Abstract
This paper is the first ever attempt to study population distribution in Al Ain city in Eastern United Arab Emirates (UAE) through integration of remote sensing and Geographic Information System (GIS). The remote sensing data used in this study included high spatial resolution (1 m) IKONOS imagery of February 17, 2001. For the population related studies IKONOS data offers number of advantages over other satellite images, e.g. it has high spatial resolution, it covers a larger area per image, it cost less per km2, and available on a more regular basis. Such characteristics provide a mechanism by which population estimates can be updated with high accuracy and better rate of frequency. The average difference between the population recorded in the 2001 and that estimated from IKONOS images for Al Ain city is found to be equal to 5%.
GIS is used for modelling the relationship among population variables and shows result obtained. Empirical model analyses results of this study show that the overall density of the city is consistent with location theories, i.e., declining population density from the Central Business District (CBD). The trend of higher-income people living in peripheries of cities is evident worldwide as it is in Al Ain.
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References
Adeniyi, P.O. (1983). An aerial photographic method for estimating urban population.Photogrammetric Engineering and Remote Sensing,49: 545–560.
Al Ain Master Plan (1986). Master plan for the region of Al Ain: Shankland Cox and SC Consultants Publications, London.
Baker, J.C., Kevin, O’Connell. M. and Williamson, R.A. (2001). Commercial observation satellites: At the leading edge of global transparency. RAND Publishers, Washington.
Batty, M. and Xie, Y. (1994). Urban analysis in GIS environment: Population density modelling using ARC/INFO. In: Fotheringham, A. S. and Rogerson, P.A. (eds.), Spatial analysis and GIS. Taylor & Francis, London, pp. 189–219.
Baudot, Y. (2001). Geographical analysis of the population of fast-growing cities in the Third World. In: Donnay, J.P., Barnsley, M.J. and Longley, P.A. (eds.), Remote sensing and urban analysis. Taylor and Francis, London, pp. 225–241.
Brugioni, D.A. (1983). The census: It can be done more accurately with space-age technology.Photogrammetric Engineering and Remote Sensing,49: 1337–1339.
Burgess, E.W. (1925). Growth of the City. In: Park, R.E., Burgess, E.W. and McKenzie, R.D., The City. University of Chicago Press, Chicago, pp. 47–62.
Carls, N. (1947). How to read aerial photographs for census work. U.S. Government Printing Office, Washington.
Clark, C. (1951). Urban population densities.J. of the Royal Statistical Society,114:490–496.
Donnay, J.P. (1992). Remotely sensed data contributions to GIS socioeconomic analysis.GIS Europe,1: 38- 41.
Donnay, J.P. (1999). Use of remote sensing information in planning. In: Stillwell, J., Geertman, S. and Openshaw, S.(eds.), Geographic Information and Planning, Springer, Berlin, pp. 242–260.
Donnay, J.P., Barnsley, M.J. and Longley, P.A. (2001). Remote sensing and urban analysis. In: Donnay, J.P. Barnsley, M.J. and Longley, P.A. (eds.), Remote sensing and urban analysis. Taylor and Francis, London, pp. 3–18.
Ehlers, M. (1995). The promise of remote sensing for land cover monitoring and modelling. Proceedings of the Joint European Conference on Geographic Information. AKM Messel AG, Basel, pp. 426–432.
Fakhru, N.A. (1998). Population growth and their place distribution variation in Qatar.J. of Humanities and Social Sciences,14(2): 169–203.
Forbes, J. (1984). Problems of cartographic representation of pattern of population change.Cartography J.,21(2): 93–102.
Gatrell, A. and Rowlingson, B. (1994). Spatial point process modelling in a GIS environment. In: Fotheringham, A.S. and P.A. Rogerson (eds.), Spatial analysis and GIS. Taylor & Francis, London, pp. 147–163.
Greene, D.L. and Barnbrock, J. (1978). A note on problems in estimating exponential urban density models.J. of Urban Economics,5: 285–290.
Harris, P.M. and Ventura, S.J. (1995). The integration of geographic data with remotely sensed imagery to improve classification in an urban area.Photogrammetric Engineering and Remote Sensing,61:993–998.
Hartl, P. and Cheng, F. (1995). Delimiting the buildings heights in a city from the shadow on a panchromatic SPOT-image: Part 2: Test of a complete city.International J. of Remote Sensing,16: 2829–2842.
Iisaka, J. and Hegedua, E. (1982). Population estimates from Landsat imagery.Remote Sensing of Environment,12: 259–272.
Kaid, O.A. and Mokhtar, B.M. (2001). Population distribution in Sultanate of Oman.Social Affairs,72(18): 67–102 (In Arabic).
Langford, M. and Unwin, D.J. (1994). Generating and mapping population density surfaces with a geographic information system.The Cartographical Journal,31: 2319–2336.
Lo, C.P. (1995). Automated population dwelling unit estimation from high-resolution satellite images: A GIS approach.International J. of Remote Sensing,16(1): 17–34.
Lo, C.P., and Chan, H.F. (1980). Rural Population estimation from aerial photographs.Photogrammetric Engineering and Remote Sensing,46: 337–345.
Lo, C.P. and Faber, B.J. (1997). Integration of Landsat Thematic Mapper and census data for quality of life assessment.Remote Sensing of Environment,62: 143–157.
Martin, D. (1989). Mapping population data from zone centroid locations.Transactions of the Institute of British Geographers,14(1): 90–97.
Mesev, T. (1998). The use of census data in urban image classification.Photogrammetric Engineering and Remote Sensing,64: 431 -438.
Rhind, D.W. (1991). Counting the people: the role of GIS. In: Maguire, D.J., Goodchild, M.F. and Rhind, D.W. (eds.), Geographical Information Systems: Principles and Applications. Longman, Harlow, pp. 127–137.
Sadler, G.J. and Barnsley, M.J. (1990). Use of population density data to improve classification accuracies in remotely-sensed images of urban areas. Proceedings of EGIS90. EGIS Foundation, Amsterdam, pp. 968- 977.
Space Imaging (2003). Space Imaging web site (http:// www.spaceimaging.com/products/ikonos/ index_2.htm). Accessed on 20 July, 2003.
Wang, F. (1999). Modeling China’s county-level population density distribution in 1990. In: Li. B.et al. (eds.), Geoinformatics and Socioinformatics, Proceedings of the Geoinformatics’ 99 held at Ann Arbor, Michigan from June 19-21, 1999, pp. 415–425.
Welch, R. (1982). Spatial resolution requirements for urban studies.International J. of Remote Sensing,3: 139–146.
Wilkinson, G.G. (1996). A review of current issues in the integration of GIS and remote sensing data.International J. of Geographical Information Systems,10: 85–101.
Zang, J. and Foody, GM. (1998). A fuzzy classification of sub-urban land cover from remotely sensed imagery.International J. of Remote Sensing,19: 2721–2238.
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Yagoub, M.M. Application of remote sensing and geographic information systems (gis) to population studies in the gulf: A case of al ain city (UAE). J Indian Soc Remote Sens 34, 7–21 (2006). https://doi.org/10.1007/BF02990743
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DOI: https://doi.org/10.1007/BF02990743