Partners

The partners are a strong team of companies, public and university partners with compentences in both R&D and public administration and commercialisation. Have a closer look here.

The section of Soil Physics and Hydropedology at the Department of Agroecology (AGRO) at Aarhus University research in soil physical, chemical, and hydrological processes. The aim is to gain a quantitative insight into the spatial distribution of soil properties on a local, regional, and national scale. The section will contribute with an integrated research effort, which will result in detailed mapping of peat areas.

 

The Department of Agroecology has a GIS team, which is responsible for field data and soil maps on a national level. The team along with the Soil Physics and and Hydropedology is responsible for policy support in relation to all soil-related inquiries. In addition, the team is leading within mapping soil, just as digital mapping using AI techniques is a top competence. The Department of Agroecology was responsible for carrying out the latest mapping of peat soils in Denmark, and are now hosting these data.

I•GIS is a small, specialized GIS and geoscience software and service provider, with an international client base. They are heavily engaged in R&D, both nationally and internationally. Their observations on market, customers, competitors, and technology indicate the existence of a lucrative market to be exploited by the developments in ReDoCO2.

I•GIS will utilize their participation in this project to continue building state-of-the-art applications for 3D geological modelling founded in research and end-user workflows. This project allows their suit of modelling and data management solution to be expanded to include modelling and decision support tools in the special case of peat mapping. However, many of the new features to be developed are believed to be general and applicable in other use-cases, and will hopefully be positive assets to already existing and future customers.

SkyTEM is an airborne geophysical company with 50+ employees and worldwide operations. Over  more than a decade, the company has applied its strategic competencies to identifying business  opportunities, developing novel technologies within its field of application and introducing new prod ucts commercially successful to the airborne EM market. In the context of this project, we have  identified a new business opportunity, entailing that the company’s broad R&D competencies are  leveraged to develop a high-resolution TEM sensor (SkyTEMPico) mountable on a UAV. SkyTEMs  project exit strategy is to extend the business foundation with a new business unit that produces  and sells combined SkyTEMPico system and service solutions.

Region Midtjylland covers 19 municipalities. It is the authority of soil pollution and raw material planning and administration, and coordinates furthermore regional development within e.g. climate adaptation / mitigation, rural development, circular economy and sustainability. RM works mostly in partnerships with municipalities, utilities, knowledge institutions etc. to find innovative and sustainable solutions on societal challenges. Coast to Coast Climate Challenge is an example for a climate adaptation project where RM, as the secretariat for the project, works together with 31 partners to create a resilient region towards the changes in the climate. In all projects the region promotes added value and multifunctionality, as part of taking care of all interests and challenges in the whole project area. Recently, RM is initiating a complementary project on Multifunctional Land Consolidation incl. a decision support tool, because many of our societal challenges can be solved by conversation of agricultural land into ecosystems which are currently under pressure. RM contributes to ReDoCO2 especially by securing the applicability of the data and makes sure the project is  meeting the needs of end users.

The computer vision research lab at AAU has conducted research within computer vision and ma chine learning for 20+ years. The lab contributes scientifically and practically to the project within all  tasks related to data integration and machine learning. The lab expects to advance their general  competences of applying data science in relation to soil science, and in particular applying deep  learning algorithms to diverse data types.

Funded by

The danish Innvationsfonden invests in entrepreneurs, researchers and businesses that create value for Denmark and new solutions to our society’s biggest challenges.