Künstliche Intelligenz in der forstlichen Standortskartierung (KI-SOIL)

Forest soils play a key role in the sustainable management and development of forests. Their diverse functions are essential for the performance of the ecosystem. In view of the climate crisis and future challenges, regular updating of soil and site information is essential.
However, the collection of this data - for example through the nationwide soil condition survey in forests (BZE), forest site mapping or forest environmental monitoring - is time-consuming. In addition, determining the properties of soil in the field is often fraught with uncertainty.
This is where the KI-SOIL project comes in: The aim is to (partially) automate the recording and description of forest soil properties using innovative technical solutions. This should make forest environmental monitoring and site mapping more efficient and reliable.
The methods used to assess the condition of forest soils should serve as a decision support system. They reduce personnel and time expenditure and minimise uncertainties in the assessment of properties of soil in the field.

In order to close existing knowledge and technology gaps, KI-SOIL is focussing on the following development priorities:

- Procedures for the digitalisation and automation of the recording, analysis and evaluation of previously unmeasurable characteristics of the soil profile description,
- a systematic and sustainable digital documentation of uniformly classified and thus comparable soil condition information,
- a minimally invasive, effort-reducing sampling.

Main tasks of the HNEE in the project:

- Designation of sample profiles of forest soils
- Soil science support and creation of training data for the AI
- Carrying out case studies, demonstrations and tests in the field