Improving the Data Basis for the Prioritization of Peatland Conservation Measures in Private and Corporate Forests (DaKliMoPuk)
The research and development project DaKliMoPuk aims to develop efficient methods to provide a solid data foundation for the targeted potential assessment and prioritization of peatland restoration projects in private and corporate forests. The project combines the evaluation of publicly available data with the automated application of established and newly developed remote sensing methods, calibrated through several test areas.
Background and motivation
Peatland conservation and restoration in private and corporate forests have played a minimal role in climate protection so far due to inconsistent or largely missing data. In addition, consent from forest owners is often required to estimate savings potential and opportunities for these areas. Without such data, landowners cannot be informed or, if desired, advised effectively about the benefits of peatland and climate protection. The project focuses on compiling and capturing site and forest inventory data from private and corporate forests on peatland sites efficiently.
Objectives
Given that cartographic sources are scattered and inconsistent, the project seeks to consolidate them and enrich them with forest stock types and spatial criteria. Innovative methods are needed to collect data in a way that is both detailed and efficient for this specific application. The improved data situation, respecting the interests of landowners, aims to:
- Assess greenhouse gas (GHG) savings potential through active climate protection in peatland forests.
- Identify implementation potential and priorities for forest areas on peat soils.
- Inform and motivate forest owners to engage in peatland conservation.
- Provide a basis for local surveys, feasibility studies, and restoration planning with the consent of forest owners, along with expert advice from agricultural and forestry authorities
Approach
In addition to reviewing, compiling, and presenting currently available data, automated remote sensing methods will be developed and their advantages, disadvantages, and limitations demonstrated. The project will test the plausibility and accuracy of these automated data collection methods in various natural environments and peatland types. This testing will involve multiple private peatland forests in Bavaria, for which owner consent has been obtained, as well as a peatland site managed by the Bavarian State Forests.
