TY - JOUR
T1 - Technical Note
T2 - Open-Source Software for Water-Level Measurement in Images With a Calibration Target
AU - Chapman, Kenneth W.
AU - Gilmore, Troy E.
AU - Chapman, Christian D.
AU - Birgand, François
AU - Mittlestet, Aaron R.
AU - Harner, Mary J.
AU - Mehrubeoglu, Mehrube
AU - Stranzl, John E.
N1 - Funding Information:
This work was supported by the U.S. Department of Agriculture—National Institute of Food and Agriculture NEB‐21‐177 (Hatch Project 1015698). Additional support was provided by the University of Nebraska Research Council through a Grant‐in‐Aid grant funded through a gift from the John C. and Nettie V. David Memorial Trust Fund. Suggestions from Frank Engel and two anonymous reviewers greatly improved the manuscript.
Funding Information:
This work was supported by the U.S. Department of Agriculture—National Institute of Food and Agriculture NEB-21-177 (Hatch Project 1015698). Additional support was provided by the University of Nebraska Research Council through a Grant-in-Aid grant funded through a gift from the John C. and Nettie V. David Memorial Trust Fund. Suggestions from Frank Engel and two anonymous reviewers greatly improved the manuscript.
Publisher Copyright:
© 2022. The Authors.
PY - 2022/8
Y1 - 2022/8
N2 - Image-based water level measurements offer data quality assurance through visual verification that no other method can provide. GaugeCam Remote Image Manager-Educational 2 (GRIME2) is a mature, open-source commercial friendly software application that automatically detects and measures water level in laboratory and field settings. The software relies on a dedicated target background for water line detection and image calibration. The system detects the change in pixel gray scale values associated with the intersection of the water level at the target surface. Fiducials on the target background are used to precisely create a pixel to real world coordinate transfer matrix and to correct for camera movement. The presented software package implements the algorithms and automates the water level measurement process, annotation of images with result overlays, creation of animations, and output of results to files that can be further analyzed in a spreadsheet or with R or Python. These GRIME2 features are illustrated using imagery from a coastal marsh field site. Tradeoffs between workflow and algorithm complexity and ease of use are discussed and future improvements are identified with the intention that this Findable, Accessible, Interoperable, and Reusable-inspired software can be adopted, modified and improved by the user community. While image resolution, quality and other factors associated with field deployment (e.g., water surface roughness, sun glare, shadows, and bio-fouling) will have an impact on measurement quality, previous controlled laboratory testing that did not manifest these issues showed potential for accuracy of ±3 mm (Gilmore et al., 2013, https://doi.org/10.1016/j.jhydrol.2013.05.011).
AB - Image-based water level measurements offer data quality assurance through visual verification that no other method can provide. GaugeCam Remote Image Manager-Educational 2 (GRIME2) is a mature, open-source commercial friendly software application that automatically detects and measures water level in laboratory and field settings. The software relies on a dedicated target background for water line detection and image calibration. The system detects the change in pixel gray scale values associated with the intersection of the water level at the target surface. Fiducials on the target background are used to precisely create a pixel to real world coordinate transfer matrix and to correct for camera movement. The presented software package implements the algorithms and automates the water level measurement process, annotation of images with result overlays, creation of animations, and output of results to files that can be further analyzed in a spreadsheet or with R or Python. These GRIME2 features are illustrated using imagery from a coastal marsh field site. Tradeoffs between workflow and algorithm complexity and ease of use are discussed and future improvements are identified with the intention that this Findable, Accessible, Interoperable, and Reusable-inspired software can be adopted, modified and improved by the user community. While image resolution, quality and other factors associated with field deployment (e.g., water surface roughness, sun glare, shadows, and bio-fouling) will have an impact on measurement quality, previous controlled laboratory testing that did not manifest these issues showed potential for accuracy of ±3 mm (Gilmore et al., 2013, https://doi.org/10.1016/j.jhydrol.2013.05.011).
KW - hydrology
KW - image processing
KW - open source software
KW - pixel to world calibration
KW - stage measurement
KW - waterline detection
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U2 - 10.1029/2022WR033203
DO - 10.1029/2022WR033203
M3 - Article
AN - SCOPUS:85137671623
SN - 0043-1397
VL - 58
JO - Water Resources Research
JF - Water Resources Research
IS - 8
M1 - e2022WR033203
ER -