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Civil-Comp Conferences
ISSN 2753-3239 CCC: 6
PROCEEDINGS OF THE SEVENTEENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING Edited by: P. Ivanyi, J. Kruis and B.H.V. Topping
Paper 15.3
The Use and Application of GIS and Remote Sensing Techniques for Monitoring Urban Growth in Koya City, Iraq-Kurdistan Region Z.F. Ali1, Y. Abduljaleel2, G. Pirisi3, A. Salem1,4, M. Amiri5 and A. Awad6
1Doctoral School of Earth Sciences, University of Pécs, Hungary
Z.F. Ali, Y. Abduljaleel, G. Pirisi, A. Salem, M. Amiri, A. Awad, "The Use and Application of GIS and Remote Sensing Techniques for Monitoring Urban Growth in Koya City, Iraq-Kurdistan Region", in P. Ivanyi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Seventeenth International Conference on
Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 6, Paper 15.3, 2023, doi:10.4203/ccc.6.15.3
Keywords: urbanization, remote sensing, geographic information system, land-use changes, land-cover changes, Iraqi Kurdistan region.
Abstract
Nowadays, rapid urban growth and urbanization is continuing to be one of the most
important problems of global change, especially in developing countries. This process
is most visible and powerful and has a key role in urban land-use and land-cover
changes and landscape pattern changes around the world. Remote sensing and
geographic information system are a reliable source to understand and quantify urban
expansion. This study uses Landsat 5 TM imagery associated with GIS techniques to
monitor urban growth in Koya city in the North Iraqi Kurdistan region between 1990,
2000, and 2010. The ERDAS 9.2 imagine software was applied to measure and
display land use classes changing utilizing supervised classification of maximum
likelihood. The outcomes demonstrate that the land-cover classes faced great changes
between 1990 and 2010. For instance, the built-up area increased dramatically from
279.9 hectares in 1990 to 992.79 hectares in 2010; whereas the rate of vegetation cover
decreased dramatically from 2,199.87 hectares to 576.09 hectares in 2010. This was
due to environmental change and socio-economic and political factors. Total accuracy
assessments of all images show that the image classification process was very
accurate, with overall accuracy greater than 95%.
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