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Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley

Soil is a fundamental resource with its value vital to the world’s ecosystem. Due to the fact that soil is one of the bases of all terrestrial life, humans cannot survive without it. However, soil erosion has jeopardized soil sustainability and affected the environmental quality, leaving a bad impac...

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Autores principales: Nasir Ahmad, Nur Syabeera Begum, Mustafa, Firuza Begham, Muhammad Yusoff, Safiah Yusmah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119017/
https://www.ncbi.nlm.nih.gov/pubmed/37362990
http://dx.doi.org/10.1007/s10668-023-03251-8
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author Nasir Ahmad, Nur Syabeera Begum
Mustafa, Firuza Begham
Muhammad Yusoff, Safiah Yusmah
author_facet Nasir Ahmad, Nur Syabeera Begum
Mustafa, Firuza Begham
Muhammad Yusoff, Safiah Yusmah
author_sort Nasir Ahmad, Nur Syabeera Begum
collection PubMed
description Soil is a fundamental resource with its value vital to the world’s ecosystem. Due to the fact that soil is one of the bases of all terrestrial life, humans cannot survive without it. However, soil erosion has jeopardized soil sustainability and affected the environmental quality, leaving a bad impact if these issues were not tackled at an earlier phase. Many research has been done to predict soil erosion susceptibility areas using different methods. This research aims to classify the contributing factors of soil erosion according to the risk and generate a soil erosion risk prediction map in Cameron Highlands. Thus, this research focuses on a knowledge-driven method that uses Analytical Hierarchy Process (AHP) technique to achieve the objectives. This technique consists of weighing the factors adopted by comparing pairs of factors that control erosion in this area through experts' opinions. 15 factors have been chosen to build the prediction map. Result shows that rainfall erosivity is the main factor contributing to soil erosion in Cameron Highlands which is 0.110, followed by land use (0.095), slope steepness (0.089), soil texture (0.079), NDVI (0.079), TWI (0.072), slope length (0.065), slope aspect (0.064), slope altitude (0.062), SPI (0.061), lithology (0.060), slope curvature (0.054), drainage density (0.049), distance to road (0.029) and distance to stream (0.025). The west part of the study area was exposed to a high risk of soil erosion. This research will give the decision-makers, policymakers and planners insight into minimizing the soil erosion problem and suggest better precautions and solutions to overcome this severe environmental problem in the more advanced phase.
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spelling pubmed-101190172023-04-24 Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley Nasir Ahmad, Nur Syabeera Begum Mustafa, Firuza Begham Muhammad Yusoff, Safiah Yusmah Environ Dev Sustain Article Soil is a fundamental resource with its value vital to the world’s ecosystem. Due to the fact that soil is one of the bases of all terrestrial life, humans cannot survive without it. However, soil erosion has jeopardized soil sustainability and affected the environmental quality, leaving a bad impact if these issues were not tackled at an earlier phase. Many research has been done to predict soil erosion susceptibility areas using different methods. This research aims to classify the contributing factors of soil erosion according to the risk and generate a soil erosion risk prediction map in Cameron Highlands. Thus, this research focuses on a knowledge-driven method that uses Analytical Hierarchy Process (AHP) technique to achieve the objectives. This technique consists of weighing the factors adopted by comparing pairs of factors that control erosion in this area through experts' opinions. 15 factors have been chosen to build the prediction map. Result shows that rainfall erosivity is the main factor contributing to soil erosion in Cameron Highlands which is 0.110, followed by land use (0.095), slope steepness (0.089), soil texture (0.079), NDVI (0.079), TWI (0.072), slope length (0.065), slope aspect (0.064), slope altitude (0.062), SPI (0.061), lithology (0.060), slope curvature (0.054), drainage density (0.049), distance to road (0.029) and distance to stream (0.025). The west part of the study area was exposed to a high risk of soil erosion. This research will give the decision-makers, policymakers and planners insight into minimizing the soil erosion problem and suggest better precautions and solutions to overcome this severe environmental problem in the more advanced phase. Springer Netherlands 2023-04-21 /pmc/articles/PMC10119017/ /pubmed/37362990 http://dx.doi.org/10.1007/s10668-023-03251-8 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Nasir Ahmad, Nur Syabeera Begum
Mustafa, Firuza Begham
Muhammad Yusoff, Safiah Yusmah
Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley
title Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley
title_full Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley
title_fullStr Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley
title_full_unstemmed Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley
title_short Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia’s Steepland Agriculture Forested Valley
title_sort spatial prediction of soil erosion risk using knowledge-driven method in malaysia’s steepland agriculture forested valley
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119017/
https://www.ncbi.nlm.nih.gov/pubmed/37362990
http://dx.doi.org/10.1007/s10668-023-03251-8
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