We are looking to join or co-develop an ambitious consortium working on the next generation of adaptive forest management systems, with a perspective extending towards 2028–2030.
Our interest goes beyond producing static forest inventories or one-time remote-sensing maps. We aim to contribute to the development of a dynamic, multi-temporal forest digital twin in which UAV LiDAR, terrestrial/mobile LiDAR, photogrammetry, multispectral and thermal imagery, GNSS observations and Earth Observation data can be integrated to describe not only the current state of a forest, but also how it is changing over time.
A particularly interesting research direction for us is the transition from forest mapping to intervention-aware forest intelligence: detecting structural and ecological change, identifying vulnerable areas, monitoring regeneration and management interventions, and translating multi-source observations into spatially explicit information for adaptive management.
We can contribute expertise in UAV and mobile LiDAR acquisition, 3D point-cloud processing, photogrammetry, multispectral/thermal remote sensing, GNSS-based field data collection, GeoAI, machine learning, spatial analysis and digital-twin development.
We are especially interested in consortia combining remote sensing and AI with forestry science, ecology, climate resilience, silviculture, robotics, biodiversity monitoring and operational forest management.
Our preferred role is as a research and technology partner responsible for multi-sensor data acquisition and fusion, 3D/4D forest modelling, GeoAI-based change analysis, field validation and the development of reproducible decision-support workflows.
We would particularly welcome collaboration with partners able to provide long-term forest study sites, ecological and silvicultural expertise, satellite Earth Observation, forest management scenarios, robotic platforms or access to operational forest management environments.

Selçuk University is a well-established public research university in Türkiye with multidisciplinary research activities in geospatial technologies, engineering, environmental applications and applied sciences.
Our research activities focus on advanced geospatial data acquisition and analysis, including UAV LiDAR, mobile and terrestrial laser scanning, photogrammetry, GNSS/RTK positioning, multispectral and thermal remote sensing, GIS, artificial intelligence and 3D spatial modelling.
We have experience in developing workflows that connect field observations with UAV- and ground-based sensing, point-cloud analysis, machine learning and spatial decision-support environments. Current research interests increasingly focus on the integration of these technologies into digital twins, automated monitoring systems and GeoAI-based analysis frameworks for forestry, environmental monitoring and other complex outdoor environments.
Within FOREST PATHWAYS, we are interested in contributing both methodological research and field-scale validation, with particular emphasis on multi-platform sensor fusion, repeatable 3D/4D monitoring, quantitative change detection and the translation of high-resolution geospatial observations into actionable forest-management information.