QLE.20.021 – Data-driven biodiversity management as a service for cities

Across the globe, biodiversity is under severe threat. Rapid urbanization is an important cause, consuming and fragmenting biodiversity hotspots, increasing pollution, and stimulating non-sustainable production methods. However, cities can also provide solutions. Rich ecosystems and biodiversity can exist in cities and increase citizens’ health, well-being and productiveness.
Urban biodiversity has not been widely studied. Concepts and tools for quantifying, standardizing and classifying urban ecologies and biodiversity have only recently been emerging in the literature. As a result, it is difficult for local governments to 1) acquire reliable biodiversity data across the city; 2) identify urban elements that have positive or negative effects on ecosystems; 3) design and evaluate effective interventions.
This research project aims to develop an instrument that monitors urban biodiversity and offers tools to develop and evaluate interventions to improve urban biodiversity. For this we propose a data-driven approach. Data collected from various devices, open data sources, and citizen science efforts are stored on a cloud platform. The devices include IoT sensors that measure the quality of soil, air, and water, and special purpose devices such as insect counters (e.g. Diopsis) or IoT beehives (e.g. BEEP platform) that directly tap into the ecosystem itself. We will use open data sources such as satellite images, LiDAR scans and city layout databases.
The variety and abundance of the data will be used to develop a standardized and broadly accepted urban biodiversity dashboard for policy makers. The dashboard includes several eco-indicators and so-called signal values for city districts or neighbourhoods, reliably expressing the local ecological value. The project will also deliver digital city twins to make the data actionable. The 3D digital city twins can be used to experiment with potential intervention scenarios to improve urban biodiversity.

Keywords

biodiversity, data platforms

Other organisations

Eindhoven University of Technology (TU/e), Gemeente Den Bosch, Gemeente Eindhoven, HAS, JADS, Naturalis, TU