Special Issue "Remote Sensing of Snow and Its Applications"

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Geophysics".

Deadline for manuscript submissions: 15 December 2018

Special Issue Editors

Guest Editor
Dr. Ali Nadir Arslan

Finnish Meteorological Institute, Helsinki, Finland
Website | E-Mail
Interests: remote sensing; electromagnetic theory & modeling; methods & applications for cryosphere; snow cover; phenology
Guest Editor
Dr. Zuhal Akyurek

Middle East Technical University, Ankara, Turkey
Website | E-Mail
Interests: snow hydrology; modelling; optical remote sensing; spatial variability of snow

Special Issue Information

Dear Colleagues,

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
Guest Editors

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)

Published Papers (1 paper)

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Open AccessArticle Analysis of QualitySpec Trek Reflectance from Vertical Profiles of Taiga Snowpack
Geosciences 2018, 8(11), 404; https://doi.org/10.3390/geosciences8110404
Received: 20 September 2018 / Revised: 26 October 2018 / Accepted: 1 November 2018 / Published: 6 November 2018
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Snow microstructure is an important factor for microwave and optical remote sensing of snow. One parameter used to describe it is the specific surface area (SSA), which is defined as the surface-area-to-mass ratio of snow grains. Reflectance at near infrared (NIR) and short-wave
[...] Read more.
Snow microstructure is an important factor for microwave and optical remote sensing of snow. One parameter used to describe it is the specific surface area (SSA), which is defined as the surface-area-to-mass ratio of snow grains. Reflectance at near infrared (NIR) and short-wave infrared (SWIR) wavelengths is sensitive to grain size and therefore also to SSA through the theoretical relationship between SSA and optical equivalent grain size. To observe SSA, the IceCube measures the hemispherical reflectance of a 1310 nm laser diode from the snow sample surface. The recently developed hand-held QualitySpec Trek (QST) instrument measures the almost bidirectional spectral reflectance in the range of 350–2500 nm with direct contact to the object. The geometry is similar to the Contact Probe, which was previously used successfully for snow measurements. The collected data set includes five snow pit measurements made using both IceCube and QST in a taiga snowpack in spring 2017 in Sodankylä, Finland. In this study, the correlation between SSA and a ratio of 1260 nm reflectance to differentiate between 1260 nm and 1160 nm reflectances is researched. The correlation coefficient varied between 0.85 and 0.98, which demonstrates an empirical linear relationship between SSA and reflectance observations of QST. Full article
(This article belongs to the Special Issue Remote Sensing of Snow and Its Applications)

Figure 1

Planned Papers

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
Cezar Kongoli
CMNS-Earth System Science Interdisciplinary Center

Title: To be decided
Kim, Edward J.

Title: To be decided
Juraj Parajka

Title: To be decided
Zuhal Akyurek

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