ARGOS – How digital eagle eyes find brownfields

The availability of land is the most important factor when it comes to developing major new business locations. In reality, however, municipalities and companies wishing to locate here are struggling with an increasing shortage of land, especially in metropolitan areas. In addition, for reasons of sustainability, the net new sealing of commercial areas is to be reduced, so that in many cases new settlements can only be realized by reactivating commercial areas that are no longer used, so-called brownfields. These have further advantages: they are often already connected to local supply networks, have good infrastructure links and are easily accessible for employees.

But where are these brownfields located and how many do they actually have? And what legacy issues can be expected on site? While some municipalities have a detailed insight here, other regions up to federal states have only sporadic and decentralized information on this.

Nationwide identification of brownfields with AI

The ARGOS project aims to realize a nationwide, AI-supported extraction of brownfields from geodata, aerial and satellite images. The goal is to use this data to develop an online information platform on the topic of brownfields that will provide an up-to-date overview of potential site options for commercial real estate projects.

To this end, experts from the Fraunhofer IIS Supply Chain Services working group are training an artificial neural network to identify appropriate sites.

Potential brownfield sites can thus be made visible and new commercial real estate projects made possible, which is not only advantageous for economic reasons, but also for sustainable ones: After all, no new land needs to be sealed for new settlements and company expansions. A preliminary study has already examined the feasibility throughout Germany, and now concrete data is being collected and evaluated on an area-wide basis.

Brownfield platform makes analysis results available

After completion of the project in fall 2024, the results will be made available on an online information platform as a brownfield cadastre. This not only shows the location and size of the areas classified with a high probability as brownfields, but also enriches them as far as possible with further meta and geodata.