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Urban development change detection based on Multi-Temporal Satellite Images as a fast tracking approach—a case study of Ahwaz County, southwestern Iran

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Abstract

Rapid land-use/land-cover changes in suburbs of metropolitan cities of Iran have recently caused serious environmental damages. Detection of these changes can be a very important step in urban planning and optimal use of natural resources. Accordingly, the present study was carried out to track land-use/land-cover (LULC) changes of Ahwaz County in southwestern Iran using remote sensing techniques over a period of 26 years, from 1987 to 2013. For this, ISODATA algorithm and Maximum Likelihood were initially used for unsupervised and supervised classifications of the satellite images. The accuracy of the LULC maps was checked by the Kappa Coefficient and the Overall Accuracy methods. As the final step, the LULC changes were detected using the cross-tabulation technique. The obtained results indicated that urban and agricultural areas have been increased about 57.5 and 84.5 %, respectively, from 1987 to 2013. Further, the area of poorly vegetated regions, in the same period, has been decreased to approximately 36 %. The largest land conversion area belongs to the poorly vegetated regions, which have been declined to about 10,371 and 1,334 ha during 1987–2007 and 2007–2013, respectively. Approximately 1,670 and 382 ha of the agricultural lands have also been changed to built-up areas by about 1,670 and 382 ha during the same periods. As a result, it was found that the northwest, southwest, and south of the county were highly subjected to urban development. This would be of great importance for urban planning decision-making faced by the planners of the city in the present and future.

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References

  • Abdulaziz, A. M., Hurtado, J. J. M., & Al-Douri, R. (2009). Application of multi-temporal Landsat data to monitor land cover changes in the Eastern Nile Delta Region, Egypt. International Journal of Remote Sensing, 30(11), 2977–2996.

    Article  Google Scholar 

  • Abdullah, S., & Nakagoshi, N. (2006). Changes in landscape spatial pattern in the highly developing State of Selangor, Peninsular Malaysia. Landscape and Urban Planning, 77(3), 263–275.

    Article  Google Scholar 

  • Alberti, M., Weeks, R., & Coe, S. (2004). Urban land-cover change analysis in Central Puget Sound. Photogrammetric Engineering & Remote Sensing, 70(9), 1043–1052.

    Article  Google Scholar 

  • Anderson, J. R., Hardy, E. E., Roach, J. T., & Witmer, R. E. (1976). A land use and land cover classification system for use with remote sensor data. United States Department of the Interior. Washington: United States Government Printing Office.

    Google Scholar 

  • Borri, D., Caprioli, M., & Tarantino , E. (2004). Spatial information extraction from VHR satellite data to detect land cover transformations. Proceedings of International Workshop on “Processing and Visualization using High-Resolution Imagery”. Vol. XXXVI, Part5/W1. Pitsanulok, Thailand: International Society for Photogrammetry and Remote Sensing (ISPRS).

  • Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., & Lambin, E. (2004). Digital change detection methods in ecosystem monitoring: a review. International Journal of Remote Sensing, 25(9), 1565–1596.

    Article  Google Scholar 

  • Deng, J. S., Wang, K., Hong, Y., & Qi, J. G. (2009). Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and Urban Planning, 92(3–4), 187–198.

    Article  Google Scholar 

  • Dewan, A. M., & Yamaguchi, Y. (2009). Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka metropolitan of Bangladesh during 1960–2005. Environmental Monitoring and Assessment, 150(1–4), 237–249.

    Article  Google Scholar 

  • Dewidar, K. M. (2004). Detection of land use land cover changes for the Northern Part of the Nile Delta (Burullus region), Egypt. International Journal of Remote Sensing, 25(20), 4079–4089.

    Article  Google Scholar 

  • Fan, F., Weng, Q., & Wang, Y. (2007). Land use and land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery. Sensors, 7(7), 1323–1342.

    Article  Google Scholar 

  • FAO. (2009). A temporary method to evaluate and prepare desertification map. (M. A. Meshkat, Trans.). Tehran: Research Institute of Forests and Rangelands (RIFR).

    Google Scholar 

  • Ikiel, C., Ustaoglu, B., Dutucu, A. A., & Kilic, D. E. (2013). Remote sensing and GIS-based integrated analysis of land cover change in Duzce Plain and its surroundings (North Western Turkey). Environmental Monitoring and Assessment, 185(2), 1699–1709.

    Article  Google Scholar 

  • Jensen, J. R. (2004). Introductory digital image processing: a remote sensing perspective (3rd ed.). Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Kamusoko, C., & Aniya, M. (2007). Land use/cover change and landscape fragmentation analysis in the Bindura District, Zimbabwe. Land Degradation & Development, 18(2), 221–233.

    Article  Google Scholar 

  • Lillesand, T., Kiefer, R. W., & Chipma, J. (2008). Remote sensing and image interpretation (6th ed.). New York: Wiley.

    Google Scholar 

  • Loveland, T. R., & DeFries, R. (2004). Observing and monitoring land use and land cover change. Ecosystems and Land Use Change, Geophysical Monograph Series, 153, 231–246.

