A Virtual Reality (VR) application is being developed to replicate digital twins of forest stands. These digital twins are integrated with a sophisticated mathematical model, allowing for a 3D representation of forest behaviour and evolution. Users can immerse themselves in a realistic forest environment from anywhere, make management decisions, and observe their long-term outcomes.  

The system enables users to perform common forestry activities, such as logging, thinning, and planting, within the VR environment. They can also accelerate simulations to view the forest's development over short or long periods and experience highly realistic tree species replicas.  

This tool empowers forest managers and foresters to accurately predict forest behaviour and the impact of their management decisions. It aids in selecting optimal management techniques for various situations, ensuring positive outcomes and saving time and resources. The system's scalability and user-friendliness make it accessible to a wide range of forest professionals, regardless of their technical expertise. 

DIGIMEDFOR developed a simple 2D spatial model as a predictive tool and a virtual environment to explore the long-term effects of different forest management strategies on Mediterranean tree species. 

It provides a simplified yet effective way to: 

1. Simulate forest growth and competition: the model allows users to visualize and analyse how individual trees interact and compete for resources over time. 
2. Evaluate management strategies: by simulating different management interventions (e.g., thinning, planting), users can assess their potential impacts on forest structure, composition, and yield. 
3. Understand natural processes: the model incorporates natural processes like death and regeneration, providing insights into the ecological dynamics of these forests. 
4. Support decision-making: the tool can help forest managers make informed decisions about harvesting, planting, and other silvicultural practices. 

The simulation can represent several commercially significant Mediterranean tree species randomly generated or derived from actual observed data from field surveys. 

An immersive 3D software presentation (VFDSS) enables users to explore, in real-time, the predicted impacts of various forest management strategies on realistically rendered trees. 

By providing a user-friendly and visually appealing interface, the model empowers a wide range of stakeholders to make data-driven decisions for the sustainable management of Mediterranean forests. The primary beneficiaries of this solution are forest managers and researchers who can use the tool to experiment with different management scenarios, predict the long-term consequences of their decisions, gain a deeper understanding of forest ecology. The model can inform forest policy development and conservation strategies and can assist private landowners in managing their forests sustainably. Lastly, this model can be used as a teaching tool to illustrate forest dynamics and management principles. 

Drones equipped with RGB and multispectral imaging systems collect high-resolution aerial data to monitor forest environments by estimating crucial micro-climate and stand structure attributes, such as soil moisture and tree species. Autonomous flight capabilities maximize forest coverage, allowing the drones to efficiently gather data from diverse areas (for further details see also Remote sensing of forest attributes from proximal to satellite platforms and Ground-based observation of biophysical forest attributes). To enhance image clarity and annotation quality, images are captured in the afternoon under favourable ambient lighting. These high-resolution images serve as valuable input for training predictive models, which rely on datasets with over 300 images to ensure robust performance. For soil moisture estimation, a custom model architecture processes spatial data, while a YOLO-based model (YOLO – You Only Look Once - models are real-time object detection systems that identify and classify objects in a single pass of the image) handles tree species identification across the entire image. Georeferencing, enabled by Real-Time Kinematic (RTK) technology, links detected trees with GPS coordinates at centimetre-level accuracy, ensuring precise location mapping. The model outputs include detailed data on soil moisture levels, GPS coordinates of the regions, and specific information on tree species, such as bounding boxes, species type, canopy diameter, and tree health status, such as whether the tree is alive or dead. This comprehensive approach facilitates accurate, efficient, and large-scale monitoring of forest health and characteristics.

The DIGIMEDFOR Knowledge Platform is an open-source web application developed to support decision-making for Mediterranean forestry stakeholders, including both private and public entities. This platform acts as an intelligent assistant, providing recommendations based on a backend that integrates various forestry management methodologies, silvicultural practices, regulations, and other relevant data. Users can explore various forestry scenarios and receive expert guidance without the need for a login. 

