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Special Issue "Modeling Saturation of Spectral Reflectance and Radar Data and Developing Corresponding Methods for Biomass Estimation of Various Forests"
Deadline for manuscript submissions: 31 December 2019.
Prof. Dr. Guangxing Wang Website E-Mail
Southern Illinois University, Department of Geography and Environmental Resources
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
Prof. Dr. Markus Holopainen E-Mail
Department of Forest Resource Management, University of Helsinki, Helsinki, Finland
Interests: forest biomass estimation using remotely sensed data including optical images and LiDAR data
Dr. Liyong Fu E-Mail
Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
Interests: forest growth and yield modeling, forest biomass estimation
Forests play a critical role in reducing carbon concentrations in the atmosphere and in the mitigation of global warming. Thus, accurately estimating and mapping forest biomass/carbon at regional, national and global scales is very important. Various remotely sensed data including optical images, LiDAR and radar data have been used for the purpose. However, saturation of spectral reflectance and radar data impedes the increase of estimation accuracy of forest biomass/carbon, and currently there have been only few reports that deal with examining the saturation and searching for corresponding solutions. LiDAR data provide a solution for the purpose, but, their applications are limited because of high cost for estimating and mapping forest biomass/carbon for large areas. Therefore, there is strong need of modeling the saturation of spectral reflectance and radar data for biomass/carbon estimation of various forests and developing corresponding methods.
This Special Issue, "Modeling Saturation of Spectral Reflectance and Radar Data and Developing Corresponding Methods for Biomass Estimation of Various Forests”, will call for papers that demonstrate the original research that can overcome current significant gaps in examining the saturation of spectral reflectance and radar data and develop corresponding solutions. Review articles are also welcome. The topics will include: 1) examining the saturation of spectral reflectance of optical images for estimating and mapping biomass/carbon of various forest ecosystems; 2) examining the saturation of radar data for estimating and mapping biomass/carbon of various forest ecosystems; and 3) developing new methods and algorithms for overcoming the saturations.
Prof. Dr. Guangxing Wang
Prof. Dr. Dengsheng Lu
Prof. Dr. Qi Chen
Prof. Dr. Markus Holopainen
Dr. Liyong Fu
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.