Special Issue "Digital Forest Resource Monitoring and Uncertainty Analysis"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (31 December 2016)
Prof. Dr. Guangxing Wang
Southern Illinois University, Department of Geography and Environmental Resources
Website | E-Mail
Interests: remote sensing, GIS, spatial statistics, natural and environmental resources, sampling design; environmental quality assessment; forest and city vegetation carbon sequestration, desertification trend monitoring, quality assessment and spatial uncertainty analysis
Currently, global warming is of major concern. To mitigate this effect, it is essential to provide policy makers with accurate information on the carbon cycle. As a significant carbon sink of terrestrial ecosystems, forests play a critical role in reducing carbon concentration in the atmosphere and in the mitigation of global warming. However, one great challenge in estimation of forest resources, and their carbon sequestration and dynamics is how to quantify its spatial distributions at various scales, including global, national, regional, and local levels. The estimates of forest resources and carbon stocks are also associated with large uncertainties and improving the quality of the products has become very important and urgent. Digital forest resource monitoring and uncertainty analysis provide the potential for searching for appropriate solutions to these challenges. Furthermore, new remote sensing technologies and their integrations with national forest sample plot data and growth models will offer powerful tools for developing solutions.
This Special Issue, "Digital Forest Resource Monitoring and Uncertainty Analysis”, will call for papers that demonstrate the original research that can overcome current significant gaps in the generation and quality assessment of digital forest resources and carbon products and provide quality control/assurance mechanisms to support decision-making regarding forest resource management and carbon simulation and thus mitigation of the greenhouse effect. Review articles are also welcome. It is expected that the papers will focus on the applications of remote sensing technologies to forest resource inventory and monitoring, and forest biomass/carbon modeling, and that the topics will include:
1) Optimal sampling strategy and designs for forest resource inventory and monitoring;
2) New methods and algorithms for forest resource inventory and monitoring, and forest biomass/carbon modeling;
3) New remote sensing technologies for forest resource inventory and monitoring, and forest biomass/carbon modeling;
4) Integration of multi-sensor data for forest resource inventory and monitoring, and forest biomass/carbon modeling;
5) Accuracy assessment and uncertainty analysis of forest resource and biomass/carbon products.
Prof. Guangxing Wang
Prof. Erkki Tomppo
Prof. Dengsheng Lu
Prof. Huaiqing Zhang
Prof. Qi Chen
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.