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Water temperature is an important parameter of water quality and influences other physical and chemical parameters. It also directly influences the survival and growth of animal and plant species in river ecosystems. In situ measurements do not allow for a total spatial coverage of water bodies and rivers that is necessary for monitoring and research at the Federal Institute of Hydrology (BfG), Germany. Hence, the ability of different remote sensing products to identify and investigate water inflows and water temperatures in Federal waterways is evaluated within the research project 'Remote sensing of water surface temperature'. The research area for a case study is the Upper and Middle Rhine River from the barrage in Iffezheim to Koblenz. Satellite products (e. g. Landsat and ASTER imagery) can only be used for rivers at least twice as wide as the spatial resolution of the satellite images. They can help to identify different water bodies only at tributaries with larger inflow volume (Main and Mosel) or larger temperature differences between the inflow (e. g. from power plants working with high capacity) and the river water. To identify and investigate also smaller water inflows and temperature differences, thermal data with better ground and thermal resolution is required. An aerial survey of the research area was conducted in late October 2013. Data of the surface was acquired with two camera systems, a digital camera with R, G, B, and Near-IR channels, and a thermal imaging camera measuring the brightness temperature in the 8-12 m wavelength region (TIR). The resolution of the TIR camera allowed for a ground resolution of 4 m, covering the whole width of the main stream and larger branches. The RGB and NIR data allowed to eliminate land surface temperatures from the analysis and to identify clouds and shadows present during the data acquisition. By degrading the spatial resolution and adding sensor noise, artificial Landsat ETM+ and TIRS datasets were created to evaluate whether the methods applied to the aerial survey data are also applicable for satellite datasets. In situ measurements were obtained from water quality measurement stations and specifically deployed temperature loggers. Two alternative methods to correct for atmospheric influences were evaluated: calibration based on in situ water temperature measurements and atmospheric correction based on atmospheric parameters modelled with MODTRAN R5. Both methods rely on input data, the former on in situ measurements of the water temperature, the latter on data from climate stations. The results are validated by the dataset of independent in situ measurements. The remaining difference of the corrected aerial survey to the in situ measurements could be reduced to 0.0±0.2 C for the calibration and 0.1±0.3 C for the atmospheric correction. The variance of the atmospheric correction proved to be larger than of the in situ calibration method, but still smaller than the variance of atmospherically corrected, real LANDSAT ETM+ data. Inflows with differing water temperatures could be identified successfully with the change point analysis method even for smaller dischargers and the mixing processes of water bodies with different temperatures could be traced into great detail. With decreasing spatial resolution and increasing sensor noise, the ability to detect inflows remained the same, but at the cost of a higher number of 'false positive' change points.
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