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Spatial Use Collision Risk Model

(Raumnutzungs-Kollisionsrisikomodell | RKR-Modell)

The Spatial Use Collision Risk Model (Raumnutzungs-Kollisionsmodell | RKRM) is an analytical tool designed to assess and minimise potential conflicts between different types of spatial use. It is particularly applied in urban planning, transport planning and environmental management. The model considers interactions between various actors—such as drivers, pedestrians, cyclists and wildlife—as well as the influence of infrastructure, including roads, pathways and buildings.

At its core, the RKRM aims to develop preventive measures to reduce the risk of accidents or disturbances in public spaces. To achieve this, data on traffic patterns, user behaviour and geographical conditions are collected and analysed. Using simulations and scenario analyses, potential risk areas can be identified and targeted measures derived, such as improved signage, adjustments to traffic flow or the creation of safe crossing zones.

A key advantage of the Spatial Use Collision Risk Model is its flexibility, as it can be adapted to various contexts, including urban environments, rural areas or special events. Implementing such models not only enhances safety but also improves quality of life by promoting harmonious coexistence in public spaces.

In the planning of nature conservation areas or recreational landscapes, the RKRM can help better manage interactions between humans and nature, thereby minimising both ecological and social risks.

Predict-Bird GmbH

– Four companies, one goal –

Predict‑Bird GmbH is a joint venture formed by four companies. Its product aims to predict the probability of fatal collisions of large birds with wind turbines using probabilistic modelling. Millions of telemetry datasets are used as training data to derive species‑specific behaviour in selected areas. The RKR model enables the integration of technological advances in remote sensing with objective movement data obtained through telemetry (GPS‑tagging of birds).

The model incorporates all factors currently considered relevant for collision risk according to the state of scientific knowledge, including:

  • 3D spatial use in relation to habitat
  • species‑specific avoidance behaviour
  • up‑to‑date breeding site information from expert field surveys
  • technical characteristics and dimensions of wind turbines

A red kite in its natural habitat.            Image source: AdobeStock | Mark Hunter

PredictBird GmbH
Dr. Thilo Liesenjohann & M.Sc. Anton Kohl
Schobüller Straße 36, 25813 Husum, Germany
Homepage: www.predictbird.de
E-Mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

USt.-Ident-Nr.: DE369473149 | Steuer-Nr.: 15 295 65365 | HR Amtsgericht Flensburg, HRB 17055 FL

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More informations, reports, reviews and a contact form can be found at www.predictbird.de