Abstract
High rate of urbanization coupled with population growth has led to unexpected land use and land cover changes in Hilla city, which is located in the Babylon governorate of Iraq. Understanding and quantifying the spatiotemporal dynamics of the urban land use and land cover changes, as well as the driving factors behind them, are therefore vital in order to design appropriate policies and monitoring mechanisms to govern urban growth. This study analyzes land use and land cover changes over Hilla city through remote sensing and GIS (Geographical Information System) techniques. IKONOS satellite imagery from years 2000, 2005, and 2011 was collected and pre-processed using ENVI and ArcGIS, which then goes through an object-based supervised image classification stage to generate land use and land cover maps. The classification is performed using the statistical machine learning algorithm, SVM (Support Vector Machine). The confusion matrix and kappa coefficients are used to evaluate the overall accuracy of the results. The statistical results obtained enable assessment of class changes from years 2000 to 2011 and also identify the gain and loss of the built-up areas in relation to other land cover classes. The results also allow assessment of the spatial trend of these built-up areas. Ultimately, forecasts can be made to predict expected future class changes in 2026 and 2036. Generally, the results of this study show increased expansions of built-up areas, i.e., from 8.14% in 2000 to 14.53% in 2005 and up to 18.36% in 2011. All this was at the expense of bare land areas. Simultaneously, there was an increased expansion of vegetation/agricultural land area, specifically from 36.14% in 2000 to 41.71% in 2005 and 45.13% in 2011. The spatial trend also shows that the growth of built-up areas is focused in the southwestern part of Hilla city. In all, we foresee that the findings of this study can provide a good visual resource for decision-makers to perform more efficient urban planning.
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Abbreviations
- CSO:
-
Central Statistics Office
- QUAC:
-
Quick Atmospheric Correction
- GIS:
-
Geographic Information System
- HRSI:
-
High-resolution satellite imagery
- OBC:
-
Object-oriented classification
- RS:
-
Remote Sensing
- SVM:
-
Support Vector Machine
- UN:
-
United Nations
- UTM:
-
Universal Transverse Mercator
- WGS:
-
World Geodetic System
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Mahmoud, A.S., Kalantar, B., Al-Najjar, H.A.H., Moayedi, H., Halin, A.A., Mansor, S. (2021). Object-Oriented Approach for Urbanization Growth by Using Remote Sensing and GIS Techniques: A Case Study in Hilla City, Babylon Governorate, Iraq. In: Sharma, P. (eds) Geospatial Technology and Smart Cities. The Urban Book Series. Springer, Cham. https://doi.org/10.1007/978-3-030-71945-6_3
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