Modellering, DSS, simulering, optimering

HeProMo is an IT-based tool to predict the costs of timber harvesting scenarios under different aspects such as harvester logging. It allows certain settings to reflect the real situations in the forest. It provides preliminary costing and sensitivity analysis. estimation of productivity and cost for wood harvesting operations (preliminary costing). Writing and controlling offers for wood harvesting operations. Estimation of variables and their importance (sensitivity analysis). Well suitable for application in teaching , eductaion and research to identify key contributing factors and assessmen of their influence on the results. The productivity model (HeProMO) predicts quickly and with a good accurancy the costs for concrete timber harvestin scenarios. It allows the identification of optimization possibilities. The application is quite easy to handle and gives a solid basis for good economic choices.

The aim of the project was to work out the complex method of defining selected forest stand descriptions as well as aboveground biomass and carbon sequestration, based on the use of remote sensing for the purposes of forest management planning.

Among main goals were:

• acquisition and processing of remote sensing, laboratory and field data,
• determining the amount of biomass and carbon in the forest based on radar data,
• development of methods for the inventory of selected stand descriptions, growing stock and biomass with the use of active remote sensing techniques,
• local correction of dendrometric volume equations based on terrestrial laser scanning data (TLS),
• development of the merchantable volume conversion factors into biomass and carbon.

Results of the project allow to: reduce time needed to carry out the work of the forest management, especially inventory of growing stock; obtain higher accuracy of the CO₂ balance, biomass and annual allowable cut calculations; determine growing stock for any forest area; reduce cost of field work in forest management.

Virtual forest 2.0 is a research and development project that has developed a digital application to enable the visualization of forest resources and spatial data in 3D. A virtual forest is software that can be utilized in participatory land use planning, advising forest owners, and taking into account the goals of user and interest groups in the areas.The virtual forest can be used to increase citizens' understanding of different forest management options and to illustrate the landscape effects of a forest plan. The virtual forest can be used to visualize the holdings of any forest owner, and the application is compatible with various information systems in the forest industry.The virtual forest 2.0 uses open QGIS geographic information system to generate changes in forest patterns or tree data, habitat data and terrain data in a virtual 3D-visualization.  The free downloadable Virtual Forest 2.0 application was released in October 2020.

The Center of Excellence for Forestry 4.0 is developing Industry 4.0 digitalization concepts for the forest and wood cluster. The driving force behind this approach is a closely cooperating working group of companies, research centers and the Forestry Education Center  North-Rhine Westphalia as a practical testbed.New, intelligent and decentrally acting machines, devices, services and people, will enable the cluster to optimize its complex value-added networks, develop new business models and meet current challenges from ecology, economy and climate change. Existing approaches address the complexity of structures and processes, and the conflicting demands on forest management only insufficiently. To "smartify" the forest and wood cluster, existing competencies from industry, science and administration must be bundled: The goal of KWH4.0 is to create a know-how base and infrastructures, and to implement forest and wood 4.0 components via innovative Smart Forest Labs. The Smart Forest Labs serve as experimental forestry laboratories in which developed components, systems and processes are tested, standardization advanced, concepts disseminated, and actors trained. Developed concepts and standards are continuously published as practical recommendations, a first version of the communication infrastructure S3I (Internet of Things application) has been established. In addition, there is an increasingly smart fleet: forestry machines have been upgraded to retrieve digital information (GPS position, fuel consumption, production data, etc.) and at the same time networked via alternative radio standards with machines in regions where mobile communication is not possible.

Taking into account the carbon issue in forest management is becoming more and more important in France, giving rise to research and development projects. The Climafor software responds to a challenge: to make carbon calculations easier to access and less time consuming. The data sources used (production tables, calculation coefficients) are now well known. Climafor integrates them into a single tool, which does not require any special training. The calculations are instantaneous and the results can be used directly in a forest carbon project. The calculations made by the software are based on production tables for each species and different coefficients from research. The software will be continuously improved by updating the different parameters and adding new tables. For the moment, it is being developed by the IDF (Institute of Forestry Development), the R&D branch of the CNPF.

A lack of forest site information in Styria created a need for a new approach to forest site classification and mapping, considering the changing climatic conditions, which will affect the classification of forest sites and the choice of tree species. Theoretical concepts for a new approach in "dynamic site classification" existed, but the implementation of an integrated site and forest classification in for the whole forest area in Styria has been a scientific challenge. In this project the forest site classification is based on a GIS-based geo-ecological stratification model. The database is based on a digital elevation model, a geological base map, digitally available site and climate data as well as empirical site parameters. A map of forest types is derived based on several thematic maps, including information about energy, water and nutrient balance. Those parameters are modeled on the basis of point and area related data, which are then combined into forest types with a uniform combination of factors. The model allows a stratification of the forest types on all sites based on digital geo-ecological parameters. In addition to the ecological facts, each forest type is characterized by a description of silvicultural guidelines containing information on the appropriate choice of tree species, potential hazards and adaptation methods. These guidelines also describe previous experiences with the tree species and their mixtures, and will provide recommendations for the future forest management with regard to climate change.

With two newly developed forwarder prototypes, five new and different modules were implemented and tested in the fields under varying production conditions within Europe. These modules are developed towards raising the productivity of the machine, improving the working conditions and lowering the ecological impact of the forwarding process. The modules contain a hydrostatic-mechanical transmission system (HVT, M1), a suspended cabin (M2), an energy regenerating and recuperating hydraulic crane (M3), a triple bogie axle for wet terrain, that can be used with or without tracks (M4) and a monitoring system to surveil and document the machine status to derive further information of production and environment (M5).

With the tests of prototype machines, the aims of development could be proven by the field tests, that were executed within the study. Especially the effect on the soils on sensitive areas, also without the use of bogie tracks, as it was tested on distributed bark beetle infested stands in Saxony, was one field of application where the advantages of tire-based working, longer bogie axle and high contact surface were positively assessed. With more experiences, the revelation of further advantages or limitations are expected.

Within the field tests, all modules of the “Triple Bogie Prototype” (M3, M4, M5) were assessed with a positive effect. For wetland (Saxony) or even peatland working conditions (Scotland, Lithuania), the triple bogie showed advantages in technical accessibility but also the lower environmental impact on sensitive areas. Without the use of tracks, especially under varying, partly sensitive soil conditions the system has advantages towards other systems as the machine was able to relocate itself on own axle for long distances and provide the protection effect. The protection of ditches while entering forest stands was a positive additional effect of the system that could be observed as it acts like a built- in bridge. Due to potential high load capacity of both base machines, also a high productivity was recorded that fit or exceeded literature findings. The crane system (M3) which has also a high positive influence on the fuel consumption could withstand a fuel consumption reduction effect on its own, at is was proven under laboratory conditions.

• With higher productivity, now due to higher driving speeds and in course of a lowered fuel consumption, the second, “HVT- Prototype” (M1, M2, M5) setup presented its advantages especially under longer hauling distances with high possible driving speeds. This machine can be especially be efficiently used in regions with low road densities.
• With the monitoring system (M5), the environmental impact and the machine behavior was actively observed and evaluated. As the here implemented iFOS system is freely configurable, it was successfully implemented in the project and could for instance be further introduced as modular environmental documentation system by forest enterprises or in public services. The separately developed data-based crane scale as stand-alone or industry 4.0 service, makes it possible to use the forwarding information in logistic applications like the energy wood supply in the wood chip logistic (Geiger et al. 2019).