Skip to content

Operational remote sensing for forestry management

Jointly organized with National Institute for Research and Development in Forestry “Marin Drăcea”

1. Earth Observation applied in forest hazards management

Session summary:

Detection and monitoring based on remotely sensed data and techniques have been used for a long time in assessing forest damage and disturbance, forest hazard and risk management. To estimate the impact of climate change on the forests and as a response to increasing hazards intensity, various new remote sensing tools have been developed to improve the traditional methods of risk estimation, modelling, monitoring of forests hazards, assessment of exposure, vulnerability and their effects on people, infrastructure, ecosystems and environment. at various spatio-temporal scales.

This session will focus on the role of remote sensing in preventing, estimating and mitigating the impact of fires, windthrows, insect attacks and plant disease on forests. The response aims also to integrate science of remote sensing into forest practice, risk administration and reduction, improve prevention and preparedness, and create resilience and adaptation against hazards.


  • Image processing and machine learning techniques to support hazard management
  • Exploitation of Big Earth Data and satellite time-series for hazard disturbance
  • Climate change impact of hazards on ecosystem services and cascade effects
  • Change detection and monitoring of hazards in forests and protected areas
  • Integration of satellite, airborne and field sensors for evaluation of post-disaster effects
  • Dynamic modelling of fire occurrence, behaviour, impacts and post-event recovery
  • Mapping of fuel models (types, load estimation, moisture and consumption)
  • Estimation of burned area, severity, fire emissions and ecological impact

2. Remote sensing solutions for a sustainable forest management

Session summary:

Remote sensing has become an important tool for assessing forest resources owing to the increasing interest in forestry research for developing feasible solutions for forestry practice. The development of new sensors and remote sensing tools that facilitate image processing and interpretation makes remote sensing a valuable tool for monitoring forest status and assessing changes in forest cover and land use.

This section aims to bridge the gap between forest science and practice by using remote sensing technologies and providing digital tools for improved forest monitoring, forest resource assessment and more effective decision-making. Special attention is given to on-demand and high-temporal resolution data obtained from active or passive sensors mounted on satellites or aerial platforms, as well as to the development of algorithms and models to automate the processes related to monitoring and managing forest resources. The integration of remote sensing active and passive sensors datasets offers excellent potential for numerous aspects of forest resource planning and management. In this regard, trend analysis studies focused on the time-series which address the fusion between optical and Synthetic Aperture Radar (SAR) datasets are encouraged. This session will allow researchers to exchange specific remote sensing-based solutions applied in forestry, which contribute to an efficient decision-making process and sustainable forest management. 


  • Forest resources assessment, modelling, and mapping
  • Detection and monitoring of climate change effects on forests
  • Operational remote sensing in forestry
  • Fusing optical and SAR data for filling time series gaps
  • Investigations on ecosystems dynamics

3. High-resolution three-dimensional remote sensing for forest ecology

Session summary:

Close-range remote sensing datasets and techniques offer scale-specific solutions for measuring and monitoring ecosystems at all scales, from the individual to the biome level. Intending to revolutionize structure, function, energy flow, water cycle and carbon and nutrient flow quantification, sensors and algorithm development advance increasingly support three-dimensional evaluation of the in-situ forest ecosystem in a non-invasive manner.

Ecological remote sensing needs to be supported by robust work tying theory to field-specific datasets to further develop and validate optimum applications required in forest management activities and policy-making processes.

Recent research highlights the major role LiDAR plays in understanding fundamental ecological aspects, further enabling new applications in characterizing forest ecosystems’ structure and dynamics through specific indices, applied biophysical parameters assessment methodologies, and alternative ecosystem services evaluation approaches.

This section aims to compile fresh concepts regarding the use of three-dimensional remote sensing as an extension to classic well-established approaches. Furthermore, the section is focused on promoting and discussing the most recently encountered practical challenges, concerns, innovations, and solutions laid down in the field of ecology by using remote sensing datasets. Research directly connecting close-range active sensors specific datasets with knowledge from various fields contributing to ecology is encouraged. Therefore, studies adding to the body of knowledge, applications, and capabilities by addressing data upscaling through the fusion of terrestrial and unmanned aircraft LiDAR or the use of other specific data, such as spectral information, will be given priority.


  • Multisource point cloud fusion
  • Ecosystem services valuation using close-range active remote sensing
  • LiDAR-based trees species classification
  • Complementing point clouds with spectral information for an enhanced forest status evaluation
  • Morphological traits using QSM
  • 3D analysis of anthropogenic landscape alteration