植物地形的模型以及一些关于森林特征的辅助数据的可用性。使用SAR空中数据在芬兰的Boreal测试网站上收集的SAR空中数据提供了SWE检索的示例。

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