Research Article
BibTex RIS Cite
Year 2018, Volume: 5 Issue: 2, 104 - 113, 01.08.2018
https://doi.org/10.30897/ijegeo.354627

Abstract

References

  • Allen, J. and Lu, K. (2003): Modeling and Prediction of Future Urban Growth in the Charleston Region of South Carolina: a GIS- based Integrated Approach.
  • Bhatta, B. (2009): Analysis of urban growth pattern using remote sensing and GIS: a case study of Kolkata, India. International Journal of Remote Sensing, 30(18), 4733- 4746.
  • Brito, P. L. and Quintanilha, J.A. (2012): A Literature Review, 2001-2008, of classification methods and inner urban characteristics identified in multispectral remote sensing images. Paper presented at the proceedings of the 4th GEOBIA, Rio de Janeiro – Brazil.
  • Dihkan, M., Güneroğlu, N., Güneroğlu, A. and Karslı, F. (2017). The need for ecosystembased coastal planning in Trabzon city, IJEGEO, Vol.4(3): 193-205.
  • Burak, S., Doğan, E. and Gazioğlu, C. (2004). Impact of urbanization and tourism on coastal environment. Ocean and Coastal Management 47(9–10): 515–527.
  • Ding, H., Wang, R.-C., Wu, J.-P., Zhou, B., Shi, Z. and Ding, L.-X. (2007): Quantifying Land Use Change in Zhejiang Coastal Region, China Using Multi-Temporal Landsat TM/ETM+ Images. Pedosphere,17(6), 712-720. doi:10.1016/s1002- 0160(07) 60086-1
  • Ezeigbo,C.U (Eds),(1998): Principle and Applications of Geographic Information Systems (series in Surveying and Geoinformatics) Department of Surveying and Geoinformatics, Faculty of Engineering, University of Lagos. Panaf Press, Lagos, Nigeria, pp 90-104.
  • Guindon,B. and Zhang,Y(2009): Automated Urban Delineation from Landsat Imagery based on Spatial Information Processing, Photogrammetric Engineering & Remote Sensing, 75(7),845-858.
  • Huang, B., Zhang, L. and Wu, B. (2009): Spatiotemporal analysis of rural-urban land conversion. International Journal of Geographical Information Science, 23(3), 379-398. doi: 10.1080/13658810802119685
  • Islam,K., Jashimuddin, M.,.Nath, b., and Nath, K. (2016). Quantitative assessment of land cover change using landsat time series data: case of Chunati Wildlife Sanctuary (CWS), Bangladesh, IJEGEO, Vol. 3(2): 45-55
  • Osgouei, P. E. and Kaya, S. (2017). Analysis of land cover/use changes using Landsat 5 TM data and indices. Environmental Monitoring and Assessment, 189(4): 136-147.
  • Roberts, D. A. and Herold, M. (2004).Imaging spectrometry of urban materials, in King, P., Ramsey, M.S. and G. Swayze, (eds.), Infrared Spectroscopy in Geochemistry, Exploration and Remote Sensing, Mineral Association of Canada, Short Course Series., 33, 155-181.
  • Subair, A.O. (2006): Change detection in land use and land cover using remote sensing data and GIS( a case study of Ilorin and its environs in Kwara state).Department of of Geography, University of Ibadan, Oyo state, Nigeria.
  • UN (1999) .Africa a world of cities, UN World Urbanization Prospects. UN-Habitat (2008). Cities and Climate Adaptation. Seville, Spain.
  • UN-Habitat (2009).The State of African Cities 2008: A Framework for Addressing Urban Challenges in Africa: Renouf Publishing Company Limited.
  • UN-Habitat (2012). Cities and Climate Change: Global report on human settlements, 2011/United Nations Human settlements programme.
  • Zhou.,X.. and Wang,Y.C.(2011).Spatialtemporal dynamics of urban green space in response to rapid urbanization and greening policies. Landscape and urban planning, 100(3): 268-277.

Spatio-Temporal Urban Expansion Analysıs in a Growing City of Oyo Town ,Oyo State, Nigeria Using Remote Sensing And Geographic Information System (GIS) Tools

Year 2018, Volume: 5 Issue: 2, 104 - 113, 01.08.2018
https://doi.org/10.30897/ijegeo.354627

Abstract

The assessment of the land use / land cover expansion that occurred in
the area over a period of thirty years is the utmost priority of this research
work. Multi temporal Landsat satellite imageries TM 1984, 1990 and ETM+ 2002,
2014 from the United States Geological Survey (USGS) website were used as the
primary dataset. Area of interest was clipped in ArcGIS 9.3 environment, image
enhancement and image classification were adequately done using ENVI 4.5 remote
sensing software. Using supervised classification algorithm, the images were
classified into bare soil, built-up area, vegetation, water body and wetland;
these were then used to carry out change detection analysis or time series
analysis. Results obtained from the analysis of built-up area dynamics for the
past three decades revealed that the town has been undergoing urban expansion
processes. The expansion was prolonged both from urban centre to adjoining
non-built-up areas in all directions. The total built up area in the town has
expanded from 28.04sq/km in 1984 to 49.51 sq/km in 2014 at an average expansion
rate of 0.7, 0.4 and 0.9 per annum during 1984 – 1990, 1990 – 2002 and 2002 –
2014 study periods respectively. The study period from 2002 – 2014 was the time
at which the town experienced the highest urban expansion. The analysis of
spatial trend revealed that the urban landscape has experienced a process of
sprawling and fragmented development pattern particularly in the fringe areas
while the town centre underwent infill and edge expansion development
processes. The fringe areas show scattered expansion pattern. Quantifying urban
expansion patterns and development processes of the past trends can help better
understand the dynamics of built up area and guide sustainable urban
development planning of the future urban growth.