    Article  Google Scholar 

  • Lu, D., Mausel, P., Brondizio, E., & Moran, E. (2004). Change detection techniques. International Journal of Remote Sensing, 25(12), 2365–2407.

    Article  Google Scholar 

  • Lunetta, R. S., Ediriwickrema, J., Johnson, D. M., Lyon, J. G., & McKerrow, A. (2002). Impacts of vegetation dynamics on the identification of land-cover change in a biologically complex community in North Carolina, USA. Remote Sensing of Environment, 82(2–3), 258–270.

    Article  Google Scholar 

  • Manandhar, R., Odeh, I. O., & Pontius, R. G. (2010). Analysis of twenty years of categorical land transitions in the Lower Hunter of New South Wales, Australia. Agriculture, Ecosystems & Environment, 135(4), 336–346.

    Article  Google Scholar 

  • Mas, J. F. (1999). Monitoring land-cover changes: a comparison of change detection techniques. International Journal of Remote Sensing, 20(1), 139–152.

    Article  Google Scholar 

  • MRUD. (2008). The master plan of Ahwaz County. Tehran: Ministry of Roads and Urban Development (MRUD).

    Google Scholar 

  • Mundia, C. N., & Aniya, M. (2005). Analysis of land use/cover changes and urban expansion of Nairobi City using remote sensing and GIS. International Journal of Remote Sensing, 26(13), 2831–2849.

    Article  Google Scholar 

  • Norman, L. M., Feller, M., & Guertin, D. P. (2009). Forecasting urban growth across the United States-Mexico border. Computers, Environment and Urban Systems, 33(2), 150–159.

    Article  Google Scholar 

  • Schlerf, M., Borens, S., Seeling, S., & Hill, J. (2007). Land use and land cover change analysis in Rhineland-Palatinate based on multi-temporal image classification. Mitteilungen aus der Forschungsanstalt fur Waldokologie und Forstwirtschaft Rheinland-Pfalz, pp., 237–245.

  • SCI. (2012). Statistical yearbook of Khuzestan Province.. Tehran: Statistical Center of Iran (SCI).

    Google Scholar 

  • Singh, A. (1989). Digital change detection techniques using remotely sensed data. International Journal of Remote Sensing, 10(6), 989–1003.

    Article  Google Scholar 

  • Sun, Z., Rui, M., & YanXin, W. (2009). Using Landsat data to determine land use changes in Datong Basin, China. Environmental Geology, 57(8), 1825–1837.

    Article  Google Scholar 

  • Versace, V. L., Ierodiaconou, D., Stagnitti, F., & Hamilton, A. J. (2008). Appraisal of random and systematic land cover transitions for regional water balance and revegetation strategies. Agriculture, Ecosystems & Environment, 123(4), 328–336.

    Article  Google Scholar 

  • Warner, T. A., & Campagna, D. J. (2009). Remote sensing with IDRISI Taiga: a beginner’s guide. Hong Kong: Geocarto International Centre.

    Google Scholar 

  • Weng, Q. (2009). Remote sensing and GIS integration: theories, methods, and applications (1st ed.). New York: McGraw-Hill Professional.

    Google Scholar 

  • Yang, X., & Lo, C. (2002). Using satellite imagery to detect land-use/land-cover changes in Atlanta, Georgia Metropolitan Area. International Journal of Remote Sensing, 23(9), 1775–1798.

    Article  Google Scholar 

  • Yin, J., Yin, Z., Zhong, H., Xu, S., Hu, X., Wang, J., et al. (2011). Monitoring urban expansion and land-use/land-cover changes of Shanghai metropolitan area during the transitional economy (1979–2009) in China. Environmental Monitoring and Assessment, 177(1–4), 609–621.

    Article  Google Scholar 

  • Yuan, D., & Elvidge, C. (1998). NALC land cover change detection pilot study: Washington D.C. area experiments. Remote Sensing of Environment, 66(2), 166–178.

    Article  Google Scholar 

  • Yuan, F., Sawaya, K. E., Loeffelholz, B. C., & Bauer, M. E. (2005). Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multi-temporal Landsat remote sensing. Remote Sensing of Environment, 98(2–3), 317–328.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Maryam Malmir

  2. Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Mir Masoud Kheirkhah Zarkesh

  3. Department of Land-use Planning and Assessment, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Seyed Masoud Monavari

  4. Department of Environment, North Tehran Branch, Islamic Azad University, Tehran, Iran

    Seyed Ali Jozi

  5. Soil Conservation and Watershed Management Research Institute, Karaj, Iran

    Esmail Sharifi

Authors
  1. Maryam Malmir
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  2. Mir Masoud Kheirkhah Zarkesh
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  3. Seyed Masoud Monavari
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  4. Seyed Ali Jozi
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  5. Esmail Sharifi
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Corresponding author

Correspondence to Maryam Malmir.

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Malmir, M., Zarkesh, M.M.K., Monavari, S.M. et al. Urban development change detection based on Multi-Temporal Satellite Images as a fast tracking approach—a case study of Ahwaz County, southwestern Iran. Environ Monit Assess 187, 108 (2015). https://doi.org/10.1007/s10661-015-4295-y

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