Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia

Asirat Teshome Tolosa

doi:doi:10.11648/j.ijema.20180606.12

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Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia

Asirat Teshome Tolosa

Published in International Journal of Environmental Monitoring and Analysis (Volume 6, Issue 6)

Received: 30 November 2018 Accepted: 11 December 2018 Published: 2 January 2019

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Abstract

Soil erosion is one of the natural resources which can be influenced by Land use land cover change (LCC). The main influencing factor for land use land cover change is the increase of population, which in turn resulted in land degradation. This study aimed at modeling and analyzing LCC and its effect on soil erosion. The study was conducted in the highlands of, Blue Nile Basin, Ethiopia. Three Landsat images (1986, 2000 and 2016) were used to analyze the LCC. Supervised classification using maximum likelihood algorism was used to analyze the LCC. Four land cover types (LCTs) cropland, forest, and grassland and shrubland were defined. Multi-criteria decision analysis (MCE) using the Analytic Hierarchy Process (AHP) was used to prioritize the most influencing factor for soil erosion. Five major factors; land use, slope, soil types, Topographic Wetness Index (TWI) and altitude were considered to analyze the erosion hotspot area. The result showed that cropland and grassland increased from 41.6% and 15.4% in 1986 to 58.8% and 28.3% in 2016, respectively. However, shrub-land and forest decline from 32.3% and 10.6% in 1986 to 5.6% and 7.3% in 2016, respectively. The AHP analysis showed that LCT is the most contributors for erosion. It is observed that free grazing in the area is the common practice which is the main contributor to erosion. Hence, 50% of the gully erosion is influenced by LCT. The resultant erosion risk map shows that 1.12% of the area lies under the low-risk zone, whereas 19.02%, 72.67% and 7.2% of the total area fall in medium, high and very high-risk categories respectively. The results verified by field data collected and the judgment of the experts.

Published in	International Journal of Environmental Monitoring and Analysis (Volume 6, Issue 6)
DOI	10.11648/j.ijema.20180606.12
Page(s)	152-166
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

GIS, Landsat, Remote Sensing, Analytic Hierarchy Process, MCE, Supervised Classification

References

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APA Style

Asirat Teshome Tolosa. (2019). Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia. International Journal of Environmental Monitoring and Analysis, 6(6), 152-166. https://doi.org/10.11648/j.ijema.20180606.12

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ACS Style

Asirat Teshome Tolosa. Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia. Int. J. Environ. Monit. Anal. 2019, 6(6), 152-166. doi: 10.11648/j.ijema.20180606.12

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AMA Style

Asirat Teshome Tolosa. Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia. Int J Environ Monit Anal. 2019;6(6):152-166. doi: 10.11648/j.ijema.20180606.12

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@article{10.11648/j.ijema.20180606.12,
  author = {Asirat Teshome Tolosa},
  title = {Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {6},
  number = {6},
  pages = {152-166},
  doi = {10.11648/j.ijema.20180606.12},
  url = {https://doi.org/10.11648/j.ijema.20180606.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20180606.12},
  abstract = {Soil erosion is one of the natural resources which can be influenced by Land use land cover change (LCC). The main influencing factor for land use land cover change is the increase of population, which in turn resulted in land degradation. This study aimed at modeling and analyzing LCC and its effect on soil erosion. The study was conducted in the highlands of, Blue Nile Basin, Ethiopia. Three Landsat images (1986, 2000 and 2016) were used to analyze the LCC. Supervised classification using maximum likelihood algorism was used to analyze the LCC. Four land cover types (LCTs) cropland, forest, and grassland and shrubland were defined. Multi-criteria decision analysis (MCE) using the Analytic Hierarchy Process (AHP) was used to prioritize the most influencing factor for soil erosion. Five major factors; land use, slope, soil types, Topographic Wetness Index (TWI) and altitude were considered to analyze the erosion hotspot area. The result showed that cropland and grassland increased from 41.6% and 15.4% in 1986 to 58.8% and 28.3% in 2016, respectively. However, shrub-land and forest decline from 32.3% and 10.6% in 1986 to 5.6% and 7.3% in 2016, respectively. The AHP analysis showed that LCT is the most contributors for erosion. It is observed that free grazing in the area is the common practice which is the main contributor to erosion. Hence, 50% of the gully erosion is influenced by LCT. The resultant erosion risk map shows that 1.12% of the area lies under the low-risk zone, whereas 19.02%, 72.67% and 7.2% of the total area fall in medium, high and very high-risk categories respectively. The results verified by field data collected and the judgment of the experts.},
 year = {2019}
}

