Know What’s Under Ground and Make Smarter Planning Decisions

Tanpere, Finland

A Finnish experimentation project developed a framework for classifying ground conditions for building and infrastructure construction. It will help anticipate the future cost of foundation laying during the early stages of city planning.

The ground conditions of an area can have a substantial effect on the costs and the environmental impacts of constructing buildings and infrastructure. At early stage, urban designers don’t typically have enough data to make smart decisions about zoning in that respect as obtaining that data is time-consuming and hence also costly.

Consequently, an experimentation project called MAKU-digi: Making the costs of land use visible devised a method for automating the analysis of ground conditions. I had the pleasure of interviewing Juha Liukas, Lead Advisor at Sitowise, and Hilkka Kallio, Geologist at Geological Survey of Finland (GTK), about the project.

Hilkka Kallio, GTK
Hilkka Kallio
Juha Liukas, Sitowise
Juha Liukas

Brewing the Idea

“While we were developing the Citycad software back in the 1990s, we had this idea of combing a ground conditions map with a town plan for analyzing constructability,” says Liukas. “One of our clients was the city of Espoo, which had just mapped out the city’s ground conditions.”

However, turning this idea into a method and a practical tool did not materialize until much later. In early 2017, Sitowise, Geological Survey of Finland, and six other organizations started an experiment as part of the national KIRA-digi digitalization program. The project was called MAKU-digi.

Espoo had meticulously kept its ground conditions data up to date and was invited to take part in the project. Other large cities—Helsinki, Vantaa, and Tampere— soon followed suite, together with the Finnish Transport Agency. They provided the project with five pilot case studies.

The Sources of Ground Conditions Data

As ground conditions data is not readily available in every part of the country, cities use local geotechnical investigations to augment data from national sources. 

“At GTK, we carried out a 35-year mapping project of superficial deposits, which created geographic data as polygons,” says Kallio. “This gives an overview of soil across the country, 1-meter deep. I think, in the beginning, soil mapping was mainly meant to serve agriculture and forest planning. Today our soil maps are widely used by land use planners”

Ground-penetrating radars, satellite imagery, and drone surveys offer additional data that geological experts can use to estimate ground conditions. However, Kallio emphasizes that geophysics does not offer alone accurate enough information for construction purposes. She would rather rely on geotechnical investigations as primary data.

Ground analysis

Automating Geotechnical Analysis

A two-by-two kilometer area can involve up to 10,000 individual geotechnical investigations. Analyzing that amount of data manually is impractical. Thus during the project, GTK devised and tested a system that automatically identifies certain beds and strata in the ground.

The other main output of MAKU-digi was a system for using geotechnical investigations, soil maps, and digital elevation models to classify any geographical location on a standardized scale. The “soil construction capacity class” of the location, combined with the location’s zoning elements, determines the foundation type. It, in turn, has a unit price that when multiplied with the building area gives an estimate of the foundation costs. The results can be presented visually on a map.

“In MAKU-digi, we dealt with the relative rather than absolute costs of foundation construction. There are other projects, like the national IHKU Alliance, that will provide a cost management system for infrastructure construction,” Liukas points out. “I envision a future where you can upload a draft detail plan to an online service and see the updated foundation costs at once, even as you make changes to the design.”

ground conditions classification

Harmonizing Urban Design Data

“The Ministry of the Environment saw our results and came to the conclusion that our harmonized classification model could become a JHS recommendation,” says Kallio. The so-called JHS recommendations provide national information management guidelines for both governmental and municipal administrations.

Another project called Municipality Pilot is formulating a process and information model for digital detail planning. It has tested combining a detail planning model with the MAKU-digi analysis in three municipalities.

“I don’t know of any examples from other countries where a ground condition method and classification is standardized at the national level. So in that sense, we are doing pioneering work here in Finland,” Kallio concludes.

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