Articles | Volume 19, issue 6
Technical note
26 Jun 2015
Technical note |  | 26 Jun 2015

Technical Note: Semi-automated effective width extraction from time-lapse RGB imagery of a remote, braided Greenlandic river

C. J. Gleason, L. C. Smith, D. C. Finnegan, A. L. LeWinter, L. H Pitcher, and V. W. Chu

Abstract. River systems in remote environments are often challenging to monitor and understand where traditional gauging apparatus are difficult to install or where safety concerns prohibit field measurements. In such cases, remote sensing, especially terrestrial time-lapse imaging platforms, offer a means to better understand these fluvial systems. One such environment is found at the proglacial Isortoq River in southwestern Greenland, a river with a constantly shifting floodplain and remote Arctic location that make gauging and in situ measurements all but impossible. In order to derive relevant hydraulic parameters for this river, two true color (RGB) cameras were installed in July 2011, and these cameras collected over 10 000 half hourly time-lapse images of the river by September of 2012. Existing approaches for extracting hydraulic parameters from RGB imagery require manual or supervised classification of images into water and non-water areas, a task that was impractical for the volume of data in this study. As such, automated image filters were developed that removed images with environmental obstacles (e.g., shadows, sun glint, snow) from the processing stream. Further image filtering was accomplished via a novel automated histogram similarity filtering process. This similarity filtering allowed successful (mean accuracy 79.6 %) supervised classification of filtered images from training data collected from just 10 % of those images. Effective width, a hydraulic parameter highly correlated with discharge in braided rivers, was extracted from these classified images, producing a hydrograph proxy for the Isortoq River between 2011 and 2012. This hydrograph proxy shows agreement with historic flooding observed in other parts of Greenland in July 2012 and offers promise that the imaging platform and processing methodology presented here will be useful for future monitoring studies of remote rivers.

Short summary
Here, we give a semi-automated processing workflow to extract hydraulic parameters from over 10,000 time-lapse images of the remote Isortoq River in Greenland. This workflow allows efficient and accurate (mean accuracy 79.6%) classification of images following an automated similarity filtering process. We also give an effective width hydrograph (a proxy for discharge) for the Isortoq using this workflow, showing the potential of this workflow for enhancing understanding of remote rivers.