2019
DOI: 10.1111/phor.12280
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Abstract: Rapid technological progress has made mobile devices increasingly valuable for scientific research. This paper outlines a versatile camera‐based water gauging method, implemented on smartphones, which is usable almost anywhere if 3D data is available at the targeted river section. After analysing smartphone images to detect the present water line, the image data is transferred into object space. Using the exterior orientation acquired by smartphone sensor fusion, a synthetic image originating from the 3D data … Show more

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Cited by 14 publications
(18 citation statements)
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References 39 publications
(51 reference statements)
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“…In view of the above-mentioned low-cost early warning flood systems using mobile and stationary cameras, these errors should be detected and compensated in applications of long-term observations using fixed object points in river's environment to determine the prevalent camera geometry at the time of data acquisition, e.g., using image-to-geometry registration [4,41,42]. Otherwise, image drifts can lead to false measurements of the water level, for instance considering the case that the water level increases but an image shift towards the riverbed would compensate the trend.…”
Section: Discussionmentioning
confidence: 99%
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“…In view of the above-mentioned low-cost early warning flood systems using mobile and stationary cameras, these errors should be detected and compensated in applications of long-term observations using fixed object points in river's environment to determine the prevalent camera geometry at the time of data acquisition, e.g., using image-to-geometry registration [4,41,42]. Otherwise, image drifts can lead to false measurements of the water level, for instance considering the case that the water level increases but an image shift towards the riverbed would compensate the trend.…”
Section: Discussionmentioning
confidence: 99%
“…Otherwise, image drifts can lead to false measurements of the water level, for instance considering the case that the water level increases but an image shift towards the riverbed would compensate the trend. In case of flood observation, the errors resulting from temperature-related changes in the IOP can be neglected because the reliability of water level estimation, e.g., with methods introduced by e.g., [4,43,44], decreases strongly due to large waves at the water surface that impede a unique detection of the shore line.…”
Section: Discussionmentioning
confidence: 99%
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“…Elias et al. (2019) provide an example of incorporating smartphone photogrammetry into a sensor‐fusion solution.…”
Section: The Variety Of Potential Sensors and Methods That Can Be Usementioning
confidence: 99%