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Land
Special Issues
Quantifying Soil Erosion Processes Using Satellite Data: Progress and Perspectives
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Quantifying Soil Erosion Processes Using Satellite Data: Progress and Perspectives

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land, Soil and Water".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 693

Special Issue Editor

Prof. Dr. Arjun Heimsath

E-Mail Website
Guest Editor
School of Earth and Space Exploration, Arizona State University, ISTB4, Room 795, 781 E. Terrace Road, Tempe, AZ 85287, USA
Interests: landscape archeology; land use; land cover; climate change impacts; geological process; soil erosion; human impacts; cosmogenic nuclides; rock weathering; river incision

Special Issue Information

Dear Colleagues,

Soil erosion has been recognized as one of the most serious global environmental problems we face today, threatening natural resources, agriculture, and the environment.

Although erosion is a natural process, human activities have increased erosion rates by 10–100 times.

There are many preventive and remedial practices that can reduce or limit the erosion of fragile soils.

Remote sensing technology offers a unique means to map, monitor, and analyze the dynamic processes in soil erosion.

The aim of this Special Issue is to collect papers (original research articles and review papers) that provide insights regarding the use of satellite data to observe soil erosion processes, determine the key factors affecting soil erosion, examine the achievements and main challenges associated with erosion prediction, and that recommend further research oriented towards the mitigation of soil erosion and its negative impacts.

The scope of this Special Issue includes, but is not limited to, the following topics:

  • Soil erosion and degradation progress;
  • Land use change and environmental effects;
  • Satellite data and remote sensing technology;
  • High-resolution land topography;
  • Landscape ecology.

We look forward to receiving your original research articles and reviews.

Prof. Dr. Arjun Heimsath
Guest Editor

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 submissions that pass pre-check are 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. Land 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 2600 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

  • soil erosion
  • land degradation
  • land use change
  • remote sensing
  • satellite data
  • human impacts

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Published Papers (1 paper)

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Research

21 pages, 6399 KiB  
Article
An Upscaling-Based Strategy to Improve the Ephemeral Gully Mapping Accuracy
by Solmaz Fathololoumi, Daniel D. Saurette, Harnoordeep Singh Mann, Naoya Kadota, Hiteshkumar B. Vasava, Mojtaba Naeimi, Prasad Daggupati and Asim Biswas
Land 2025, 14(7), 1344; https://doi.org/10.3390/land14071344 - 24 Jun 2025
Viewed by 237
Abstract
Understanding and mapping ephemeral gullies (EGs) are vital for enhancing agricultural productivity and achieving food security. This study proposes an upscaling-based strategy to refine the predictive mapping of EGs, utilizing high-resolution Pléiades Neo (0.6 m) and medium-resolution Sentinel-2 (10 m) satellite imagery, alongside [...] Read more.
Understanding and mapping ephemeral gullies (EGs) are vital for enhancing agricultural productivity and achieving food security. This study proposes an upscaling-based strategy to refine the predictive mapping of EGs, utilizing high-resolution Pléiades Neo (0.6 m) and medium-resolution Sentinel-2 (10 m) satellite imagery, alongside ground-truth EGs mapping in Niagara Region, Canada. The research involved generating spectral feature maps using Blue, Green, Red, and Near-infrared spectral bands, complemented by indices indicative of surface wetness, vegetation, color, and soil texture. Employing the Random Forest (RF) algorithm, this study executed three distinct strategies for EGs identification. The first strategy involved direct calibration using Sentinel-2 spectral features for 10 m resolution mapping. The second strategy utilized high-resolution Pléiades Neo data for model calibration, enabling EGs mapping at resolutions of 0.6, 2, 4, 6, and 8 m. The third, or upscaling strategy, applied the high-resolution calibrated model to medium-resolution Sentinel-2 imagery, producing 10 m resolution EGs maps. The accuracy of these maps was evaluated against actual data and compared across strategies. The findings highlight the Variable Importance Measure (VIM) of different spectral features in EGs identification, with normalized near-infrared (Norm NIR) and normalized red reflectance (Norm Red) exhibiting the highest and lowest VIM, respectively. Vegetation-related indices demonstrated a higher VIM compared to surface wetness indices. The overall classification error of the upscaling strategy at spatial resolutions of 0.6, 2, 4, 6, 8, and 10 m (Upscaled), as well as that of the direct Sentinel-2 model, were 7.9%, 8.2%, 9.1%, 10.3%, 11.2%, 12.5%, and 14.5%, respectively. The errors for EGs maps at various resolutions revealed an increase in identification error with higher spatial resolution. However, the upscaling strategy significantly improved the accuracy of EGs identification in medium spatial resolution scenarios. This study not only advances the methodology for EGs mapping but also contributes to the broader field of precision agriculture and environmental management. By providing a scalable and accessible approach to EGs mapping, this research supports enhanced soil conservation practices and sustainable land management, addressing key challenges in agricultural sustainability and environmental stewardship. Full article
(This article belongs to the Special Issue Quantifying Soil Erosion Processes Using Satellite Data: Progress and Perspectives)
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