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Advanced Remote Sensing Technologies for Soil Erosion Mapping and Modeling
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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: 31 December 2026 | Viewed by 2015

Editors

Dr. Haijing Shi

E-Mail Website
Guest Editor
Institute of Soil and Water Conservation, Northwest A&F University, Xianyang 712100, China
Interests: GIS-based ecological modeling
Dr. Xihua Yang

E-Mail Website
Guest Editor
New South Wales Department of Planning, Industry and Environment, University Technology Sydney, P.O. Box 624, Parramatta, NSW 2150, Australia
Interests: remote sensing; landscape modeling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alfredo Huete

E-Mail Website
Guest Editor
School of Life Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
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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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

22 pages, 1498 KB  
Article
Coupling RUSLE with Spatial Econometrics: A 35-Year Assessment of Soil Erosion Dynamics and Driving Factors on the Loess Plateau, China (1990–2024)
by Yuhanbing Liang, Wen Dai, Yujin Xia, Jiangbing Sun and Qigen Lin
Remote Sens. 2026, 18(12), 2034; https://doi.org/10.3390/rs18122034 - 18 Jun 2026
Abstract
Soil erosion poses a severe threat to agricultural productivity and ecological security on the Loess Plateau. However, previous studies have rarely integrated physical modeling, elasticity coefficients, and spillover effects into a unified framework at the county level. To address this gap, this study [...] Read more.
Soil erosion poses a severe threat to agricultural productivity and ecological security on the Loess Plateau. However, previous studies have rarely integrated physical modeling, elasticity coefficients, and spillover effects into a unified framework at the county level. To address this gap, this study coupled the Revised Universal Soil Loss Equation (RUSLE) with the Spatial Durbin Model (SDM) to systematically investigate the spatiotemporal dynamics, factor elasticity characteristics, and spatial dependence mechanisms of soil erosion on the Loess Plateau from 1990 to 2024. Results show that the annual average erosion rate decreased by 15.5%, with a highly volatile phase before 2001 and a stabilized, low-erosion phase thereafter. The driving factors exhibited marked heterogeneity in direction and strength. The land cover and management factor (C) was the strongest erosion-reducing factor, whereas annual precipitation (PRE) was the primary natural erosion-enhancing factor. County-level erosion also displayed significant positive spatial dependence. PRE had a stable positive indirect effect, whereas C and the support practice factor (P) mainly contained erosion within local jurisdictions. These findings of a unified RUSLE–SDM framework reveal a joint driving mechanism of localized human interventions and climate-driven cross-regional spillovers, providing quantitative support for differentiated soil and water conservation strategies on the Loess Plateau. Full article
(This article belongs to the Special Issue Advanced Remote Sensing Technologies for Soil Erosion Mapping and Modeling)
27 pages, 11903 KB  
Article
Contribution Analysis of Soil Erosion and Future Sustainable Management Zoning in the Wuding River Basin (2001–2024)
by Dangjun Wang, Qiaotian Shen, Ye Wang, Geyu Zhang, Hao Li, Xinyu Lu, Zhiyang Xia, Xiangnan Zhong, Xiangnan Gao, Yangyang Liu and Zhongming Wen
Remote Sens. 2026, 18(11), 1707; https://doi.org/10.3390/rs18111707 - 25 May 2026
Viewed by 380
Abstract
Soil erosion is a serious problem threatening regional ecological security, particularly in the Loess Plateau of China. This study focuses on the Wuding River Basin on the Loess Plateau. Based on multi-source data from 2001 to 2024, the RUSLE model was used to [...] Read more.
Soil erosion is a serious problem threatening regional ecological security, particularly in the Loess Plateau of China. This study focuses on the Wuding River Basin on the Loess Plateau. Based on multi-source data from 2001 to 2024, the RUSLE model was used to estimate the soil erosion modulus. We used comprehensive methods, such as trend analysis, multiple regression, scenario simulation, partial least squares structural equation modeling (PLS-SEM), hot spot analysis, and Hurst exponent, to systematically analyze the spatiotemporal evolution characteristics of soil erosion, the contributions of driving factors, and the sustainability of trends. The results showed that over the 24-year period, the soil erosion modulus in the basin generally showed a decreasing trend, suggesting an improvement in soil erosion conditions. The area of mild and above erosion grades continued to shrink. Among the RUSLE factors, the vegetation cover factor (C) showed a significant downward trend (R2 = 0.7721), with the decreasing area accounting for 95.8%; the rainfall erosivity factor (R) showed a slight upward trend, with the increasing area accounting for 92.7%; and the erosion control practice factor (P) remained stable in most areas (96.8%). Relative contribution analysis indicated that the R-factor dominated the largest area (46.85%), while absolute contribution analysis showed that the C-factor contributed most significantly to erosion reduction. PLS-SEM demonstrated that the influence pathways of natural factors and human activities on soil erosion differed significantly across spatial and temporal scales. On the temporal scale, the R-factor had the strongest direct positive effect on erosion; on the spatial scale, the topography factor (LS) had the strongest positive effect on erosion. Furthermore, we found that the disturbance of vegetation by human activities is being weakened with the continuous implementation of soil and water conservation projects. The cold and hot spots of erosion trends were concentrated in the southeastern part of the basin. Based on trend sustainability, the basin was divided into successfully treated areas (57.6%), potential rebound risk areas (29.4%), emergency treatment areas (11.2%), and monitoring priority areas (1.8%). Overall, this study advances the understanding of soil erosion evolution under long-term ecological restoration and provides a scientific basis for optimizing sustainable soil and water conservation management in the Wuding River Basin. Full article
