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Moisture Roughness map in arctic national wildlife Refuge/Alaska

机译:北极国家野生动物避难所/阿拉斯加的湿度和粗糙度图

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We propose an algorithm to estimate moisture level of active layer of permafrost over permafrost area. This algorithm is based on Oh's semi-empirical model, and PALSAR data observed both in winter and summer seasons with vh polarization. PALSAR vh polarization data observed in winter is used to estimate surface roughness of permafrost. Then, the estimated surface roughness and PALSAR vh polarization data observed in summer is used to estimate the moisture level of the active layer of the permafrost. The moisture levels estimated from PALSAR data moderately matched to those of validation data taken in the field with correction factor of 0.6, while the surface roughness value shows some difference. The possible cause of the difference observed in the roughness value is that the surface roughness derived from the field data collection represents the roughness of the top of the sphagnum moss layer covered on the active layer of the permafrost, while the one estimated from PALSAR represents the roughness of the underlying active layer of the permafrost.
机译:我们提出了一种算法来估计多年冻土区域的活跃层的水分水平。该算法基于OH的半经验模型,并且在冬季和夏季季节观察到具有VH极化的波拉纳数据。在冬季观察到的Palsar VH偏振数据用于估计永久冻土的表面粗糙度。然后,在夏季观察到的估计表面粗糙度和波纹VH偏振数据用于估计多年冻土的有源层的水分水平。从波兰数据估计的水分含量适度匹配,与校正因子为0.6的验证数据,而表面粗糙度值显示出一些差异。在粗糙度值中观察到的可能原因是,从现场数据收集得出的表面粗糙度代表了Permafrost的有源层覆盖的SpHagnum苔藓层顶部的粗糙度,而来自波瓦拉的估计的摩尔层的粗糙度代表了永久冻土的底层活性层的粗糙度。

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