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TY - JOUR
T1 - Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia
AU - Asirat Teshome Tolosa
Y1 - 2019/01/02
PY - 2019
N1 - https://doi.org/10.11648/j.ijema.20180606.12
DO - 10.11648/j.ijema.20180606.12
T2 - International Journal of Environmental Monitoring and Analysis
JF - International Journal of Environmental Monitoring and Analysis
JO - International Journal of Environmental Monitoring and Analysis
SP - 152
EP - 166
PB - Science Publishing Group
SN - 2328-7667
UR - https://doi.org/10.11648/j.ijema.20180606.12
AB - Soil erosion is one of the natural resources which can be influenced by Land use land cover change (LCC). The main influencing factor for land use land cover change is the increase of population, which in turn resulted in land degradation. This study aimed at modeling and analyzing LCC and its effect on soil erosion. The study was conducted in the highlands of, Blue Nile Basin, Ethiopia. Three Landsat images (1986, 2000 and 2016) were used to analyze the LCC. Supervised classification using maximum likelihood algorism was used to analyze the LCC. Four land cover types (LCTs) cropland, forest, and grassland and shrubland were defined. Multi-criteria decision analysis (MCE) using the Analytic Hierarchy Process (AHP) was used to prioritize the most influencing factor for soil erosion. Five major factors; land use, slope, soil types, Topographic Wetness Index (TWI) and altitude were considered to analyze the erosion hotspot area. The result showed that cropland and grassland increased from 41.6% and 15.4% in 1986 to 58.8% and 28.3% in 2016, respectively. However, shrub-land and forest decline from 32.3% and 10.6% in 1986 to 5.6% and 7.3% in 2016, respectively. The AHP analysis showed that LCT is the most contributors for erosion. It is observed that free grazing in the area is the common practice which is the main contributor to erosion. Hence, 50% of the gully erosion is influenced by LCT. The resultant erosion risk map shows that 1.12% of the area lies under the low-risk zone, whereas 19.02%, 72.67% and 7.2% of the total area fall in medium, high and very high-risk categories respectively. The results verified by field data collected and the judgment of the experts.
VL - 6
IS - 6
ER -

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Author Information

Asirat Teshome Tolosa

Department of Hydraulic and Water Resources Engineering, Debre Tabor University, Debre Tabor, Ethiopia

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Asirat Teshome Tolosa. (2019). Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia. International Journal of Environmental Monitoring and Analysis, 6(6), 152-166. https://doi.org/10.11648/j.ijema.20180606.12

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ACS Style

Asirat Teshome Tolosa. Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia. Int. J. Environ. Monit. Anal. 2019, 6(6), 152-166. doi: 10.11648/j.ijema.20180606.12

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AMA Style

Asirat Teshome Tolosa. Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia. Int J Environ Monit Anal. 2019;6(6):152-166. doi: 10.11648/j.ijema.20180606.12

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@article{10.11648/j.ijema.20180606.12,
  author = {Asirat Teshome Tolosa},
  title = {Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {6},
  number = {6},
  pages = {152-166},
  doi = {10.11648/j.ijema.20180606.12},
  url = {https://doi.org/10.11648/j.ijema.20180606.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20180606.12},
  abstract = {Soil erosion is one of the natural resources which can be influenced by Land use land cover change (LCC). The main influencing factor for land use land cover change is the increase of population, which in turn resulted in land degradation. This study aimed at modeling and analyzing LCC and its effect on soil erosion. The study was conducted in the highlands of, Blue Nile Basin, Ethiopia. Three Landsat images (1986, 2000 and 2016) were used to analyze the LCC. Supervised classification using maximum likelihood algorism was used to analyze the LCC. Four land cover types (LCTs) cropland, forest, and grassland and shrubland were defined. Multi-criteria decision analysis (MCE) using the Analytic Hierarchy Process (AHP) was used to prioritize the most influencing factor for soil erosion. Five major factors; land use, slope, soil types, Topographic Wetness Index (TWI) and altitude were considered to analyze the erosion hotspot area. The result showed that cropland and grassland increased from 41.6% and 15.4% in 1986 to 58.8% and 28.3% in 2016, respectively. However, shrub-land and forest decline from 32.3% and 10.6% in 1986 to 5.6% and 7.3% in 2016, respectively. The AHP analysis showed that LCT is the most contributors for erosion. It is observed that free grazing in the area is the common practice which is the main contributor to erosion. Hence, 50% of the gully erosion is influenced by LCT. The resultant erosion risk map shows that 1.12% of the area lies under the low-risk zone, whereas 19.02%, 72.67% and 7.2% of the total area fall in medium, high and very high-risk categories respectively. The results verified by field data collected and the judgment of the experts.},
 year = {2019}
}

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