Carolin Wloczyk

Sea and lake surface temperature retrieval from Landsat thermal data in Northern Germany

Landsat thermal data are employed to derive lake and sea surface temperatures. The limitations of this approach are obvious, since the calculation of surface temperatures based solely on image data requires at least two thermal bands to compensate the atmospheric influence which is mainly caused by water vapour absorption. However, the 1 km spatial resolution of currently available multi‐band thermal satellite sensors (NOAA‐AVHRR, MODIS) is often not appropriate for lake and coastal zone applications. Therefore, it is worthwhile investigating the accuracy which can be obtained with single‐band thermal data using radiosonde information of the atmospheric water vapour column from meteorological stations in the study area. In addition, standard atmospheres from the MODTRAN code were considered that are based on seasonal climatologic values of water vapour, e.g. mid‐latitude summer, mid‐latitude winter, etc. The study area of this investigation comprises various lakes and coastal zones of the Baltic Sea in NE Germany. Landsat‐7 ETM+ imagery of nine acquisition dates was selected covering the time span from February to November 2000. Results of derived lake and sea surface temperatures were compared with in situ measurements and with an empirical model of the Deutscher Wetterdienst (Germanys National Meteorological Service, DWD). RMS deviations of 1.4 K were obtained for the satellite‐derived lake surface temperatures with respect to in situ measurements and 2.2 K with respect to the empirical DWD model. RMS deviations of 1.6 K were obtained with respect to in situ bulk temperatures in coastal zones of the Baltic Sea. This level of agreement can be considered as satisfactory given the principal constraints of this approach. A better accuracy can only be obtained with high spatial resolution (<100 m) multi‐band thermal instruments delivering imagery on an operational basis.

Estimation of instantaneous air temperature above vegetation and soil surfaces from Landsat 7 ETM+ data in northern Germany

The temperature–vegetation index method (TVX method, also called contextual method) for the area-wide mapping of instantaneous air temperature is adopted for use with Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. The method requires multispectral data consisting of bands in the red, near-infrared and thermal spectral regions, and no additional data. The approach is complemented with an iterative filtering routine for eliminating outliers and an interpolation algorithm for filling data gaps. The adopted method is applied to a multi-temporal dataset of nine ETM+ scenes, covering large parts of north-eastern Germany including the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site. Thus, for the first time the TVX method is applied to fine spatial resolution data and a central European region. The satellite-derived air temperatures (60 m spatial resolution) are compared with in situ measurements, showing an average error of about 3 K (root mean square, RMS), whereas the mean error in land surface temperature (LST) estimation is about 2 K. The results compare well with the in situ values throughout all seasons. The accuracy of about 3 K is in line with previously reported results for the TVX method (employing medium spatial resolution data) as well as for physically based approaches (ecosystem- or energy-balance models). Only remote sensing models incorporating in situ air temperature (as training data for neural networks or in multiple regression analysis) are reported to perform better in terms of RMS deviations. In the past, overestimation of air temperature by the TVX method was repeatedly observed. It is shown that the remote sensing approach tends to under- or overestimate the in situ air temperatures, depending on the in situ measurement heights. In conjunction with the attempt to assign the satellite-derived air temperature to a certain height above ground, the possibility of a simple correction for reference height is investigated. Over- and underestimations larger than 2 K seem to reflect existing differences in temperature rather than calculation errors. Furthermore, the dependence of the derived air temperature spatial pattern on different moving window sizes is shown. Possible sources of errors and limitations of the approach are discussed in detail.

Estimation of incident solar radiation on the ground from multispectral satellite sensor imagery

A simple and fast, physically based method for the estimation of global radiation is presented. It is applicable for clear‐sky multispectral satellite sensor imagery with channels at least in the VNIR region and works without the need for additional ground data. The atmospheric influence is taken into account using look‐up tables based on standard atmospheres from the MODTRAN code. The algorithm was tested with a time series of nine Landsat‐7 ETM+ scenes of a region in north‐eastern Germany. Remotely sensed global radiation is in close agreement with in situ measurements of the German Meteorological Service as indicated by RMS deviations of 20–24 W m−2 depending on the bands and atmospheric parameterization employed. The image‐derived global radiation at this level of accuracy is a useful supplement for studies in landscape ecology and related fields, for example as input for regional modelling of evapotranspiration.