The platform is divided into two main components: the "Forest Pathway" and the "Partner Repository." The Forest Pathway is a search tool that enables users to plan forestry itineraries by selecting species, bioclimatic zones, forest site quality, and desired management outcomes. It aims to offer general guidance rather than processing specific inventory data. The Partner Repository is hosted on Zenodo and serves as a secure data repository for all project-generated outputs, ensuring long-term accessibility and storage of project information. This repository allows project partners to upload and manage data with restricted access options, supporting future data use and collaboration. 

The DIGIMEDFOR Knowledge Platform provides a valuable resource for forestry planning and management, enabling evidence-based decision-making and facilitating the sharing of knowledge across the Mediterranean forestry sector.

Using available digital information on ecosystem services allows us to quantify the contributions of PEFC-certified forests under the Sustainable Forest Management System. Access to this information will be provided through the register of PEFC-certified forest areas in Catalonia. Each management unit will be linked to specific Forest Ecosystem Services (ESS) and their indicators, provided by the Catalan Forestry Laboratory. 

By digitizing these ESS, we improve information accessibility and availability, providing forest owners and stakeholders with a comprehensive view of ESS in certified forests. 

For public authorities and forest managers, the digitized ESS system improves forest resource management, providing insights into the positive impact of forest management and facilitating compliance with environmental regulations. For private forest owners, managers, and other companies involved in forest management, the digitization process increases transparency in forest activities, enhances productivity by optimizing resource use, and adds value to the intangible services provided. 

Certification bodies can utilize the standardized data to improve the traceability and accountability of certified forests. 

The guidelines for digitalization help practitioners navigate the forest certification process and understand how to digitalize ecosystem services. They provide clear directions on the type of data and work required to create a digital platform for ecosystem services.

The Picture-based Tracking System is a computer-based solution designed to monitor and control the volumes of timber transported from logging sites to sawmills. Leveraging artificial intelligence, the system utilizes trained models built from a comprehensive, continuously updated image database. The system captures rear-view images of trucks loaded with logs. These images are automatically added to the database, which constantly evolves and improves. Trained AI models analyse the images to estimate timber volumes. 

The benefits of this tracking system are: 

The Data Traceability Platform System is a comprehensive cloud and blockchain-based service designed to support forestry operations by improving data traceability. It seamlessly integrates digital tools into existing workflows, ensuring accuracy, reliability, and compliance with regulatory standards, from tree marking to mill processing. 

The system caters to forest managers, private forest owners, forest operators, wood processing companies, forestry and environmental management professionals, and forestry and land management experts. These users can enhance the value and exploit the traceability and quality levels of their timber production by utilizing this digital tool for collecting traceability and quality information. 

The system enables tracking of volume variations within each forest unit, known as a "Traceability Box." When installed on drones used for forest surveys (LiDAR, aerophotogrammetry, etc.), the box records and securely transmits flight data to the platform using cryptography. 

Additionally, managers and operators can register relevant traceability information for the following elements on the platform: 

The in-situ wood evaluation aims to bring timber quality assessment earlier in the supply chain, directly to standing trees in the forest and to felled logs shortly after harvest. 

This in-situ evaluation helps forest owners understand the value of their properties by assessing the quality of their standing trees. Unlike traditional methods, our approach offers quick and easy evaluations using portable instruments or smartphones, saving time and effort while providing valuable information. 

From a forest management perspective, understanding the impact of various factors on both growth and wood quality can help decision-makers make informed choices about interventions. Focusing on wood quality in silvicultural planning improves wood resource management and conservation, creating value beyond simple extraction. 

Both forest owners and users benefit from insights into the quality of forest compartments, leading to more efficient buying and selling. Similarly, by using data collected at the felling site, harvesting companies can optimize log sales by segregating logs into batches of different value and identifying the best market destinations for each material. This targeted approach, rather than selling entire batches indiscriminately, increases profitability and ensures optimal utilization of harvested resources. 

The entire supply chain benefits as timber manufacturing companies gain better insight into raw material availability, enabling more effective production planning.

The TRESTIMA app provides a powerful and efficient solution for forest data collection and analysis. Already trusted by hundreds of Nordic forestry professionals, TRESTIMA offers a solid foundation for the Mediterranean forestry sector as well. 

The system comprises two key components: a cloud-based web service, accessible through www.trestima.com, allowing for data management and analysis; a mobile application, available for Android devices, facilitating data collection directly in the field. 