References

  • Allen, J. and Lu, K. (2003): Modeling and Prediction of Future Urban Growth in the Charleston Region of South Carolina: a GIS- based Integrated Approach.
  • Bhatta, B. (2009): Analysis of urban growth pattern using remote sensing and GIS: a case study of Kolkata, India. International Journal of Remote Sensing, 30(18), 4733- 4746.
  • Brito, P. L. and Quintanilha, J.A. (2012): A Literature Review, 2001-2008, of classification methods and inner urban characteristics identified in multispectral remote sensing images. Paper presented at the proceedings of the 4th GEOBIA, Rio de Janeiro – Brazil.
  • Dihkan, M., Güneroğlu, N., Güneroğlu, A. and Karslı, F. (2017). The need for ecosystembased coastal planning in Trabzon city, IJEGEO, Vol.4(3): 193-205.
  • Burak, S., Doğan, E. and Gazioğlu, C. (2004). Impact of urbanization and tourism on coastal environment. Ocean and Coastal Management 47(9–10): 515–527.
  • Ding, H., Wang, R.-C., Wu, J.-P., Zhou, B., Shi, Z. and Ding, L.-X. (2007): Quantifying Land Use Change in Zhejiang Coastal Region, China Using Multi-Temporal Landsat TM/ETM+ Images. Pedosphere,17(6), 712-720. doi:10.1016/s1002- 0160(07) 60086-1
  • Ezeigbo,C.U (Eds),(1998): Principle and Applications of Geographic Information Systems (series in Surveying and Geoinformatics) Department of Surveying and Geoinformatics, Faculty of Engineering, University of Lagos. Panaf Press, Lagos, Nigeria, pp 90-104.
  • Guindon,B. and Zhang,Y(2009): Automated Urban Delineation from Landsat Imagery based on Spatial Information Processing, Photogrammetric Engineering & Remote Sensing, 75(7),845-858.
  • Huang, B., Zhang, L. and Wu, B. (2009): Spatiotemporal analysis of rural-urban land conversion. International Journal of Geographical Information Science, 23(3), 379-398. doi: 10.1080/13658810802119685
  • Islam,K., Jashimuddin, M.,.Nath, b., and Nath, K. (2016). Quantitative assessment of land cover change using landsat time series data: case of Chunati Wildlife Sanctuary (CWS), Bangladesh, IJEGEO, Vol. 3(2): 45-55
  • Osgouei, P. E. and Kaya, S. (2017). Analysis of land cover/use changes using Landsat 5 TM data and indices. Environmental Monitoring and Assessment, 189(4): 136-147.
  • Roberts, D. A. and Herold, M. (2004).Imaging spectrometry of urban materials, in King, P., Ramsey, M.S. and G. Swayze, (eds.), Infrared Spectroscopy in Geochemistry, Exploration and Remote Sensing, Mineral Association of Canada, Short Course Series., 33, 155-181.
  • Subair, A.O. (2006): Change detection in land use and land cover using remote sensing data and GIS( a case study of Ilorin and its environs in Kwara state).Department of of Geography, University of Ibadan, Oyo state, Nigeria.
  • UN (1999) .Africa a world of cities, UN World Urbanization Prospects. UN-Habitat (2008). Cities and Climate Adaptation. Seville, Spain.
  • UN-Habitat (2009).The State of African Cities 2008: A Framework for Addressing Urban Challenges in Africa: Renouf Publishing Company Limited.
  • UN-Habitat (2012). Cities and Climate Change: Global report on human settlements, 2011/United Nations Human settlements programme.
  • Zhou.,X.. and Wang,Y.C.(2011).Spatialtemporal dynamics of urban green space in response to rapid urbanization and greening policies. Landscape and urban planning, 100(3): 268-277.
There are 17 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Rafiu Jimoh 0000-0002-2366-0736

Yusuf Afonja This is me

Christopher Albert This is me

N Amoo This is me

Publication Date August 1, 2018
Published in Issue Year 2018 Volume: 5 Issue: 2

Cite

APA Jimoh, R., Afonja, Y., Albert, C., Amoo, N. (2018). Spatio-Temporal Urban Expansion Analysıs in a Growing City of Oyo Town ,Oyo State, Nigeria Using Remote Sensing And Geographic Information System (GIS) Tools. International Journal of Environment and Geoinformatics, 5(2), 104-113. https://doi.org/10.30897/ijegeo.354627