The assessment of water-borne erosion at catchment level using GIS-based RUSLE and remote sensing: A review

Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors. Such factors vary over space and time, making the assessment of soil erosion even more difficult. Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rathe...

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Published inInternational Soil and Water Conservation Research Vol. 7; no. 1; pp. 27 - 46
Main Authors Phinzi, Kwanele, Ngetar, Njoya Silas
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.03.2019
KeAi Communications Co., Ltd
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Abstract Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors. Such factors vary over space and time, making the assessment of soil erosion even more difficult. Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors. RUSLE considers rainfall (R), topography (LS), soil erodibility (K), cover management (C), and support practice (P) as important factors affecting soil erosion. In the past few years, RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing. In this paper, an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided, placing an emphasis on related successes and challenges. This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges. Future research, however, must pay special attention to error assessment of remote sensing-derived RUSLE parameters.
AbstractList Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors. Such factors vary over space and time, making the assessment of soil erosion even more difficult. Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors. RUSLE considers rainfall (R), topography (LS), soil erodibility (K), cover management (C), and support practice (P) as important factors affecting soil erosion. In the past few years, RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing. In this paper, an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided, placing an emphasis on related successes and challenges. This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges. Future research, however, must pay special attention to error assessment of remote sensing-derived RUSLE parameters.
Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors. Such factors vary over space and time, making the assessment of soil erosion even more difficult. Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors. RUSLE considers rainfall (R), topography (LS), soil erodibility (K), cover management (C), and support practice (P) as important factors affecting soil erosion. In the past few years, RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing. In this paper, an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided, placing an emphasis on related successes and challenges. This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges. Future research, however, must pay special attention to error assessment of remote sensing-derived RUSLE parameters. Keywords: Soil erosion, Revised Universal Soil Loss Equation (RUSLE) parameters, Geographic Information System (GIS), Remote sensing
Author Phinzi, Kwanele
Ngetar, Njoya Silas
Author_xml – sequence: 1
  givenname: Kwanele
  surname: Phinzi
  fullname: Phinzi, Kwanele
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  givenname: Njoya Silas
  surname: Ngetar
  fullname: Ngetar, Njoya Silas
  email: njoya@ukzn.ac.za
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Issue 1
Keywords Soil erosion
Geographic Information System (GIS)
Revised Universal Soil Loss Equation (RUSLE) parameters
Remote sensing
Language English
License This is an open access article under the CC BY-NC-ND license.
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PublicationTitle International Soil and Water Conservation Research
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Snippet Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors. Such factors vary over space and time, making the...
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SubjectTerms erodibility
Geographic Information System (GIS)
geographic information systems
rain
Remote sensing
Revised Universal Soil Loss Equation
Revised Universal Soil Loss Equation (RUSLE) parameters
Soil erosion
space and time
topography
water conservation
watersheds
Title The assessment of water-borne erosion at catchment level using GIS-based RUSLE and remote sensing: A review
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