Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya

Morris Barasa Waswa; Andrew Thiaine Imwati

doi:doi:10.11648/j.ajese.20190301.14

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Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya

Morris Barasa Waswa, Andrew Thiaine Imwati

Published in American Journal of Environmental Science and Engineering (Volume 3, Issue 1)

Received: 9 January 2019 Accepted: 11 February 2019 Published: 11 March 2019

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Abstract

Increase in population and the desire to seek new opportunities has contributed to urban growth, putting pressure on facilities in urban centres. Bungoma town, being the headquarter of Bungoma County has undergone radical changes in its physical form, not only in territorial expansion, but also through internal physical transformation. In the process of urbanization, physical characteristic of the town is gradually changing as cropland (agricultural land), vegetation and wetland has been converted to built-up areas. This new urban fabric needs to be analysed to understand the impact of these changes. The aim of this research was to evaluate the suitability of Bungoma town setting, model its growth and predict the future growth of the town based on land cover changes (1985-2015). Landsat satellite images were classified with five land cover classes followed by change detection. To simulate land cover map for Bungoma town in 2030, Markov Chain model and Cellular Automata Markov (CA-Markov) model were used. It was found that built-up area increased over the study period. The major contributors to this change are cropland, vegetation and wetland land cover types. The CA-Markov model results showed that 52% of the total study area will be converted into built-up area, 19% to cropland, 20% to vegetation, 5% to open spaces and 3% to wetland by 2030. This would have negative implication on food security in the region which is a major source of income for the inhabitants. There is need therefore for proper land use planning in the area. In addition, vertical urban development should be encouraged to control rapid expansion of the town.

Published in	American Journal of Environmental Science and Engineering (Volume 3, Issue 1)
DOI	10.11648/j.ajese.20190301.14
Page(s)	22-30
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

CA-Markov, Simulate, Suitability

References

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APA Style

Morris Barasa Waswa, Andrew Thiaine Imwati. (2019). Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya. American Journal of Environmental Science and Engineering, 3(1), 22-30. https://doi.org/10.11648/j.ajese.20190301.14

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ACS Style

Morris Barasa Waswa; Andrew Thiaine Imwati. Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya. Am. J. Environ. Sci. Eng. 2019, 3(1), 22-30. doi: 10.11648/j.ajese.20190301.14

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AMA Style

Morris Barasa Waswa, Andrew Thiaine Imwati. Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya. Am J Environ Sci Eng. 2019;3(1):22-30. doi: 10.11648/j.ajese.20190301.14

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@article{10.11648/j.ajese.20190301.14,
  author = {Morris Barasa Waswa and Andrew Thiaine Imwati},
  title = {Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya},
  journal = {American Journal of Environmental Science and Engineering},
  volume = {3},
  number = {1},
  pages = {22-30},
  doi = {10.11648/j.ajese.20190301.14},
  url = {https://doi.org/10.11648/j.ajese.20190301.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajese.20190301.14},
  abstract = {Increase in population and the desire to seek new opportunities has contributed to urban growth, putting pressure on facilities in urban centres. Bungoma town, being the headquarter of Bungoma County has undergone radical changes in its physical form, not only in territorial expansion, but also through internal physical transformation. In the process of urbanization, physical characteristic of the town is gradually changing as cropland (agricultural land), vegetation and wetland has been converted to built-up areas. This new urban fabric needs to be analysed to understand the impact of these changes. The aim of this research was to evaluate the suitability of Bungoma town setting, model its growth and predict the future growth of the town based on land cover changes (1985-2015). Landsat satellite images were classified with five land cover classes followed by change detection. To simulate land cover map for Bungoma town in 2030, Markov Chain model and Cellular Automata Markov (CA-Markov) model were used. It was found that built-up area increased over the study period. The major contributors to this change are cropland, vegetation and wetland land cover types. The CA-Markov model results showed that 52% of the total study area will be converted into built-up area, 19% to cropland, 20% to vegetation, 5% to open spaces and 3% to wetland by 2030. This would have negative implication on food security in the region which is a major source of income for the inhabitants. There is need therefore for proper land use planning in the area. In addition, vertical urban development should be encouraged to control rapid expansion of the town.},
 year = {2019}
}

