AI- and citizen science-supported monitoring of certified biodiversity projects

The sustainable conservation and improvement of biodiversity requires solutions that are scalable and also take greater account of the responsibility of economic actors and private citizens. One approach to this is the system for certifying local biodiversity conservation initiatives, which is currently being implemented in Germany. A key element here is effective monitoring concepts, which currently pose a major challenge for technical reasons. The aim of the project is therefore to develop an AI- and citizen science-based monitoring tool that can scale biodiversity assessments for certification processes, which will be integrated into the existing AgoraNatura platform. The AI tool relies on citizen science approaches for this purpose.

To achieve this goal, existing AI algorithms will be tested for their suitability in phase 1 and the implementation of data sets will be tested. At the same time, the specific requirements for AI-supported monitoring of nature conservation projects will be analyzed in order to link them to certification standards and compare them with economic requirements. In this way, KICS-Zert contributes to the conservation of biodiversity and thus to the objectives of the research initiative. In the first phase, in addition to this initial scientific work, the project also pursues the preparation of an application for a second phase, which will focus on the implementation of the aforementioned objectives.

As a result of the implementation phase, the AI tool integrated into the certification system should promote a new certification model that enables large-scale monitoring of measures to conserve biodiversity in the environment and connects local landowners, farmers, businesses, conservationists and citizens.

Project lead: Prof. Dr. Masahiro Ryo

Leibniz Centre for Agricultural Landscape Research (ZALF)