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Description
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Abstract. In this study we assess the practicability of applying thermal infrared (TIR) imagery for mapping surface saturation dynamics. The advantage of TIR imagery compared to other surface saturation mapping methods is its large spatial and temporal flexibility combined with a non-invasive and intuitive character. Based on an 18-month field campaign, we review and discuss the methodological principles, under which conditions the method works best and what problems may occur. These considerations enable to plan efficient TIR imagery mapping campaigns and to benefit from the full potential offered by TIR imagery, which we demonstrate with several application examples. In addition, we elaborate on image post-processing and test different methods for the generation of binary saturation maps from the TIR images. The method testing is performed on various images with different image characteristics. Results show that the best method in addition to a manual image classification is a statistical-based approach that combines distribution fitting of two pixel classes, adaptive thresholding and region growing. (2018-07-02)
***This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.5194/hess-2018-334 for the original and latest version of the publication*** (2026-07-01)
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Keyword
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Thresholding, Thermal infrared, Pixel, Computer science, Artificial intelligence, Remote sensing, Saturation (graph theory), Flexibility (engineering), Computer vision, Image (mathematics), Pattern recognition (psychology), Infrared, Mathematics, Geography, Optics, Statistics, Physics |