Geospatial solutions

The Blue Carbon Marketplace, developed for our client TransparenC, represents a significant stride in combating the climate crisis by leveraging the voluntary carbon market. This innovative platform is crucial as it facilitates the trading and management of carbon credits derived from blue carbon ecosystems, like mangroves, seagrasses, and salt marshes, which are vital in sequestering carbon dioxide, a major greenhouse gas. Additionally, the Blue Carbon Marketplace harnesses the power of geospatial data analytics, utilizing satellite imagery and other spatial data sources to accurately monitor and verify the carbon sequestration impact of each project.

Together with the Karlsruhe Institute of Technology, Technical University of Munich, and public organizations, we participate in a research project that aims to develop a monitoring, data management and information system based on artificial intelligence (AI) for the prediction of groundwater levels and salinization. Our task is to analyze the requirements and develop a prototype of a user-specific decision support system that is intended to provide early warning of groundwater low levels and salinization and the associated damage.

For Biodiversify we built and implemented a software as a service application to allow users to analyse the Biodiversity Net Gain (BNG) implications of potential development sites. Biodiversify's BNG screening tool estimates the likely BNG implications of development sites. The tool uses advanced geospatial analysis to calculate the potential impact of development sites in terms of the Natural England Biodiversity Metric using the best nationally available data.

We developed an intuitive self-service web application that integrates wind speed, flood hazard, and accessibility data to assess the most suitable locations for wind turbines by applying different criteria specified by the user. The tool provides a comprehensive map visualization and enables the user to see more details about the top 10 sites based on the selected criteria.

Together with the University of Potsdam, Technical University of Munich and KISTERS, we participate in a research program that aims at the development and integration of innovative digital tools for the management of risks from heavy rain events in cities. Based on a hydrological model, we predict the infrastructure damage caused by extreme precipitation events and create a web-based decision support system with target group-specific storylines and dynamic infographics for better risk communication.

FarmChamps uses a field vitality model to forecast harvest of crops for farmers and biofuel producers. We developed a web solution that empowers users to make informed decisions for day-to-day management of ground food production in order to understand the current crop status, plan more efficient harvests, and forecast likely yields.

Uncontrolled vegetation causes damages, delays and safety issues for railways. ENVU’s Smart Weeding System uses weed detection technology to perform precision spraying of herbicides only where weed is present. The approach reduces the amount of herbicides by up to 50 %. We helped ENVU develop and implement a digital platform for their customers to process the spraying data and to visualize and monitor the maintenance activities and results.

Lebenswald creates new habitats, protects endangered species and actively fights against climate change. The initiative Lebenswald is part of Borneo Orangutan Survival (BOS) that saves the acutely endangered orangutans in Borneo. Together we developed a map-focused, donation platform that engages with donors allowing them to select their region for planting.

We supported HereWeGrow with the implementation and execution of a large-scale training program. The goal was to improve coffee yield and quality to raise the household income of 50,000 coffee farmers in Ethiopia. We built and implemented a system for monitoring and evaluation of the training offering, attendance tracking, training module navigation with data collection, and farm visit surveys.

Working with EGLV, we instrumented the digitization of task-allocation to improve situational awareness, task dispatching and workforce management during flooding events. Management and workers alike are situationally aware in real time.

The Store Locator was developed to enhance the customer experience by making it easier for users to find retail locations that carry Black Buffalo products. Leveraging cutting-edge location services, we created a seamless solution that is fully integrated into the Black Buffalo website, offering an intuitive, responsive, and user-friendly interface. The solution features dynamic search filters, comprehensive store details, and interactive maps to ensure a smooth and efficient user experience. By driving more in-store traffic, the Store Locator supports Black Buffalo's mission to expand the availability of their premium products to a broader audience.

Together with Graz Linien and the EIT UM, we are working on the SmartDrive AI solution, a pioneering initiative aimed at enhancing road safety for Graz Linien drivers. This project focuses on real-time accident reporting, GPS-based location marking, and the integration of location data analysis to highlight high-risk areas, enabling drivers to prevent future accidents. Our role includes the digital transition of accident documentation and advanced data analysis, ultimately contributing to a safer urban environment.

Together with RAG, we are supporting safety and sustainability in the Ruhr region. Despite all prevention efforts, property damages caused by former mining activities are still common. We brought in new spatial data to augment the existing complex RAG mining and claims data. We trained and validated a spatio-temporal model for prediction of future claims. The prediction outputs are visualized and integrated as a service layer into existing RAG systems.

We developed an intuitive self-service web application that integrates wind speed, flood hazard, and accessibility data to assess the most suitable locations for wind turbines by applying different criteria specified by the user. The tool provides a comprehensive map visualization and enables the user to see more details about the top 10 sites based on the selected criteria.

We developed an intuitive self-service web application that integrates demographics, accessibility, and property data to compare existing, future, and competitor retail locations. The application provides a comprehensive KPI visualization and an AI-powered prediction of site suitability.

Uncontrolled vegetation causes damages, delays and safety issues for railways. ENVU’s Smart Weeding System uses weed detection technology to perform precision spraying of herbicides only where weed is present. The approach reduces the amount of herbicides by up to 50 %. We helped ENVU develop and implement a digital platform for their customers to process the spraying data and to visualize and monitor the maintenance activities and results.

We developed an automatic progress tracking solution for ThyssenKrupp’s large construction sites using imagery collected from drones. The award winning solution combines 3D geospatial datasets and artificial intelligence for smart, autonomous feature recognition and automated reporting.

Lebenswald creates new habitats, protects endangered species and actively fights against climate change. The initiative Lebenswald is part of Borneo Orangutan Survival (BOS) that saves the acutely endangered orangutans in Borneo. Together we developed a map-focused, donation platform that engages with donors allowing them to select their region for planting.

We supported HereWeGrow with the implementation and execution of a large-scale training program. The goal was to improve coffee yield and quality to raise the household income of 50,000 coffee farmers in Ethiopia. We built and implemented a system for monitoring and evaluation of the training offering, attendance tracking, training module navigation with data collection, and farm visit surveys.

Together with Graz Linien and the EIT UM, we are working on the SmartDrive AI solution, a pioneering initiative aimed at enhancing road safety for Graz Linien drivers. This project focuses on real-time accident reporting, GPS-based location marking, and the integration of location data analysis to highlight high-risk areas, enabling drivers to prevent future accidents. Our role includes the digital transition of accident documentation and advanced data analysis, ultimately contributing to a safer urban environment.

Together with the Karlsruhe Institute of Technology, Technical University of Munich, and public organizations, we participate in a research project that aims to develop a monitoring, data management and information system based on artificial intelligence (AI) for the prediction of groundwater levels and salinization. Our task is to analyze the requirements and develop a prototype of a user-specific decision support system that is intended to provide early warning of groundwater low levels and salinization and the associated damage.

Together with the University of Potsdam, Technical University of Munich and KISTERS, we participate in a research program that aims at the development and integration of innovative digital tools for the management of risks from heavy rain events in cities. Based on a hydrological model, we predict the infrastructure damage caused by extreme precipitation events and create a web-based decision support system with target group-specific storylines and dynamic infographics for better risk communication.