To optimize TRESTIMA for the challenges of the Mediterranean region, DIGIMEDFOR has implemented key enhancements: 

DIGIMEDFOR's quadruped robot is designed to navigate challenging Mediterranean forest terrain. Its semi-autonomous navigation allows it to traverse rough paths, avoid obstacles, and follow predefined routes marked by small metal signs. 

Equipped with a 16kg payload capacity, the robot can carry essential sensors like LiDAR, HD cameras, and multispectral cameras, powered by a high-capacity battery or external power bank, enabling 24/7 operation within the forest. Connectivity is ensured through Wi-Fi, 4G, or Starlink satellite, enabling data transmission to the cloud for processing and analysis. 

A Real-Time Kinematic Global Navigation Satellite System (GNSS) system is crucial for accurate geolocation, and the integration of Internet of Things (IoT) devices further enhances data collection. The collected data is stored in a PostgreSQL database for future analysis.  PostgreSQL database is a reliable and efficient system widely used to store and manage large amounts of data that can be searched using simple language (SQL) or more complex formats (JSON). 

The use of these devices is highly recommended despite the initial cost. This investment can significantly improve data quality and reduce the need for post-processing data cleaning. 

These devices, powered by low-power technologies like Wi-Fi or LoRa (a Long Range wireless platform of IoT), can continuously monitor environmental parameters such as temperature, humidity, and soil moisture. Careful consideration must be given to the placement of these devices to maximize data relevance.

DIGIMEDFOR proposes a drone for forests surveillance, designed for complex, remote environments. It has a dual imaging system with multispectral and high-resolution RGB cameras. The multispectral cameras capture data in green, red, red-edge, and near-infrared bands, enabling the calculation of indices, such as Normalized Difference Vegetation Index, which are useful for identifying stressed or declining vegetation over time. The high-resolution (20 Megapixel) RGB camera captures high-quality, colour-accurate images suitable for identifying tree species, assessing forest structure, and detecting illegal logging activities. Together, these imaging tools offer a comprehensive view of forest conditions and support tasks like biodiversity mapping and habitat assessment. 

The drone's Real-Time Kinematic (RTK) positioning system provides centimetre-level accuracy for precise monitoring and mapping. Its microsecond-level synchronization ensures accurate geotagging for consistent, high-quality data. With a 43-minute flight time and fast charging, the drone can cover up to 200 hectares in a single mission, enabling continuous operation and around-the-clock surveillance. The O3 transmission system offers stable, long-range data transmission (up to 15 km) for real-time analysis and decision-making. The omnidirectional obstacle sensing system and terrain-following feature ensure safe operation in challenging forest environments. The Simultaneous Localization and Mapping (SLAM)-like navigation system supports efficient, autonomous navigation, enabling optimized path planning and precise data collection. 

Forest management plans (FMPs) play a crucial role in promoting sustainable forest practices in Mediterranean Europe, whether for public or private forests. Due to the diverse requirements of land governments and forest managers across European and extra-European countries, the data source approach, the content and the quality of these FMPs often differ. This variability can lead to challenges in standardising and digitalising forests’ inventory data.  

The DIGIMEDFOR project has developed a standard format for the digitalisation of forests data to create a European database of digital inventory of forests that includes a set of attributes helpful for the manager authorities, policy and decision-makers, and wood industry sectors. The digitalisation and integration of maps and the inventory of forests attributes represent the best strategies to meet the monitoring and reporting requirements on harvested wood volumes, carbon stock, sink and emissions, and more in general, on fluxes of forests’ ecosystem services, in agreement with the monitoring framework for resilient European forests.  

Digital forests inventory provides significant advantages beyond ensuring the economic viability of the local forests’ enterprise and the sustainable use of forests resources but also opens a world of other tangible and intangible benefits. It facilitates both the use of open data and the transfer of information between operators along the forest supply chain, improving monitoring of wood resources, operational efficiency and the competitiveness of the forest sector. 

This digital revolution in forest management promises a brighter, more sustainable future for European forests, aligning with broader environmental and economic goals.