Forest Inventory, Modeling and Remote Sensing
A section of Forests (ISSN 1999-4907).
Section Information
This section highlights progress in the mensuration, modelling and monitoring of forests around the world. The total woody volume and stem volume of a tree, aboveground biomass and basal area are key forest inventory attributes that are required by forest managers. Reliable mapping of volumes and biomass facilitates the implementation of sustainable management strategies and practices. We encourage applications tackling issues of integrating ground and satellite data for the calibration and validation of remote sensing-based forest observations.
Contributions dealing with various types of sensors (active and passive) and carriers (terrestrial, airborne, unmanned aerial vehicles, space-borne) or combinations thereof are welcome. We solicit contributions describing innovative remote sensing-based approaches, data processing techniques and modelling tools, to improve understanding forest structure and composition supporting operational applications. We invite researchers to contribute original research articles as well as review articles. Potential topic areas include, but are not necessarily limited to:
- Multispectral (e.g., Sentinel-2, Landsat-8 OLI) and hyperspectral (e.g., PRISMA) data processing for forest monitoring;
- LiDAR processing in vegetation characterization and mensuration;
- New LiDAR metrics at stand and individual tree levels apart from height metrics (e.g., height heterogeneity, canopy gaps and LAI profiles) to predict canopy characteristics (i.e., wood volume, stem volume, aboveground biomass and basal area, among others) across a wide range of canopy structures;
- Methods for multi-source data fusion and integration for forest modelling, mensuration and inventory area (e.g., integration of satellite, aerial/drone and in situ observations);
- Analysis of forest conditions at multiple spatial and temporal scales and geostatistical analysis;
- Development of novel statistical or functional approaches for quantifying forest conditions;
- Forest monitoring and evolution simulation;
- Recent developments in artificial intelligence (AI) for forest modelling;
- Models combining field sample plots from National Forest Inventories with satellite and/or LiDAR data;
- Identification of forest areas at risk.
Editorial Board
Topical Advisory Panel
Special Issues
Following special issues within this section are currently open for submissions:
- Applications of Artificial Intelligence in Forestry (Deadline: 15 December 2023)
- Impacts of Climate Change on Forest by Using Growth Modeling (Deadline: 20 December 2023)
- Detection and Mitigation of Forest Degradation and Fragmentation (Deadline: 31 December 2023)
- Forest 4.0: Advancements and Challenges in Digital Technologies for Sustainable Forest Management (Deadline: 9 January 2024)
- GIS and Satellite Image Technology in Forest and Urban Forest Detection and Monitoring (Deadline: 10 January 2024)
- Spatio-Temporal Monitoring of Forest Fires and Vegetation (Deadline: 23 January 2024)
- Forest Growth Modeling in Different Ecological Conditions (Deadline: 25 January 2024)
- Advances in Forest Growth and Site Productivity Modeling—Series II (Deadline: 31 January 2024)
- Forest Characterization Assisted by Remote Sensing Technologies (Deadline: 31 January 2024)
- Remote Sensing Application for Mapping and Monitoring Forest Ecosystems (Deadline: 31 January 2024)
- Applications of Laser Scanning and Satellite Images in Forest Mensuration—Series II (Deadline: 31 January 2024)
- Forest Structure Monitoring Based on Remote Sensing (Deadline: 29 February 2024)
- Panoptic Segmentation of Tree Scenes from Mobile LiDAR Data (Deadline: 29 February 2024)
- Remote Sensing of Forest Land-Cover Change and Microclimate Conditions (Deadline: 29 February 2024)
- Computer Application and Deep Learning in Forestry (Deadline: 11 March 2024)
- Advances in Remote Sensing for Forestry: Theory, Methods, Applications, and Validation (Deadline: 21 March 2024)
- Application of Active and Passive Remote Sensors in the Forest Inventory (Deadline: 25 March 2024)
- Application of Remote Sensing Technology in Forest Fires (Deadline: 25 March 2024)
- Application of Close-Range Sensing in Forestry (Deadline: 25 March 2024)
- Machine Learning and Big Data Analytics in Forestry (Deadline: 31 March 2024)
- Application of Remote Sensing in Vegetation Dynamic and Ecology (Deadline: 31 March 2024)
- Machine Learning Techniques in Forest Mapping and Vegetation Analysis (Deadline: 15 April 2024)
- Monitoring Forest Change Dynamic with Remote Sensing (Deadline: 30 April 2024)
- Remote Sensing of Forest Biomass and Carbon Dynamics Using Multiple Sources and Technologies (Deadline: 20 May 2024)
- Image Processing for Forest Characterization (Deadline: 30 May 2024)
- Modeling Forest Response to Climate Change (Deadline: 31 May 2024)
- Forest Inventory Monitoring Based on Remote Sensing (Deadline: 31 May 2024)
- Imaging Sensors for Monitoring Forest Dynamics (Deadline: 31 May 2024)
- Application of Laser Scanning Technology in Forestry (Deadline: 31 May 2024)
- Prognosis of Forest Production Using Machine Learning Techniques (Deadline: 1 June 2024)
- Modeling Aboveground Forest Biomass: New Developments (Deadline: 30 June 2024)
- UAV Application in Forestry (Deadline: 30 June 2024)
- Airborne and Terrestrial Laser Scanning in Forests (Deadline: 30 June 2024)
- Innovations in Forest Fire Detection and Monitoring: Integrating GISs, Remote Sensing, and AI (Deadline: 30 June 2024)
- New Tools for Forest Science (Deadline: 30 July 2024)
- Modeling and Remote Sensing of Forests Ecosystem (Deadline: 31 July 2024)
- Study of Forest Landscape Development Based on Geospatial Technologies (Deadline: 31 July 2024)
- Forest Biometrics, Inventory, and Modelling of Growth and Yield (Deadline: 31 July 2024)
- Integrated Measurements for Precision Forestry (Deadline: 31 July 2024)
- Precise Forestry: Forest Dynamic Change Mapping, Monitoring and Modeling (Deadline: 5 August 2024)
- Artificial Intelligence and Machine Learning Applications in Forestry (Deadline: 30 August 2024)
- LiDAR Remote Sensing for Forestry (Deadline: 31 August 2024)
- Satellite Time Series Analysis for Forest Mapping and Change Detection (Deadline: 30 September 2024)
- Methodology and Theory of Forest Parameters Estimation Using Multi-Source Remote Sensing (Deadline: 30 October 2024)