Special Issue "Lidar Remote Sensing of Forest Structure, Biomass and Dynamics"
Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 38435
Interests: remote sensing of vegetation; LiDAR; 3D point cloud processing and pattern recognition; machine learning; 3D forest structure; tree modeling; forest demographics and disturbance; large-scale forest biomass mapping
Interests: remote sensing of vegetation; 3D forest structure and dynamics characterization using active and passive sensors; forest fires (fuels characterization—moisture and structure—and post fire damage assessment and recovery); data integration; machine learning; radiative transfer models
Interests: forest ecology; remote sensing; LiDAR; forest inventory; tree size scaling theories; forest structure; competition and dominance; modelling; data fusion
Special Issues, Collections and Topics in MDPI journals
Special Issue in Forests: Applications of LiDAR and Photogrammetry for Forest Inventory and Management
Special Issue in Remote Sensing: Remote Sensing Data Fusion for Mapping Ecosystem Dynamics
Special Issue in Forests: Remote Sensing of Forest Disturbance and Recovery
LiDAR remote sensing is widely accepted as the most appropriate technique to characterize the 3D forest structure and therefore a valuable tool to a broad range of applications that require information in both vertical and horizontal dimensions. LiDAR products in the forestry domain include biomass mapping, fuels assessment, heterogeneity indexes, tree/stand structural traits, ecological indicators, habitat mapping, and forest disturbance and regrowth. LiDAR technology has evolved at an incredible speed and includes new multispectral sensors; increased productivity by using MPiA (multiple points in the air) or SPL (single photon LiDAR); and multiple platforms such as terrestrial, drone, airborne, and satellite. Due to its reliability, LiDAR-derived metrics and models are currently seen as a crucial tool for the calibration and validation of satellite observations with applications in the field of terrestrial ecosystems sciences (e.g., GEDI, NISAR, BIOMASS, Sentinel, Landsat, and SBG). In addition, LiDAR products are being increasingly used to initialize and constrain ecological (e.g., evapotranspiration) and demographic models.
The Special Issue is calling for original and innovative papers that demonstrate the use of LiDAR techniques from all platforms (e.g., satellite, airborne, terrestrial, and UAV) to advance remote sensing applications for forest science and ecology and support forest inventories. We welcome contributions showing the potential of LiDAR as a valuable tool for current environmental challenges over different forested biomes.
Welcome topics include but are not limited to the following:
- Forest structure mapping from terrestrial, airborne, and satellite LiDAR;
- Operational use of LiDAR data to characterize forest structures;
- Quantifying carbon stocks using LiDAR;
- Mapping forest degradation from LiDAR data;
- Forest structure dynamics using LiDAR;
- Uncertainty in measuring forest structure;
- Novel sensors and platforms: multispectral lidar and UAV-LiDAR;
- Integration of LiDAR with other remote measurements (SAR, optical, eddy covariance, etc.).
Dr. António Ferraz
Dr. Mariano García
Dr. Rubén Valbuena
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Forest structure
- Forest dynamics
- Multiplatform LiDAR
- Multispectral LiDAR
- Data integration
- Forest inventory
- Forest management
- Ecological applications
- Habitat mapping
- 3D point cloud processing
- Uncertainties assessment