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TY - JOUR
T1 - Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya
AU - Morris Barasa Waswa
AU - Andrew Thiaine Imwati
Y1 - 2019/03/11
PY - 2019
N1 - https://doi.org/10.11648/j.ajese.20190301.14
DO - 10.11648/j.ajese.20190301.14
T2 - American Journal of Environmental Science and Engineering
JF - American Journal of Environmental Science and Engineering
JO - American Journal of Environmental Science and Engineering
SP - 22
EP - 30
PB - Science Publishing Group
SN - 2578-7993
UR - https://doi.org/10.11648/j.ajese.20190301.14
AB - Increase in population and the desire to seek new opportunities has contributed to urban growth, putting pressure on facilities in urban centres. Bungoma town, being the headquarter of Bungoma County has undergone radical changes in its physical form, not only in territorial expansion, but also through internal physical transformation. In the process of urbanization, physical characteristic of the town is gradually changing as cropland (agricultural land), vegetation and wetland has been converted to built-up areas. This new urban fabric needs to be analysed to understand the impact of these changes. The aim of this research was to evaluate the suitability of Bungoma town setting, model its growth and predict the future growth of the town based on land cover changes (1985-2015). Landsat satellite images were classified with five land cover classes followed by change detection. To simulate land cover map for Bungoma town in 2030, Markov Chain model and Cellular Automata Markov (CA-Markov) model were used. It was found that built-up area increased over the study period. The major contributors to this change are cropland, vegetation and wetland land cover types. The CA-Markov model results showed that 52% of the total study area will be converted into built-up area, 19% to cropland, 20% to vegetation, 5% to open spaces and 3% to wetland by 2030. This would have negative implication on food security in the region which is a major source of income for the inhabitants. There is need therefore for proper land use planning in the area. In addition, vertical urban development should be encouraged to control rapid expansion of the town.
VL - 3
IS - 1
ER -

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Author Information

Morris Barasa Waswa

Department of Geomatic Engineering and Geospatial Information Systems, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Andrew Thiaine Imwati

Department of Geomatic Engineering and Geospatial Information Systems, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

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APA Style

Morris Barasa Waswa, Andrew Thiaine Imwati. (2019). Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya. American Journal of Environmental Science and Engineering, 3(1), 22-30. https://doi.org/10.11648/j.ajese.20190301.14

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ACS Style

Morris Barasa Waswa; Andrew Thiaine Imwati. Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya. Am. J. Environ. Sci. Eng. 2019, 3(1), 22-30. doi: 10.11648/j.ajese.20190301.14

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AMA Style

Morris Barasa Waswa, Andrew Thiaine Imwati. Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya. Am J Environ Sci Eng. 2019;3(1):22-30. doi: 10.11648/j.ajese.20190301.14

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@article{10.11648/j.ajese.20190301.14,
  author = {Morris Barasa Waswa and Andrew Thiaine Imwati},
  title = {Geographical Information System and Multi-criteria Based Cellular Automata Markov Model for Urban Growth and Analysis the Case Study of Bungoma Town Kenya},
  journal = {American Journal of Environmental Science and Engineering},
  volume = {3},
  number = {1},
  pages = {22-30},
  doi = {10.11648/j.ajese.20190301.14},
  url = {https://doi.org/10.11648/j.ajese.20190301.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajese.20190301.14},
  abstract = {Increase in population and the desire to seek new opportunities has contributed to urban growth, putting pressure on facilities in urban centres. Bungoma town, being the headquarter of Bungoma County has undergone radical changes in its physical form, not only in territorial expansion, but also through internal physical transformation. In the process of urbanization, physical characteristic of the town is gradually changing as cropland (agricultural land), vegetation and wetland has been converted to built-up areas. This new urban fabric needs to be analysed to understand the impact of these changes. The aim of this research was to evaluate the suitability of Bungoma town setting, model its growth and predict the future growth of the town based on land cover changes (1985-2015). Landsat satellite images were classified with five land cover classes followed by change detection. To simulate land cover map for Bungoma town in 2030, Markov Chain model and Cellular Automata Markov (CA-Markov) model were used. It was found that built-up area increased over the study period. The major contributors to this change are cropland, vegetation and wetland land cover types. The CA-Markov model results showed that 52% of the total study area will be converted into built-up area, 19% to cropland, 20% to vegetation, 5% to open spaces and 3% to wetland by 2030. This would have negative implication on food security in the region which is a major source of income for the inhabitants. There is need therefore for proper land use planning in the area. In addition, vertical urban development should be encouraged to control rapid expansion of the town.},
 year = {2019}
}

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