In Portugal, increasing wildfire frequency and severe storm events have intensified the need for advanced monitoring tools to assess forest damage and recovery efficiently. This study explores the application of deep learning neural network technique...
Unmanned Aerial Vehicles (UAVs, also known as drones) have become increasingly appealing with various applications and services over the past years. Drone-based remote sensing has shown its unique advantages in collecting ground-truth and real-time d...
Data gathered through community-based forest monitoring (CBFM) programs may be as accurate as those gathered by professional scientists, but acquired at a much lower cost and capable of providing more detailed data about the occurrence, extent and dr...
Background: The forestry industry plays an important role in the economy and environmental sustainability, facing significant logistical challenges such as the geographical dispersion of plantations, the variability of raw materials, and high transpo...
Accurate, scalable forestry insights are critical for implementing carbon credit-based reforestation initiatives and data-driven ecosystem management. However, existing forest quantification methods face significant challenges: hand measurement is la...
Drone area coverage primarily involves using unmanned aerial vehicles (UAVs) for extensive monitoring, surveying, communication, and other tasks over specific regions. The significance and value of this technology are multifaceted. Firstly, UAVs can...
In the context of green transition and digital transformation, forestry is becoming a strategic area of application of current modern technologies. The Internet of Things (IoT), artificial intelligence (AI), big data analysis (Big Data) and Digital T...
Currently, the use of Unmanned Aerial Vehicles (UAVs) in natural and complex environments has been increasing, because they are appropriate and affordable solutions to support different tasks such as rescue, forestry, and agriculture by collecting an...
There is no doubt that unmanned aerial systems (UAS) will play an increasing role in Earth observation in the near future. The field of application is very broad and includes aspects of environmental monitoring, security, humanitarian aid, or enginee...
In recent years, technological advances have led to the increasing use of unmanned aerial vehicles (UAVs) for forestry applications. One emerging field for drone application is forest health monitoring (FHM). Common approaches for FHM involve small-s...
Climate change significantly intensifies agroforestry workers’ exposure to atmospheric particulate matter (PM), raising occupational health concerns. This review, based on the analysis of 174 technical and scientific sources including articles,...
Geospatial sensing and data-driven technologies (GSDDTs) are playing an increasingly important role in transforming (agro)forestry practices across the Western Balkans 6 region (WB6). This review critically examines the current state of GSDDT applica...
The current COVID-19 global pandemic has amplified the pressure on the agriculture sector, inciting the need for sustainable agriculture more than ever. Thus, in this review, a sustainable perspective of the use of remotely piloted aircraft (RPA) or...
The classification and identification of individual tree species in forest environments are critical for biodiversity conservation, sustainable forestry management, and ecological monitoring. Recent advances in drone technology and artificial intelli...
Pine wilt disease (PWD) is a forest disease characterized by rapid spread and extremely high lethality, posing a serious threat to the ecological security of China’s forests and causing significant economic losses in forestry. Given the extensi...
The responsibility for risk assessment and user safety in forested and recreational areas lies with the property owner. This study shows that unmanned aerial vehicles (UAVs), combined with remote sensing and GIS analysis, effectively support the iden...
Effective detection techniques are important for wildlife monitoring and conservation applications and are especially helpful for species that live in complex environments, such as arboreal animals like koalas (Phascolarctos cinereus). The implementa...
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentat...
Urban afforestation is increasingly regarded as a key strategy for fostering biodiversity to restore and enhance the ecosystem services needed to counteract the effects of climate change in built-up areas. In Italy, several experimental afforestation...
The diameter distribution of savanna tree populations is a valuable indicator of savanna health because changes in the number and size of trees can signal a shift from savanna to grassland or forest. Savanna diameter distributions have traditionally...