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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 system consists of four components:

• remote sensing data - quick access to current and historical data, enabling the user to compare satellite images from different periods;
• complementary data - cadastral data and detailed forest inventory data from management plans (FMP);
• remote sensing data products - geometric layers resulting from the processing of satellite images, showing the condition and health status of vegetation and forests;
• geospatial analyses - juxtaposition of remote sensing data products with cadastral data and detailed forest inventory data, enabling to identify inconsistencies between the actual state of the forest and the state recorded in databases, as well as recent changes.

The entire solution is based on an intuitive map portal for users, which is used to generate various types of maps, including maps of forests and tree cover, forest changes, maps of forest types, maps of forest condition, maps of crown density, maps of aboveground forest biomass and the extent of stand damage due to windstorms, fires, floods and insect infestations. Users of the system have access to current and archival satellite images, and they can compare different types of maps with complementary data as well as upload their own data sets.

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.

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.

Agricultural residues such as straw, bank canes and trees pruning constitute a significant load of green waste in rural areas from both sides of the borders. Those wastes are poorly managed causing severe environmental impacts. At the same time local authorities use expensive fossil fuel for space heating of public buildings, and due to the current economic recession, very often the amount of heat generated cannot satisfy the real needs of the building users. The sustainable management of the green waste can offer a real solution in both of the above problems. There is available technology that can utilize agrowastes as fuel for space heating under the only condition that a reliable supply chain is established.

Scope of this project is to establish a supply chain for green wastes, combined with the relevant business model, which will secure its sustainability. The supply chain will be customized according to the wastes that are available from both sides of the border and the business model will be adapted to the specific local conditions. The supply chain will serve selected end users in each country, therefore its operability will be tested and possible problems and barriers will be resolved.

Forest Data Bank is a data warehouse collecting, processing and sharing information concerning forests of all ownership forms in Poland. It’s aims include also supporting scientific research, enabling analysis and forecasting of forest resources and promoting standards of collecting and processing of forest data.

Data Bank provides both descriptive and geo-referenced spatial data. Available data cover forest stand and statistical unit description, forecasting and additional information such as: forest protection, fire protection, nature conservation, environment monitoring, hydrology, climatology, geology, nature and forest regionalisation, forest functional areas, seed regionalisation and National Register of Boundaries.
Forest Data Bank could be accessed through web portal (which includes also reports, publications and maps) or mobile app (mBDL), which offers access to map resources and navigation. Main target group are foresters but it is also used for the purposes of spatial planning, science, public and international statistics, and tourism. It provides information not only at the central level, but also regional and local ones. Data Bank is covering about 95% of forests in Poland (one of the most comprehensive dataset comparing to other countries that own such systems) and there are more than 25 thou visitors on the BDL portal per month.
 

El objetivo del proyecto ChainWood es diseñar y desarrollar una infraestructura de software segura basada en tecnologías blockchain y de Internet de las cosas, ajustada a todas las cadenas de suministro de la madera, que permita a los distintos actores sacar el máximo partido a sus datos y gestionar el producto de una forma más eficiente en términos de coste, trazabilidad y sostenibilidad.
Las principales soluciones a problemas detectados son: Garantía en las transacciones, Información de confianza en tiempo real, Semiautomatización de la operación, Datos de calidad accesibles, Mejora de la competencia.
Recomendaciones: 

• Para los productores
  Información en tiempo real sobre el volumen y el estado del producto.
• Para la industria transformadora
  Acceso a una enorme fuente de datos sobre la materia prima que les permitirá optimizar sus procesos de suministro y agilizar la gestión de sus operaciones.
• Para las empresas de explotación
  Transparencia y garantía en las transacciones, sacando el máximo partido a la tecnología actual.
• Para las autoridades de control
  Reducción de costes en los procesos de auditoría y control, así como un conocimiento más preciso de las cadenas de suministro.
• Para las empresas logísticas 
  Información que les permitirá optimizar su flota y prestar servicios de manera más eficiente.
• Para las administraciones públicas
  Mayor facilidad de acceso a los datos sobre la madera permitiendo una gestión más ágil y eficiente de los procesos que supervisa.

The objective of the ChainWood project is to design and develop a secure software infrastructure based on blockchain and Internet of Things technologies, adjusted to all wood supply chains, allowing the different actors to make the most of their data and manage the product in a more efficient way in terms of cost, traceability and sustainability. The main solutions to problems detected are: transaction assurance, Real-time trusted information, Semi-automation of the operation, Accessible quality data, Improved competition.

Recommendations:

• For producers: Real-time information on the volume and status of the product.
• For the processing industry: Access to a huge source of raw material data that will allow them to optimize their supply processes and streamline the management of their operations.
•  For operating companies: Transparency and assurance in transactions, making the most of today's technology.
• For control authorities: Cost reduction in auditing and control processes, as well as a more precise knowledge of supply chains.
• For logistics companies: Information that will enable them to optimize their fleet and provide services more efficiently.
• For public administrations: Easier access to timber data, allowing a more agile and efficient management of the processes they supervise.

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.