Monitoring water streets and vegetation – mDRONES4Rivers

Drones with their exciting technical development and high flexibility are still an unexploited potential for monitoring water streets and its vegetation. However, analysing the variety of vegetation and structures of the ecological flowing-water habitat pose a challenge because of required high efforts for detailed observations. Especially when centered on ground based surveys, and this even more in hard to reach areas. An excellent opportunity for drones and manned gyrocopters as tools for offering thrilling new perspectives and imagery for monitoring and measurement!

Landing phase of the drone used for the water street survey

The aim of the project mDRONES4Rivers is to develop a new monitoring and assessment solution with immediate benefit by using the latest advances in comparatively “low cost” drone and gyrocopters technology, coupled with state of the art long term ground reference measurements.

The project is supported by the German mFund, BMVI research funding. Within mDRONES4Rivers the four partners GEOCOPTIX, the Federal Institute of Hydrology  “bfg”, the University of Koblenz team up with JB Hyperspectral Devices to enable new ways of remote sensing of water streets , pairing manned Gyrocopters, unmanned drones and ground based spectral surveys.

RoX systems used for cal/vall during the flight survey

JB Hyperspectral Devices participates not only with regard to scientific observations, but beyond that allows fascinating new exploitation opportunities. The exemplary setup of a “reflectance-sensor-network“ for waterbodies is yet unique and – based on the gained experience – could be used as prototype for sensor-networks in the future. Not only the technical findings during the installation and permanent operation of measuring stations in dynamic environments of waterbodies, but also the data recall and storage is a practical illustration for running such a network. Potential customers will rely on the knowledge established during the project and so turn new sensor-networks into reality.