Special Issue "Remote Sensing Technology Applications in Forestry and REDD+"
A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Quantitative Methods and Remote Sensing".
Deadline for manuscript submissions: closed (31 August 2019).
A printed edition of this Special Issue is available here.
Interests: LiDAR; 3D measurements; remote sensing; ecosystem monitoring and modelling; fusion of ground-based and airborne data
Interests: remote Sensing and Earth observation; In situ vegetation structure and biomass assessment; Carbon studies in the climate change context
Interests: remote sensing; laser scanning; precision forestry; forest structure
Interests: assessing the quality of information about forests derived from in situ measurement devices and Earth Observation satellites; improving global satellite-derived biophysical product validation strategies; and contributing to good practice guidance for the evaluation of ECV data records
Special Issues and Collections in MDPI journals
Advances in close-range and remote sensing technologies drive innovations in forest resource assessments and monitoring at varying scales. Data acquired with airborne and spaceborne platforms provide us with higher spatial resolution, more frequent coverage and an increased spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems and community-based monitoring of forests. The UNFCCC REDD+ mechanism has moved the remote sensing community in advancing and developing forest geospatial products which can be used by countries for the international reporting and national forest monitoring. However, there still is an urgent need to better understand the options and limitations of remote and close-range sensing techniques in the field of degradation and forest change.
Therefore, we invite scientists working on remote sensing technologies, close-range sensing and field data to contribute to this Special Issue. Topics of interest include (a) novel remote sensing applications that can advance the needs on forest resource information and REDD+ MRV; (b) case studies of applying remote sensing data for REDD+ MRV; (c) timeseries’ algorithms and methodologies for forest resource assessment at the different spatial scales varying from tree to national level; (d) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV; We would particularly welcome submissions on data fusion.
Dr. Kim Calders
Dr. Inge Jonckheere
Assoc. Prof. Mikko Vastaranta
Dr. Joanne Nightingale
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. Forests is an international peer-reviewed open access monthly 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.
- Remote sensing
- Close-range sensing