Spectral tempering to model non-stationary covariance of nitrous oxide emissions from soil using continuous or categorical explanatory variables at a landscape scale
Spectral tempering to model non-stationary covariance of nitrous oxide emissions from soil using continuous or categorical explanatory variables at a landscape scale
复制标题
使用景观尺度的连续或分类解释变量对土壤一氧化二氮排放的非平稳协方差进行光谱调节
DOI：
10.1016/j.geoderma.2010.08.012
复制
发表时间：
2010
期刊：
影响因子：
6.1
通讯作者：
Haskard K
中科院分区：
文献类型：
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作者：
Haskard K
一氧化二氮的排放率从276个土壤芯的7.5公里的样带，然后这些数据的一个子集被用来计算地质统计模型，其中土地类别（土地利用和土壤类型）是固定的影响。在一个模型中，随机效应被假定为二阶平稳。在其他模型中，非平稳随机变化独立建模的自相关性和方差的空间相关成分的排放率，和块金方差。这是用光谱回火的方法完成的。将非平稳方差参数建模为离散或连续辅助变量的函数。模型中，光谱回火应用二次函数的土壤pH值拟合的数据显着优于一个固定的模型，并给出了更好的估计的预测误差方差。一个显着更好的拟合也获得了使用样条的位置模型的非平稳性，但映射的土壤协会没有提供一个显着更好的方差模型的基础。计算困难与光谱回火确定和策略，以克服他们进行了讨论。
The rate of nitrous oxide emissions was measured from 276 soil cores on a 7.5-km transect, and then a subset of these data was used to compute geostatistical models in which land categories (land-use and soil type) were fixed effects. In one model the random effects were assumed to be second-order stationary. In the other models non-stationary random variation was modelled independently for the autocorrelation and variance of the spatially correlated component of emission rate, and for the nugget variance. This was done with the method of spectral tempering. Non-stationary variance parameters were modelled as functions of discrete or continuous auxiliary variables. Models in which spectral tempering was applied using quadratic functions of soil pH fitted the data significantly better than a stationary model and gave better estimates of the prediction error variances. A significantly better fit was also obtained using splines on location to model non-stationarity, but mapped soil associations did not provide a basis for a significantly better variance model. Computational difficulties with spectral tempering are identified and strategies to overcome them are discussed.