Special Issue "Remote Sensing of Soil Erosion"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 31 May 2020.

Special Issue Editors

Dr. Dimitrios D. Alexakis
E-Mail Website
Guest Editor
Assistant Researcher (Researcher C’), GeoSAT ReSearch Lab, Institute for Mediterranean Studies, Foundation for Research and Technology Hellas (FORTH), Rethymno 74100, Greece
Interests: remote sensing (satellite, SAR, UAV, aerial, lidar); GIS; geomorphology; natural hazards; spatial analysis; land use/land cover monitoring; soil erosion; soil moisture; floods; landscape ecology; landscape archaeology; hydrology; environmental surveillance
Special Issues and Collections in MDPI journals
Dr. Athos Agapiou
E-Mail Website
Guest Editor
Department of Civil Engineering and Geomatics, Eratosthenes Research Centre, Cyprus University of Technology, Saripolou 2-8, Limassol 3036, Cyprus
Interests: Remote Sensing, Optical Sensors, Landscape Archaeology, GIS
Special Issues and Collections in MDPI journals
Dr. Antonios Mouratidis
E-Mail Website
Guest Editor
Department of Physical and Environmental Geography, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Tel. +30 6945670903
Interests: SAR Remote Sensing, Geomorphology, Digital Elevation Models, GIS, Education

Special Issue Information

Dear Colleagues,

Soil erosion is considered a major environmental problem, as it seriously threatens natural resources, agriculture, and the environment. This Special Issue aims to assess the impact of a changing climate, land use, soil moisture, hydrology, topography, and vegetation cover on the soil erosion processes. Thus, several innovative Earth observation (EO) approaches (satellite remote sensing, field spectroscopy, UAVs, LiDAR, SAR, and aerial photos) will be investigated for their potential and impact on monitoring soil properties and the corresponding soil erosion phenomena. Remote sensing offers a unique opportunity to map, monitor, quantify, and analyze, in detail, the processes that contribute to soil loss as a result of water erosion. The main aim of this Special Issue is to raise a dialogue between remote sensing experts about the use, perspective, and current limits of EO and the associated geospatial science and technology in monitoring and modeling soil erosion both at a local and regional scale. In addition, this Special Issue can include topics related to soil loss and erosion as a result of climate change, land degradation, current and future land use, and agricultural practices, as well as the associated educational aspects. Authors are encouraged to submit articles on, but not limited to, the following subjects:

  • Soil erosion
  • Remote sensing (both optical and SAR)
  • UAVs
  • LiDAR
  • Climate change
  • Land use
  • Geomorphology
  • Hydrology
  • Landscape ecology
  • Land degradation
  • Conservation practices
  • GIS modelling (RUSLE, G2, etc.)
  • High resolution land topography
  • Remote sensing education, training, capacity building, and outreach practices and activities related to soil erosion.

Dr. Dimitrios D. Alexakis
Dr. Athos Agapiou
Dr. Antonios Mouratidis
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 2000 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.

Published Papers (1 paper)

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Open AccessArticle
Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)
Remote Sens. 2019, 11(21), 2577; https://doi.org/10.3390/rs11212577 - 02 Nov 2019
Cited by 3
Gully erosion is considered to be one of the main causes of land degradation in arid and semi-arid territories around the world. In this research, gully erosion susceptibility mapping was carried out in Semnan province (Iran) as a case study in which we [...] Read more.
Gully erosion is considered to be one of the main causes of land degradation in arid and semi-arid territories around the world. In this research, gully erosion susceptibility mapping was carried out in Semnan province (Iran) as a case study in which we tested the efficiency of the index of entropy (IoE), the Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and their combination. Remote sensing and geographic information system (GIS) were used to reduce the time and costs needed for rapid assessment of gully erosion. Firstly, a gully erosion inventory map (GEIM) with 206 gully locations was obtained from various sources and randomly divided into two groups: A training dataset (70% of the data) and a validation dataset (30% of the data). Fifteen gully-related conditioning factors (GRCFs) including elevation, slope, aspect, plan curvature, stream power index, topographical wetness index, rainfall, soil type, drainage density, distance to river, distance to road, distance to fault, lithology, land use/land cover, and soil type, were used for modeling. The advanced land observing satellite (ALOS) digital elevation model with a spatial resolution of 30 m was used for the extraction of the above-mentioned topographic factors. The tolerance (TOL) and variance inflation factor (VIF) were also included for checking the multicollinearity among the GRCFs. Based on IoE, we concluded that soil type, lithology, and elevation were the most significant in terms of gully formation. Validation results using the area under the receiver operating characteristic curve (AUROC) showed that IoE (0.941) reached a higher prediction accuracy than VIKOR (0.857) and VIKOR-IoE (0.868). Based on our results, the combination of statistical (IoE) models along with remote sensing and GIS can convert the multi-criteria decision-making (MCDM) models into efficient and powerful tools for gully erosion prediction. We strongly suggest that decision-makers and managers should use these kinds of results to develop more consistent solutions to achieve sustainable development on degraded lands such as in the Semnan province. Full article
(This article belongs to the Special Issue Remote Sensing of Soil Erosion)
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