Call for Papers: Advanced methods and applications in Remote Sensing for Forestry and Agroforestry.
New methods of remote sensing have strongly influenced forest applications in the fields of conservation, monitoring and assessment of forest ecosystems.
From assessing forest ecosystem health, over protecting and preserving biodiversity, to monitoring single trees and entire forests – gaining accurate information on the status and distribution of forest structures over various time scales is vital.
The same is true for agroforestry applications. These human-made ecosystems combine trees producing marketable products with pasture or cropping systems. Agroforestry systems are of high cultural and biodiversity value and are often protected. In Europe, typical agroforestry systems are e.g. Dehesas in Spain and traditional orchard meadows in Germany.
Several technological and methodological developments are worth mentioning. Active and passive sensors provide high-resolution data that capture and reflect the three-dimensional forest structure in geometric and multispectral detail. Besides the conventional LiDAR and optical sensors, new instruments - operating with higher point density in extended radiometric ranges - are available as aerial, terrestrial and mobile tools, allowing for new approaches and applications. The miniaturization of sensors and platforms in combination with increased measurement speed opens up new application possibilities with a clear tendency towards drone-based ones. New deep learning methods outperform classic machine learning techniques and lead to new methodological approaches with a significant increase in accuracy.
In this special issue, we would like to offer an unique compilation of original papers focusing on advanced methods in the field of remote sensing for forestry and agroforestry. In particular, we want to highlight new methods, techniques and applications that take advantage of the new opportunities of high-resolutional fused data and advanced analysis methods.
Topics may include but are not limited to the following:
- New sensors (LiDAR, optical, hyperspectral, multispectral, SAR)
- New platforms (UAV) for forest applications
- Deep learning approaches for estimating forest structure attributes
- Multisensor, multitemporal, multiresolution data
- Data fusion approaches using multiple remote sensing data sources for forest monitoring
- Biodiversity in forests
- Monitoring of forest ecosystem
- Monitoring of agroforestry systems
- Advanced forest inventory
- Advanced single tree detection
- Advanced single tree metrics
All submitted manuscripts are subject to a peer-review according to the PFG-standards. The deadline for submitting papers is June 30, 2021.