Next Article in Journal
Extraction of Broad-Leaved Tree Crown Based on UAV Visible Images and OBIA-RF Model: A Case Study for Chinese Olive Trees
Next Article in Special Issue
A New Systematic Framework for Optimization of Multi-Temporal Terrestrial LiDAR Surveys over Complex Gully Morphology
Previous Article in Journal
Forest Fire Monitoring and Positioning Improvement at Subpixel Level: Application to Himawari-8 Fire Products
Previous Article in Special Issue
Automatic Extraction of Mountain River Surface and Width Based on Multisource High-Resolution Satellite Images
 
 
Review

A Review on the Possibilities and Challenges of Today’s Soil and Soil Surface Assessment Techniques in the Context of Process-Based Soil Erosion Models

1
Department of Physical Geography, Friedrich-Schiller University Jena, 07743 Jena, Germany
2
District Administration Siegen-Wittgenstein, Administrative Department for Climate and Sustainable Mobility, 57072 Siegen, Germany
3
Thuringian State Institute of Agriculture, 07743 Jena, Germany
4
Institute of Photogrammetry and Remote Sensing, Technical University Dresden, 01069 Dresden, Germany
5
Institute of Drilling Engineering and Fluid Mining, Flow and Transport Modelling in the Geosphere, TU Bergakademie Freiberg, 09599 Freiberg, Germany
6
Department Ecology and Environment, IPROconsult GmbH, 01069 Dresden, Germany
7
Institute of Geoecology, Landscape Ecology and Environmental Systems Analysis, TU Braunschweig, 38106 Braunschweig, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: José Vicente Pérez-Peña and Álvaro Gómez-Gutiérrez
Remote Sens. 2022, 14(10), 2468; https://doi.org/10.3390/rs14102468
Received: 4 April 2022 / Revised: 12 May 2022 / Accepted: 19 May 2022 / Published: 20 May 2022
(This article belongs to the Special Issue Quantifying Landscape Evolution and Erosion by Remote Sensing)
To investigate relevant processes as well as to predict the possible impact of soil erosion, many soil erosion modelling tools have been developed. The most productive development of process-based models took place at the end of the 20th century. Since then, the methods available to observe and measure soil erosion features as well as methods to inter- and extrapolate such data have undergone rapid development, e.g., photogrammetry, light detection and ranging (LiDAR) and sediment tracing are now readily available methods, which can be applied by a broader community with lower effort. This review takes 13 process-based soil erosion models and different assessment techniques into account. It shows where and how such methods were already implemented in soil erosion modelling approaches. Several areas were found in which the models miss the capability to fully implement the information, which can be drawn from the now-available observation and data preparation methods. So far, most process-based models are not capable of implementing cross-scale erosional processes and can only in parts profit from the available resolution on a temporal and spatial scale. We conclude that the models’ process description, adaptability to scale, parameterization, and calibration need further development. The main challenge is to enhance the models, so they are able to simulate soil erosion processes as complex as they need to be. Thanks to the progress made in data acquisition techniques, achieving this aim is closer than ever, if models are able to reap the benefit. View Full-Text
Keywords: process-based soil erosion model; remote sensing; photogrammetric methods; tracing; soil surface measurement; soil assessment; soil erosion process-based soil erosion model; remote sensing; photogrammetric methods; tracing; soil surface measurement; soil assessment; soil erosion
Show Figures

Graphical abstract

MDPI and ACS Style

Epple, L.; Kaiser, A.; Schindewolf, M.; Bienert, A.; Lenz, J.; Eltner, A. A Review on the Possibilities and Challenges of Today’s Soil and Soil Surface Assessment Techniques in the Context of Process-Based Soil Erosion Models. Remote Sens. 2022, 14, 2468. https://doi.org/10.3390/rs14102468

AMA Style

Epple L, Kaiser A, Schindewolf M, Bienert A, Lenz J, Eltner A. A Review on the Possibilities and Challenges of Today’s Soil and Soil Surface Assessment Techniques in the Context of Process-Based Soil Erosion Models. Remote Sensing. 2022; 14(10):2468. https://doi.org/10.3390/rs14102468

Chicago/Turabian Style

Epple, Lea, Andreas Kaiser, Marcus Schindewolf, Anne Bienert, Jonas Lenz, and Anette Eltner. 2022. "A Review on the Possibilities and Challenges of Today’s Soil and Soil Surface Assessment Techniques in the Context of Process-Based Soil Erosion Models" Remote Sensing 14, no. 10: 2468. https://doi.org/10.3390/rs14102468

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop