1. Poprawa odporności lasu i adaptacja do zmian klimatu

The threat of forests by various harmful microorganisms is growing due to changing climate conditions and spreading of non-native pathogens and pests.. Simultaneously the relevance of biological methods of monitoring and preventing forest degradation is increasing in the face of the chemical’s use restrictions. The main aim of the project is the development of an innovative device (electronic nose/ e-NOS), based on a matrix of broad-band electrochemical sensors and neural networks that would detect and analyse the odor-based signals e.g. pheromones of certain insect species. The examples of pathogens and pests addressed in the project include Dendrolimus Pini (L.) and Phytophthora oomycetes.
The developed system delivers comprehensive and complex information which allows to create a neural classifier (using artificial intelligence). The dedicated software was developed to perform the analysis of the data and create a database – library of signals, which will allow to detect the analytes sought in the field. For each application foreseen in the project (analysis of specific smells), dedicated sensory matrices were prepared.   

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.

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.

Cross-Forest está desarrollando una plataforma común de datos forestales abiertos y un modelo de datos transfronterizo (ontología) compartido entre Portugal y España, para la publicación de inventarios forestales, mapas y otras bases de datos forestales en formato Linked Open Data (LOD). Cross-Forest proporcionará un repositorio público (endpoint) de publicación de Datos Forestales según el modelo producido. El objetivo principal se centra en mantener la información forestal siempre disponible y actualizada para facilitar su explotación a todos los agentes implicados en la gestión e investigación forestal.

Se están desarrollando dos casos de uso:
CAMBRIC - orientado a simular la evolución de las masas forestales y la calidad de la madera en distintos escenarios de gestión forestal.
FRAME – enfocado a la predicción del comportamiento y propagación de los incendios forestales a través de información precisa sobre materiales combustibles, mapas forestales y modelos de propagación.

Se emplean recursos de computación de alto rendimiento (HPC) debido a la cantidad de datos generados y gestionados, y a la complejidad de los modelos.

Los resultados obtenidos hasta ahora demuestran la utilidad y versatilidad que proporciona la tecnología LOD, ya que permite a los usuarios acceder y gestionar libremente datos actualizados para desarrollar herramientas adaptadas a sus necesidades y propósitos. La publicación de datos como LOD permite a las Administraciones Públicas cumplir fácilmente con sus requisitos de transparencia y publicidad, optimizar recursos y llevar un control estadístico del uso de los datos públicos.

Cross-Forest is developing a common platform for open forest data, and a cross-border data model (ontology) shared between Portugal and Spain, for the publication of forest inventories, maps and other forest databases in Linked Open Data format (LOD). Cross-Forest will provide a public endpoint exposing Forest Data, according to the produced model. The main goal is focused on keeping forest information always available and updated, to make exploitation easier for all stakeholders involved in forest management and research.
Two use cases are being developed:
CAMBRIC - to estimate the evolution of forests and wood quality, under different management scenarios
FRAME - to predict forest fires behavior and spreading through precise information on combustible materials, forestry maps and propagation models.
High Performance Computing (HPC) resources are employed due to the amount of data generated and managed, and to the complexity of the models.
Results so far show the usefulness and versatility provided by LOD technology, as It allows users to freely access and manage updated data to develop tools adapted to their needs and purposes. Publishing data as LOD allows Public Administrations to easily fulfil their requirements of transparence and publicity, optimize resources and keep a statistic control of the use of public data.

SiWaWa 2.0 is a simple developed new forest growth simulation model for practitioner (Android-App). SiWaWa needs only the number of the stems [N], the basal area per hectare [G] of a certain stand to generate separated the stem distribution curve according to the DBH-classes. SiWaWa 2.0 supports the decision makers in two aspects: Silvicultural and forest planning. It supports the foresters in a better understanding of the state point and forest development

Free available Android-App, which could be used in the following fields:
1. Strategy: Goal dimension of the trees, cutting time
2. Care concept: Coordination of harvesting time, optimization of productivity
3. Measurements: Urgency and priority
4. Analysis: Starting point and forest development without interventions. Definition of intervention measures and simulation