Time and Space Series

Several analytical tools from the field of time series analysis applied in areas such as hydrology and economic sciences have been used in soil science. They allow for the decomposition of the variability of spatial or temporal data series and to model processes of variables or vectors in space or time. This chapter focuses on spatial correlation, spectral analysis, and state-space modeling. State-space analysis is a tool borrowed from time series analysis that allows for the description of a spatial or temporal process based on two components. One is the physical or auto-or cross-covariate linkage between subsequent states of a vector. The other is the identification of signal and noise; that is, observations can be treated as an indirect reflection of the true state of a system. Spectral analysis consists of a set of analytical tools that allows for the decomposition of cyclic or periodically repeating variation of regularly sampled one-dimensional data.