Depending on their present condition, peatlands can store a huge amount of carbon (C) or be a source of carbon dioxide (CO2), which is a crucial challenge globally. In Denmark, peatlands constitute a key target to achieve the national goal of reducing CO2 emissions with 70% by 2030. There is thus a great need to investigate the spatial variability of peat soil properties in order to assess the total amount of C stored in these soils.  

Through the combination of state of-the-art hardware, software, modelling techniques and IT technologies the present project will develop an overall methodology to map peatlands in detail and enable accurate estimates of CO2 emissions and potential C stocks. This methodology will provide decision-makers with detailed information and cost-effective tools to appropriately select which peatland areas to take out of agricultural production and restore. Notably, the combination of the drone-mounted cutting-edge geophysical sensors, advanced 2D modelling techniques and 3D software will be a game changer for peatland mapping both nationally and worldwide.  

In an ambitious two-year project, Stanford University partners with leading Danish companies and three water agencies in California to develop a template for an optimal workflow that would use airborne electromagnetic (AEM) data as the foundation for the development of hydrogeological conceptual models. This provides a key step in the implementation of the Sustainable Groundwater Management Act (SGMA) in California and will provide value to groundwater architecture mapping worldwide. The workflow includes not only the deployment of the AEM technology to acquire vast amounts of AEM data, but more importantly designing the supporting geophysical and computational infrastructure for data analysis, interpretation, and archiving. Significant advancements can be made by studying ways in which California can develop and implement a workflow and build on Danish experience.

Groundwater mapping in Denmark is internationally acknowledged and regarded as a benchmark approach. Huge amounts of data (well logs, geophysical, geo- and hydro-logical data) have been collected. Today these data are combined in a deterministic sequential workflow, where, typically, a single final model represents all available information. While successful, this workflow has some limitations: There is no way to ensure the final model consistency with all information at hand, and there is no way to ensure correct uncertainty quantification. To remedy this, we propose to develop a probabilistic data integration workflow that allows consistent integration of well-log, geophysical and geological data. The results will be a probabilistic geological model that: a) will be consistent with all data, and b) allow detailed uncertainty analysis. The resulting probabilistic geo-model can be efficiently used by the end-users for informed, data-driven, decision- making and for risk assessment.

Based on the increasing urbanization, building activity, contamination, and drainage of climate change induced heavy precipitation, a need for knowledge about the urban subsurface in modern cities is  grow

ing fast. To obtain this knowledge, a massive amount of geotechnical data, and tools to obtain, visualize and interpret on these data are required. This project attack these challenges, and aim to develop integrated tools enabling non-geoscience experts to both generate and and utilize urban geothechnical information.

This project intend to develop a foundation for geological modeling in cities. By developing tools and workflows for urban geological modeling the hope is to enable the cities to utilize the geological potential with respect to more sustainability concerning water supply, climate adaption, and heat storage. To achieve this, the project has two main scientific goals: 

1. Improve management, design, and construction of urban subsurface infrastructure through new methods of urban geological mapping by activating and including non-digitized geological archive data. 
2. Enable High Definition 3D visualization allowing easier and better utilization of the geological information and the different geodata.  

The Project is partly financed by the Danish Eco-Innovation Program (MUDP) and is a 2 year project running from January 2016 including GEO, University of Copenhagen, Frederiksberg Forsyning and I•GIS

For more information contact us at consultancy@geoscene3d.com  

 

The goal of this project is to develop a user-friendly expert