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Remote monitoring of spatial and temporal surface soil moisture in fire disturbed boreal forest ecosystems with ERS SAR imagery

机译:利用ERS SAR图像远程监测火灾困扰的北方森林生态系统的时空表层土壤水分。

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Due to the large volume of carbon currently stored in boreal regions and the high frequency of wildfire, the prospects of a warming climate would have important implications for the ecology of boreal forests which in turn would have significant feedbacks for carbon cycling, fire frequency, and global climate change. Since ecological studies and climate change models require routine information on surface soil moisture, the ability to remotely sense this variable is highly desirable. Toward this end research was conducted on developing methods for the retrieval of spatially and temporally varying patterns of soil moisture from recently burned boreal forest ecosystems of Alaska using C-band satellite radar data. To do this we focused on both individual date and temporal SAR datasets to develop techniques and algorithms which indicate how moisture varies across a recently burned boreal forest. For each of the methods developed we focused on reducing errors of SAR-derived soil moisture estimates due to confounding factors of variations in vegetative biomass and surface roughness. For the individual date soil moisture monitoring, we grouped test sites by a measurable biophysical variable, burn severity, and then developed algorithms relating moisture to SAR backscatter for each burn severity group. The algorithms developed had high coefficients of determination (0.56-0.82) and the moisture maps produced had high accuracy (3.61 rms error) based on the minimal validation conducted. For the seasonal soil moisture mapping we used principal component analysis to capture the time-variant feature of soil moisture and minimize the relatively time-invariant features that confound SAR backscatter. This resulted in good agreement between the drainage maps produced and our limited in situ observations and weather data. However, further validation, with larger sample sizes, is needed. While this study focuses on Alaska, research indicates that the techniques developed should be applicable to boreal forests worldwide.
机译:由于目前北方地区储存的大量碳以及野火的频繁发生,气候变暖的前景将对北方森林的生态产生重要影响,进而对碳循环,火灾频率和碳排放产生重要反馈。全球气候变化。由于生态研究和气候变化模型需要有关表层土壤水分的常规信息,因此非常需要能够远程感知此变量的功能。为此,进行了研究,开发了利用C波段卫星雷达数据从阿拉斯加最近燃烧的北方森林生态系统中检索土壤水分时空变化格局的开发方法。为此,我们专注于单个日期和时间SAR数据集,以开发出指示最近燃烧的北方森林中水分如何变化的技术和算法。对于每种开发的方法,我们专注于减少由于植被生物量和表面粗糙度变化的混杂因素而导致的由SAR得出的土壤湿度估算值的误差。对于单个日期的土壤湿度监测,我们通过可测量的生物物理变量,燃烧严重性将测试地点分组,然后针对每个燃烧严重性组开发了将水分与SAR反向散射相关的算法。基于所进行的最少验证,所开发的算法具有较高的确定系数(0.56-0.82),并且所生成的湿度图具有较高的精度(3.61 rms误差)。对于季节性土壤水分测绘,我们使用主成分分析来捕获土壤水分的时变特征,并最小化混淆SAR反向散射的相对时变特征。这使得所制作的排水图与我们有限的现场观测和天气数据之间达成了良好的一致性。但是,需要使用更大的样本量进行进一步的验证。虽然这项研究的重点是阿拉斯加,但研究表明,开发的技术应适用于全世界的寒带森林。

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