Advanced Remote Sensing Technologies for Soil Erosion Mapping and Modeling
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 21
Special Issue Editors
Interests: GIS-based ecological modeling
Interests: remote sensing; landscape modeling
Special Issues, Collections and Topics in MDPI journals
Interests: biophysical remote sensing; terrestrial ecohydrology; land surface phenology; carbon and water fluxes; geostationary and low-earth observations; time series analyses; climate change impacts; vegetation health and ecosystem resilience; ecological forecasting
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Soil erosion is a critical global environmental threat that jeopardises land productivity, water quality, and ecosystem sustainability. Accurate and timely estimation of soil erosion rates is paramount for developing effective conservation strategies. While traditional methods like the Revised Universal Soil Loss Equation (RUSLE) are widely used, they often suffer from limitations in data availability and spatial resolution. The advent of high-resolution remote sensing data (from satellites, UAVs, etc.) and advanced geospatial technologies (GIS, machine learning) has revolutionised our ability to map, monitor, and model soil erosion processes at multiple scales with unprecedented accuracy. This Special Issue aims to capture the latest advancements in leveraging remote sensing for precise and dynamic soil erosion estimation.
This Special Issue, entitled "Advanced Remote Sensing Technologies for Soil Erosion Mapping and Modeling", aligns perfectly with the Remote Sensing journal's scope of "applied remote sensing for environmental monitoring and management." The primary aim is to collate innovative research that integrates remote sensing data with modeling approaches to improve the quantification of soil erosion. We encourage submissions that address key challenges, such as deriving high-resolution input parameters (e.g., C-factor, P-factor), quantifying gully erosion, assessing the impact of conservation practices, and forecasting erosion under climate change scenarios.
We invite original research articles, reviews, and case studies on topics including, but not limited to, the following:
- Novel remote sensing techniques for mapping soil erosion features (gullies, rills);
- Machine learning and AI applications in soil erosion prediction;
- High-resolution mapping of RUSLE parameters using satellite/UAV imagery;
- Integration of multi-source data (optical, radar, LiDAR) for comprehensive erosion assessment;
- Soil erosion monitoring and assessment at various scales (from plot to watershed);
- Impact assessment of land use/cover change and soil conservation measures on erosion dynamics;
- Applications of UAV/drones in quantifying soil erosion and sediment transport.
Dr. Haijing Shi
Dr. Xihua Yang
Prof. Dr. Alfredo Huete
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 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 250 words) can be sent to the Editorial Office for assessment.
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 2700 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
- remote sensing
- RUSLE
- gully erosion
- land degradation
- machine learning
- GIS
- UAV
- sediment yield
- conservation practices
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