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Special Issue "Radiative Transfer Modelling and Applications in Remote Sensing"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (31 July 2018).
Dr. Yuri Knyazikhin
Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA
Interests: forward and inverse radiative transfer theory; developing satellite products; numerical radiative transfer equation; analyses of satellite data
Dr. Matti Mõttus
VTT Technical Research Centre of Finland, PO Box 1000, Tekniikantie 1, Espoo, FIN-02044 VTT, Finland
Tel. +358 40 849 3037
Interests: forest reflectance models; imaging spectroscopy of vegetation photosynthesis; application of photon recollision probability in vegetation reflectance models; spectral measurements from leaf to canopy scales; radiation field inside vegetation canopies; hyperspectral remote sensing
The radiative transfer theory provides the most logical linkage between observations and physical processes that generate signals in optical remote sensing. The radiative transfer equation, therefore, is an integral part of Earth remote sensing, since it provides the most efficient tool for accurate retrievals of Earth properties from satellite data. Advances in radiative transfer modeling enhance our ability to detect and monitor changes in our planet through new methodologies and technical approaches to analyze and interpret measurements from space-borne sensors.
We invite scientists working on forward and inverse radiative transfer to contribute to this Special Issue. Topics of interest include (a) theoretical aspects of radiative transfer that can advance remote sensing techniques; (b) models for radiative transfer in the atmosphere and the Earth's surface that further our understanding of information content of multiangle, spectral and polarimetric data; (c) analyses of 3D effects in radiative transfer and associated uncertainties in interpretation of remotely sensed data; and (d) methodologies that minimize the discretizing effects in numerical solutions of the radiative transfer equation. Contributions related to development of various indices that correlate with parameters of the atmosphere and land surface are also encouraged. However, we expect that such papers will provide analyses of underlying physical mechanisms of the correlation, which is required to distinguish causality from correlations in interpretation of remote sensing data.
Dr. Yuri Knyazikhin
Dr. Alexander Marshak
Dr. Matti Mõttus
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.
- radiative transfer equation
- inverse technique
- multiangle, spectral and polarimetric signals
- computational methods
- remote sensing indices