Special Issue "Aerial and Near-Field Remote Sensing Developments in Forestry"
Deadline for manuscript submissions: closed (31 December 2018)
Dr. Lin Cao
Department of Forest Resources Management, Faculty of Forestry, Nanjing Forestry University, No. 159 Lonpang Road, Nanjing 210037, China
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Interests: LiDAR applications in forest inventory and management; UAV and their point cloud processing; forest biomass estimation; forest change detection; tree species classification; subtropical forest ecology; ecological modelling; wildlife habitat
Prof. Dr. Nicholas Coops
Department of Forest Resources Management, The University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
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Interests: Active and Passive remote sensing technologies for biodiversity assessment, Forest structure, species diversity and richness, Long Time Series Satellite Data, Dynamic Habitat Index
The past decade has seen an explosion in the availability of highly detailed, remotely sensed information on forestry structure and function. This data revolution has resulted from the widespread use of unmanned aerial vehicles, or drone technologies, the miniaturization of computing and sensor equipment, advances in digital photogrammetric techniques and an improved understanding of how changing spectra and 3D structure can inform our understanding of key forest attributes such as tree dimensions, growth and stand conditions, and characteristics.
Accommodating these acquisition advancements, open source software, cloud computing, and big data allow these datasets to be innovatively processed and linked to other airborne and satellite datasets, which, when integrated intelligently, have the potential to address many of the environmental issues of our time.
This special issue addresses the advancement of these technologies, specifically for forestry applications, be it with forestry production or conservation foci. We encourage papers in the application of 3D technologies such as LiDAR and Photogrammetric Point Clouds (PPS) from UAV/drones from above, or, within the canopy, hand-held or ground-based devices. We encourage papers on the integration of these data with other complementary datasets such as conventional ALS or satellite observations.
Assoc. Prof. Dr. Lin Cao
Prof. Dr. Nicholas Coops
Mr. Tristan Goodbody
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 papers will be 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 1800 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.
- forestry attributes
- tree and stand volume
- unmanned aerial vehicles
- digital aerial photogrammetry
- photogrammetric point clouds
- airborne laser scanning
- terrestrial LiDAR
- species assessment
- tree condition
- plantation forestry