Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]

Soil erosion probability maps were produced under various case scenarios by accounting for uncertainties in the data and in the decision rule, using the Universal Soil Loss Equation (USLE), remote sensing and geographical information systems (GIS). This objective was realized by applying the Bayesia...

Full description

Bibliographic Details
Published in:Hydrological Sciences Journal
Main Author: Baban S.M.J.; Yusof K.W.
Format: Article
Language:English
Published: 2001
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035312275&doi=10.1080%2f02626660109492815&partnerID=40&md5=3f5912934f516b32da74eae39ae74dfc
id 2-s2.0-0035312275
spelling 2-s2.0-0035312275
Baban S.M.J.; Yusof K.W.
Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
2001
Hydrological Sciences Journal
46
2
10.1080/02626660109492815
https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035312275&doi=10.1080%2f02626660109492815&partnerID=40&md5=3f5912934f516b32da74eae39ae74dfc
Soil erosion probability maps were produced under various case scenarios by accounting for uncertainties in the data and in the decision rule, using the Universal Soil Loss Equation (USLE), remote sensing and geographical information systems (GIS). This objective was realized by applying the Bayesian Probability Theory within IDRISI, a raster based GIS. The outcomes were two continuous probability soil erosion maps ranging from zero to 1. Comparing these maps with an earlier study indicates that accounting for the uncertainties has, in general, decreased the probability of soil erosion. Based on average readings for specific sites on the maps, increases in erosion risk under the second case scenario have had the highest impact on the highlands that is in the central, eastern, and northern regions of Langkawi Island, Malaysia. Assuming a 10% risk, this impact has increased by 11.98, 11.83 and 5.741% for high, medium and low soil erosion risk areas on the island respectively. © 2001 Taylor & Francis Group, LLC.

2626667
English
Article

author Baban S.M.J.; Yusof K.W.
spellingShingle Baban S.M.J.; Yusof K.W.
Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
author_facet Baban S.M.J.; Yusof K.W.
author_sort Baban S.M.J.; Yusof K.W.
title Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
title_short Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
title_full Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
title_fullStr Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
title_full_unstemmed Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
title_sort Modelling soil erosion in tropical environments using remote sensing and geographical information systems; [Modélisation de l'érosion des sols dans un environnement tropical utilisant la télédétection et les SIG]
publishDate 2001
container_title Hydrological Sciences Journal
container_volume 46
container_issue 2
doi_str_mv 10.1080/02626660109492815
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035312275&doi=10.1080%2f02626660109492815&partnerID=40&md5=3f5912934f516b32da74eae39ae74dfc
description Soil erosion probability maps were produced under various case scenarios by accounting for uncertainties in the data and in the decision rule, using the Universal Soil Loss Equation (USLE), remote sensing and geographical information systems (GIS). This objective was realized by applying the Bayesian Probability Theory within IDRISI, a raster based GIS. The outcomes were two continuous probability soil erosion maps ranging from zero to 1. Comparing these maps with an earlier study indicates that accounting for the uncertainties has, in general, decreased the probability of soil erosion. Based on average readings for specific sites on the maps, increases in erosion risk under the second case scenario have had the highest impact on the highlands that is in the central, eastern, and northern regions of Langkawi Island, Malaysia. Assuming a 10% risk, this impact has increased by 11.98, 11.83 and 5.741% for high, medium and low soil erosion risk areas on the island respectively. © 2001 Taylor & Francis Group, LLC.
publisher
issn 2626667
language English
format Article
accesstype
record_format scopus
collection Scopus
_version_ 1818940564411777024