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Moisture Roughness map in arctic national wildlife Refuge/Alaska

机译:北极国家野生动植物保护区/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算多年冻土地区多年冻土活动层的水分含量。该算法基于Oh的半经验模型,并且在冬季和夏季以vh极化观测到的PALSAR数据。冬季观测到的PALSAR vh极化数据用于估算多年冻土的表面粗糙度。然后,将夏季观测到的估计表面粗糙度和PALSAR vh极化数据用于估算多年冻土活性层的水分含量。从PALSAR数据估算的水分含量与校正因子为0.6的现场验证数据适度匹配,而表面粗糙度值显示出一些差异。观察到的粗糙度值差异的可能原因是,由现场数据收集得出的表面粗糙度代表了覆盖在永久冻土活性层上的泥炭藓类层顶部的粗糙度,而根据PALSAR估算的粗糙度代表了永久冻土下层活动层的粗糙度。

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