(This article belongs to the Special Issue Advanced Remote Sensing Technologies for Soil Erosion Mapping and Modeling)
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33 pages, 37111 KB  
Article
Regional Soil Erosion Assessment Using Remote Sensing and Field Validation: Enhancing the Erosion Potential Model
by Siniša Polovina, Boris Radić, Vukašin Milčanović, Ratko Ristić, Ivan Malušević, Armin Hadžialić and Šemsa Imširović
Remote Sens. 2026, 18(8), 1227; https://doi.org/10.3390/rs18081227 - 18 Apr 2026
Cited by 1 | Viewed by 516
Abstract
Soil erosion assessment in Southeast Europe’s mountainous regions often lacks systematic field validation, limiting confidence in model-based predictions. This study integrates the Erosion Potential Model (EPM) with remote sensing and field verification across 26,570 km2 in the Federation of Bosnia and Herzegovina [...] Read more.
Soil erosion assessment in Southeast Europe’s mountainous regions often lacks systematic field validation, limiting confidence in model-based predictions. This study integrates the Erosion Potential Model (EPM) with remote sensing and field verification across 26,570 km2 in the Federation of Bosnia and Herzegovina (FBiH) and Brčko District (BD). We developed a two-stage framework: initial GIS-based assessment using digital elevation models, soil maps, climate data, CORINE Land Cover, and Landsat imagery, followed by field calibration at 190 representative sites. Spectral indices (NDVI, BSI) provided dynamic corrections for vegetation cover and visible erosion features. Field validation significantly improved model performance; the erosion coefficient increased from Z = 0.21 to Z = 0.24, while discriminatory power improved AUC from 0.82 to 0.85, with corresponding gains in overall accuracy from 0.78 to 0.84 and F1-score from 0.78 to 0.85. The field-validated model estimated mean annual sediment production of 546.60 m3·km−2·year−1, with total erosion material production of 14,074,940.2 m3·year−1. Field calibration revealed substantial spatial redistribution, with medium-to-excessive erosion categories expanding by 30.37%, affecting 1319.12 km2 requiring priority intervention. The Kappa coefficient (0.81) confirms high classification reliability. This field-validated framework enables evidence-based identification of degradation hotspots and provides actionable guidance for soil conservation planning in geomorphologically heterogeneous, data-limited regions. Full article
(This article belongs to the Special Issue Advanced Remote Sensing Technologies for Soil Erosion Mapping and Modeling)
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24 pages, 4043 KB  
Article
Spatiotemporal Analysis and Multi-Scenario Projection of Soil Erosion in the Loess Plateau Using the PLUS-CSLE Model
by Xiaohan Su, Haijing Shi, Yangyang Liu, Zhongming Wen, Ye Wang, Guang Yang, Yufei Zhang and Xihua Yang
Remote Sens. 2026, 18(8), 1202; https://doi.org/10.3390/rs18081202 - 16 Apr 2026
Viewed by 437
Abstract
Soil erosion remains a critical ecological challenge on China’s Loess Plateau (LP), where fragile geomorphology and intensive human activities jointly amplify land degradation risks. As land-use and land-cover change (LUCC) is a primary determinant of erosion processes, clarifying the nexus between land patterns [...] Read more.
Soil erosion remains a critical ecological challenge on China’s Loess Plateau (LP), where fragile geomorphology and intensive human activities jointly amplify land degradation risks. As land-use and land-cover change (LUCC) is a primary determinant of erosion processes, clarifying the nexus between land patterns and erosion intensity is essential for formulating effective conservation strategies. This study integrates the Chinese Soil Loss Equation (CSLE) with the Patch-generating Land Use Simulation (PLUS) model to analyze the spatiotemporal dynamics of soil erosion from 2000 to 2020 and project future patterns for 2060 under five scenarios: Natural Development (ND), Ecological Protection (EP), Economic Development (ED), Cropland Protection (CP), and Planning Guidance (PG). Results indicate a fluctuating decline in LP soil erosion during 2000–2020, marked by a transition toward predominantly slight erosion (~70% of the total area), while high-intensity erosion remained concentrated in central and western cropland and grassland. Scenario projections reveal pronounced divergence in erosion outcomes. The EP scenario, characterized by sustained vegetation expansion, demonstrated the highest efficacy in erosion mitigation. Conversely, the ED scenario exhibited the most severe erosion risk due to urban expansion into ecological areas. The PG scenario effectively reconciled the trade-offs between ecological conservation and socioeconomic demands, maintaining a balanced erosion control performance. In the context of global climate change, the complexity of soil and water conservation governance is expected to intensify. This study suggests that future efforts should focus on scientifically guiding the evolution of land-use patterns through sustainable spatial planning. Furthermore, targeted engineering and biological conservation measures must bae implemented for high-risk land categories to ensure the long-term stability of the regional ecological security barrier. Full article
(This article belongs to the Special Issue Advanced Remote Sensing Technologies for Soil Erosion Mapping and Modeling)
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