Special Issue "Remote Sensing of Snow and Its Applications"
Deadline for manuscript submissions: 31 October 2018
Snow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water and carbon cycles. Surface temperature is highly dependent on the presence or absence of snow cover, and temperature trends have been shown to be related to changes in snow cover. Its quantification in a changing climate is thus important for various environmental and economic impact assessments. Identification of snowmelt processes could significantly support water management, flood prediction and prevention.
Remote sensing provides a good understanding of snow cover and enable snow cover information to be assimilated into hydrological, land surface, meteorological and climate models for predicting snowmelt runoff, snow water resources and to warn about snow-related natural hazards.
This Special Issue invites and encourages to submit covering all instrumentation/sensors and methodologies/models/algorithms in remote sensing of snow parameters (snow extent, snow depth, snow wetness, snow density, snow water equivalent, etc.) and applications where remotely-sensed snow information are used for, including, but not limited to:
- Remote sensing techniques and methods for snow
- Modelling, retrieval algorithms and in-situ measurements of snow parameters
- Multi-source and multi-sensor remote sensing of snow
- Remote sensing and model integrated approaches of snow
- Applications where remotely sensed snow information used for such as weather forecasting, flooding, avalanche, water management, traffic, health and sport, agriculture and forestry, climate scenarios, etc.
- Copernicus Sentinels, etc.
Dr. Ali Nadir Arslan
Dr. Zuhal Akyurek
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. Geosciences 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 550 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
- snow parameters
- spatial and temporal variability of snow
- snow hydrology
- integration of remote sensing with models (hydrological, land surface, meteorological and climate)
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Snow Data Assimilation and Validation Methods for Hydrological, Land Surface, Meteorological and Climate Models - Review Paper
Improved Snow Thaw and Clearance Date Estimates over Northern Hemisphere
Takala, M., Pulliainen, J
Finnish Meteorological Institute
Scaling Geometric Snow Surface Aerodynamic Roughness Length from Lidar Retrieved Data
Steven R. Fassnacht, Jessica E. Sanow, Ron M. Pasquini, Patrick D. Shipman, Iuliana Oprea, Graham A. Sexstone, Zong-Liang Yang
Colorado State University
US Geological Survey
University of Texas
Integrating Remote Sensing Data and Hydrological Modelling to Estimate Basin-Wide Snow Quantities
Cenk Donmez, Suha Berberoglu, Ahmet Cilek
Cukurova University, Landscape Architecture Department, 01330, Adana, Turkey
Blending remotely sensed and in-situ snow depth using 2-dimensional optimal interpolation
CMNS-Earth System Science Interdisciplinary Center
Title: To be decided
Kim, Edward J.
Title: To be decided
Title: To be decided