Special Issue "Remote Sensing of Permafrost Environment Dynamics"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Dr. Stéphane Guillaso
E-Mail Website
Guest Editor
Remote Sensing Section 1.4, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Germany
Interests: radar remote sensing; optical remote sensing; electromagnetism; permafrost; periglacial regions
Dr. Franck Garestier
E-Mail Website
Guest Editor
Remote Sensing Group, lab M2C, UMR CNRS 6143, 24, rue des Tilleuls, University of Caen-Normandy, 14000 Caen, France
Interests: SAR interferometry; permafrost
Dr. Elena Zakharova
E-Mail
Guest Editor
IRSTEA, 3275, Route de Cézanne, Aix-en-Provence, 13182, France
Tel. +33 442669958
Interests: hydrology; altimetry; optical imagery; cold regions
Dr. Thomas Schmid
E-Mail
Guest Editor
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Avenida Complutense 40, 28040 Madrid, Spain
Interests: soil; periglacial processes; optical remote sensing; SAR; Antarctica

Special Issue Information

Dear Colleagues,

The thawing of permafrost due to global warming is an increasing problem and is evermore affecting polar and high-altitude regions that are regarded as the most climate-sensitive places on Earth. The consequences of the release of greenhouse gases, altered landscapes, and crumbling infrastructures due to unstable ground are already starting to cause devastating effects on ecosystems and communities living within these regions.

The monitoring of these phenomena often requires the use of remote sensed (optical, thermal, and/or radar) data where access to a site of interest is often time consuming and costly. Furthermore, new sensor technologies with high spatial and temporal resolutions and advanced remote sensing data processing capacities create new opportunities for periglacial studies.

This Special Issue aims to present new and/or innovative methods/approaches/products to characterize the permafrost environment dynamics using remote sensing data. We welcome original manuscripts that use different remotely sensed data available from field to satellite-borne sensors for describing the characteristics and dynamics of permafrost environments. Submissions using multiple scales and time series data together with field observations and measurements are encouraged.

Dr. Stéphane Guillaso
Dr. Franck Garestier
Dr. Elena Zakharova
Dr. Thomas Schmid
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. 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.

Keywords

  • Remote sensing
  • Permafrost environment dynamics
  • Field observations
  • Soil development
  • Periglacial processes
  • Time series

Published Papers (2 papers)

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Research

Open AccessArticle
Assessing Spatiotemporal Variations of Landsat Land Surface Temperature and Multispectral Indices in the Arctic Mackenzie Delta Region between 1985 and 2018
Remote Sens. 2019, 11(19), 2329; https://doi.org/10.3390/rs11192329 - 08 Oct 2019
Abstract
Air temperatures in the Arctic have increased substantially over the last decades, which has extensively altered the properties of the land surface. Capturing the state and dynamics of Land Surface Temperatures (LSTs) at high spatial detail is of high interest as LST is [...] Read more.
Air temperatures in the Arctic have increased substantially over the last decades, which has extensively altered the properties of the land surface. Capturing the state and dynamics of Land Surface Temperatures (LSTs) at high spatial detail is of high interest as LST is dependent on a variety of surficial properties and characterizes the land–atmosphere exchange of energy. Accordingly, this study analyses the influence of different physical surface properties on the long-term mean of the summer LST in the Arctic Mackenzie Delta Region (MDR) using Landsat 30 m-resolution imagery between 1985 and 2018 by taking advantage of the cloud computing capabilities of the Google Earth Engine. Multispectral indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Tasseled Cap greenness (TCG), brightness (TCB), and wetness (TCW) as well as topographic features derived from the TanDEM-X digital elevation model are used in correlation and multiple linear regression analyses to reveal their influence on the LST. Furthermore, surface alteration trends of the LST, NDVI, and NDWI are revealed using the Theil-Sen (T-S) regression method. The results indicate that the mean summer LST appears to be mostly influenced by the topographic exposition as well as the prevalent moisture regime where higher evapotranspiration rates increase the latent heat flux and cause a cooling of the surface, as the variance is best explained by the TCW and northness of the terrain. However, fairly diverse model outcomes for different regions of the MDR (R2 from 0.31 to 0.74 and RMSE from 0.51 °C to 1.73 °C) highlight the heterogeneity of the landscape in terms of influential factors and suggests accounting for a broad spectrum of different factors when modeling mean LSTs. The T-S analysis revealed large-scale wetting and greening trends with a mean decadal increase of the NDVI/NDWI of approximately +0.03 between 1985 and 2018, which was mostly accompanied by a cooling of the land surface given the inverse relationship between mean LSTs and vegetation and moisture conditions. Disturbance through wildfires intensifies the surface alterations locally and lead to significantly cooler LSTs in the long-term compared to the undisturbed surroundings. Full article
(This article belongs to the Special Issue Remote Sensing of Permafrost Environment Dynamics)
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Open AccessArticle
Seasonal Progression of Ground Displacement Identified with Satellite Radar Interferometry and the Impact of Unusually Warm Conditions on Permafrost at the Yamal Peninsula in 2016
Remote Sens. 2019, 11(16), 1865; https://doi.org/10.3390/rs11161865 - 09 Aug 2019
Abstract
Ground subsidence monitoring by Synthetic Aperture Radar interferometry (InSAR) over Arctic permafrost areas is largely limited by long revisit intervals, which can lead to signal decorrelation. Recent satellite missions such as COSMO-Skymed (X-band) and Sentinel-1 (C-band) have comparably short time intervals of a [...] Read more.
Ground subsidence monitoring by Synthetic Aperture Radar interferometry (InSAR) over Arctic permafrost areas is largely limited by long revisit intervals, which can lead to signal decorrelation. Recent satellite missions such as COSMO-Skymed (X-band) and Sentinel-1 (C-band) have comparably short time intervals of a few days. We analyze dense records of COSMO-Skymed from 2013 and 2016 and of Sentinel-1 from 2016, 2017, and 2018 for the unfrozen period over central Yamal (Russia). These years were distinct in environmental conditions and 2016 in particular was unusually warm. We evaluate the InSAR-derived displacement with in situ subsidence records, active-layer thickness measurements, borehole temperature records, meteorological data, C-band scatterometer records, and a land-cover classification based on Sentinel-1 and -2 data. Our results indicate that a comparison of seasonal thaw evolution between years is feasible after accounting for the early thaw data gap in InSAR time series (as a result of snow cover) through an assessment with respect to degree-days of thawing. Average rates of subsidence agree between in situ and Sentinel-1 (corrected for viewing geometry), with 3.9 mm and 4.3 mm per 100 degree-days of thaw at the test site. X-band and C-band records agree well with each other, including seasonal evolution of subsidence. The average displacement is more than twice in magnitude at the active-layer monitoring test site in 2016 compared to the other years. We further demonstrate that InSAR displacement can not only provide information on the magnitude of ground thaw but also on soil properties through analyses of seasonal evolution in extreme years. Full article
(This article belongs to the Special Issue Remote Sensing of Permafrost Environment Dynamics)
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