Volume XLII-2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 543-550, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-543-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 543-550, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-543-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 May 2018

30 May 2018

VERSATILE MOBILE AND STATIONARY LOW-COST APPROACHES FOR HYDROLOGICAL MEASUREMENTS

M. Kröhnert and A. Eltner M. Kröhnert and A. Eltner
  • Institute for Photogrammetry and Remote Sensing, TU Dresden, 01062 Dresden, Germany

Keywords: flood monitoring, geo-crowd sourcing, image-to-geometry intersection, time lapse image analysis, smartphone application, low-cost camera system, Raspberry Pi

Abstract. In the last decades, an increase in the number of extreme precipitation events has been observed, which leads to increasing risks for flash floods and landslides. Thereby, conventional gauging stations are indispensable for monitoring and prediction. However, they are expensive in construction, management, and maintenance. Thus, density of observation networks is rather low, leading to insufficient spatio-temporal resolution to capture hydrological extreme events that occur with short response times especially in small-scale catchments. Smaller creeks and rivers require permanent observation, as well, to allow for a better understanding of the underlying processes and to enhance forecasting reliability.
Today’s smartphones with inbuilt cameras, positioning sensors and powerful processing units may serve as wide-spread measurement devices for event-based water gauging during floods. With the aid of volunteered geographic information (VGI), the hydrological network of water gauges can be highly densified in its spatial and temporal domain even for currently unobserved catchments. Furthermore, stationary low-cost solutions based on Raspberry Pi imaging systems are versatile for permanent monitoring of hydrological parameters. Both complementary systems, i.e. smartphone and Raspberry Pi camera, share the same methodology to extract water levels automatically, which is explained in the paper in detail. The annotation of 3D reference data by 2D image measurements is addressed depending on camera setup and river section to be monitored. Accuracies for water stage measurements are in range of several millimetres up to few centimetres.