Identification of catchment functional units by time series of thermal remote sensing images

Abstract:

The identification of catchment functional behaviour with regard to water and energy balance is an important step during the parameterization of land surface models. An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated to identify land surface functioning as is represented in the temporal dynamics of land surface temperature (LST). For the meso-scale Attert catchment in midwestern Luxembourg, a time series of 28 TIR images from ASTER was extracted and analysed.

The persistency of the LST pattern time series is analysed in two different ways deriving summary statistics of the correlation of shifted windows across the original or transformed images and/or time steps (overall pattern persistency, pattern dynamics persistency). Both methods indicate a strong degree of consistency, which is further analysed by principal component analysis (PCA) of the LST pattern time series. Component values of the 2 most dominant components could be related for each land surface pixel to vegetation/land use data, and geology, respectively and is illustrated in Fig. 1a.

The loadings derived from PCA for each time step allow the derivation of 'most distinct' days during the time series. Taking the median temperature as a threshold value for each scene, each pixel can be classified as 'below (0)' or 'above (1)' this threshold. Consecutive dates therefore generate "binary words (sequences of 1 and 0)" representing distinct differences in LST dynamics, and allowing the separation of the landscape into functional units under radiation driven conditions (Fig. 1b).

We would argue that both information, component values from PCA as well as the functional units from 'binary words' classification, will highly improve the conceptualisation and parameterization of land surface models as they represent a real system state (surface temperature) that is the result of the complex interactions of the water and energy balance at each location in the landscape and therefore a surrogate for the functioning of the landscape under radiation driven conditions. The information would also support the planning of observational networks or filed campaigns when the task is to properly represent the spatial variability of the water and energy balance component within a catchment.