Satellite-based System for Monitoring Animal Population to Assess Environmental Quality Parameters
Erich H. Franke
The quality of the environmental conditions in biotopes can be assessed by observing the interaction of animals and plants in each respective area. In typical predator-prey systems, the food chain is a solid reflection of the conditions inside of the habitat. A good example is the interaction between bats and the insects these flying mammals hunt. The size of the insect population reacts rather sensitively to pollution or poisoning in a given biotope, and, since the number of hunting bats in an area depends on the available insect prey, counting bat flights on a long-term basis provides an indication of the habitat’s quality. However, counting bats is tedious a task, and human observers’ results often lack reproducibility and reliability, which lowers their significance. Automated detection, position finding, classification, and counting of bats can significantly improve the quality of the derived data.
Derived from technology originally developed for green border surveillance, the automated system detects bats’ ultrasonic “calls”. It performs a triangulation using hyperbolic navigation using three sensor heads to find out if the bats are flying in or out of the area under surveillance. Geodetic position and time synchronisation are performed through the satellite navigation system, while the data collected is transmitted to a surveillance centre through satellite communication.
The primary users will be government agencies and larger organisations responsible for environmental protection. Since these issues have become legally mandatory in Europe, authorities have to generate and publish statistics in order to prove, for example, that a new motorway or industrial area project will not have adverse effects on the environment. We anticipate higher demand in lightly populated European countries with large forests and uninhabited areas, where manpower costs are increasing.
Automated detection and counting will dramatically improve the reliability and reproducibility of environmental data and prevent it from being challenged if cited in a court of law. Furthermore, the cost of studies based on long-term observations will be significantly reduced due the much lower manpower requirements.