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Other contributing persons, institutions or organisationseu - Funder
Other contributing persons, institutions or organisationsKröhnert, Melanie - TU Dresden - Researcher
Other contributing persons, institutions or organisationsSardemann, Hannes - TU Dresden - Researcher
Other contributing persons, institutions or organisationsSpieler, Diana - TU Dresden - Researcher
Person(s) who is (are) responsible for the content of the research dataEltner, Anette
AbstractThe dataset includes image sets and data to reference the image measurements. The image sets and datasets are used for figure 3 in the WRR manuscript 'Automatic image-based water stage measurement for long-term observations in ungauged catchments'. The image sets comprise the master images of the image sequences captured in frequent interval with Raspberry Pi cameras at the river Wesenitz and Wernersbach in Saxony, Germany. If entire image sequences (instead of single masters) are requested (they are not provided here due to large data size), please contact Anette.Eltner@tu-dresden.de
Counties, the data is referencingGERMANYde
Regions the data is referencingSaxony
Additional keywordsphotogrammetry, SfM, water stage, low-cost, image-processing
Year or period of data production2018
Publication year2018
PublisherTechnische Universität Dresden
Content of the research dataImage, Dataset: Masters of image sequences of camera-gauge Wesenitz (imgsWesenitz_*.zip) Masters of image sequences of camera-gauge Wernersbach (imgsWernersbach.zip) Dataset to retrieve 3D info at camera-gauge Wesenitz (dataWesenitz.zip) Dataset to retrieve 3D info at camera-gauge Wernersbach (dataWernersbach.zip)
Other specification of usage rights
Holder of usage rightsTechnische Universität Dresden
Usage rights of the dataCC-BY-NC-4.0
Discipline(s)Geographyde
Discipline(s)Otherde
Title of the datasetStageDetect - An image-based tool for automatic water stage detection - image dataset


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  • Automatic image-based water stage measurement for long-term observations in ungauged catchments [1]Open Access Icon
    Small scale and headwater catchments are mostly ungauged, even though their observation could help to improve the understanding of hydrological processes. However, it is expensive to build and maintain conventional measurement networks. Thus, the heterogeneous characteristics and behavior of catchments are currently not fully observed. This study introduces a method to capture water stage with a flexible low-cost camera setup. By considering the temporal signature of the water surface, water lines are automatically retrieved via image processing. The image coordinates are projected into object space to estimate the actual water stage. This requires high resolution 3D models of the river bed and bank area which are calculated in a local coordinate system with SfM, employing terrestrial as well as UAV imagery. A medium- and a small-scale catchment are investigated to assess the accuracy and reliability of the introduced method. Results reveal that the average deviation between the water stages measured with the camera gauge and a reference gauge are below 6 mm in the medium-scale catchment. Trends of water stage changes are captured reliably in both catchments. The developed approach uses a low-cost camera design in combination with image-based water level measurements and high-resolution topography from SfM. In future, adding tracking algorithms can help to densify existing gauging networks.

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