Land Use and Land Cover Changes of West Tahta Region, Sohag Governorate, Upper Egypt

Ismail Esam, Faid Abdalla, Niesner Erich

Department of Applied Geosciences and Geophysics, Montanuniversit?t Leoben, Leoben, Austria.
National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt.

DOI: 10.4236/jgis.2012.46053                

Abstract

Due to the growing of population in Egypt during the last few decades, great changes in agricultural area, and urbanization of Egypt art occurred. In this study we utilized the available record of multitemporal Land sat Thematic Mapper (Tm) and Egyptsat image to produce land cover/land use map of the area between 1987 and 2009. Also we used the post-classification change detection analysis to detect the change in the agriculture, urban areas and the change in the River Nile during the period between 1987 and 2009. The post-classification change detection analysis shows that agriculture development increased by 1785.96 Hectare through the study period with average annual rate of land reclamation 81.18 Hectare/year. While the urban area increased by 2231.24 Hectare with average annual rate 101.42 Hectare/ year the increase of the urbanization and the growth occurring through encroachment into the farmer old cultivated lands. The change in the River Nile is not so much is reached to 138.32 hectare in the study period with average annual rate 6.29 Hectare/year. The result of this study show that, the accuracy are quantify with the land cover changes and also delineate their spatial patterns, which display the efficiency of land sat in evaluating landscape dynamics over a particular time span. This data are very useful for natural resources management.

Keywords

Land Use; Land Cover; Remote Sensing; Change Detection

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Msrintranet.Capmas.gov.eg, “Central Agency for Population Mobilisation and Statistics—Population Clock,” 2011. http://www.msrintranet.capmas.gov.eg/pls/fdl/tst12e?action=&lname
[2]	T. H. Brikowski and A. M. Faid, “Pathline-Calibrated Groundwater Flow Models of Nile Valley Aquifers, Esna, Upper Egypt,” Journal of Hydrology, Vol. 324, No. 1-4, 2006, pp. 195-209. doi:10.1016/j.jhydrol.2005.10.011
[3]	Food and Agriculture Organization of the United Nations, “FAO Statistical Year Books 2005-2006, Issue 2,” Food and Agriculture Organization of the United Nations, Rome, 2006.
[4]	A. M. Abdulaziz, J. M. Hurtado and R. Al-Douri, “Application of Multitemporal Landsat Data to Monitor Land Cover Changes in the Eastern Nile Delta Region, Egypt,” International Journal of Remote Sensing, Vol. 30, No. 11, 2009, pp. 2977-2996. doi:10.1080/01431160802558675
[5]	J. R. G. Townshend, “Improved Global Data for Land Applications: A Proposal for a New High Resolution Data Set,” Report No. 20, International Geosphere-Biosphere Program, Stockholm, 1992.
[6]	R. S. DeFries and J. R. G. Townshend, “Global Land Cover: Comparison of Ground Based Data Sets to Classifications with AVHRR Data,” Wiley, Chichester, 1994.
[7]	J. E. Vogelmann, D. Helder, R. Morfitt, M. J. Choate, J. W. Merchant and H. Bulley, “Effect of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus Radiometric and Geometric Calibrations and Corrections on Landscape Characterization,” Remote Sensing of Environment, Vol. 78, No. 1-2, 2001, pp. 55-70. doi:10.1016/S0034-4257(01)00249-8
[8]	K. Green, D. Kempka and L. Lackey, “Using Remote Sensing to Detect and Monitor Land-Cover and Land-Use Change,” Photogrammetric Engineering and Remote Sensing, Vol. 60, No. 3, 1994, pp. 331-337.
[9]	P. T. Wolter, D. J. Mladenoff, G. E. Host and T. R. Crow, “Improved Forest Classification in the Northern Lake States Using Multitemporal Landsat Imagery,” Photogrammetric Engineering and Remote Sensing, Vol. 61, No. 9, 1995, pp. 1129-1143.
[10]	R. K. Kaufman and K. C. Seto, “Change Detection, Accuracy, and Bias in a Sequential Analysis of Landsat Imagery in the Pearl River Delta, China: Econometric Techniques,” Agriculture, Ecosystems and Environment, Vol. 85, No. 1-3, 2001, pp. 95-105. doi:10.1016/S0167-8809(01)00190-6
[11]	F. Yuan, K. E. Sawaya, B. C. Loeffelholz and M. E. Bauer, “Land Covers Classification and Change Analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat Remote Sensing,” Remote Sensing of Environment, Vol. 98, No. 2-3, 2005, pp. 317-328. doi:10.1016/j.rse.2005.08.006
[12]	L. Geosystems, “Leica Geosystems Geospatial Imaging ERDAS IMAGINE 9.2,” Leica Geosystems Geospatial Imaging, Norcross, 2008.
[13]	H. El-Sayed, “Environmental Investigation on Lake Maryut, West of Alexandria, Egypt: Geochemical, Geophysical and Remote Sensing Study,” M.Sc. Thesis, Alexandria University, Alexandria, 2010.
[14]	N. Levin, “Fundamentals of Remote Sensing,” 1st Hydrographic Data Management Course, IMO—International Maritime Academy, Trieste, 1999.
[15]	F. F. Sabins, “Remote Sensing, Principles and Interpretation,” Freeman, New York, 1997.
[16]	P. M. Harris and S. J. Ventura, “The Integration of Geographic Data with Remotely Sensed Imagery to Improve Classification in an Urban Area,” Photogrammetric Engineering and Remote Sensing, Vol. 61, No. 8, 1995, pp. 993-998.
[17]	J. R. Jensen, “Digital Change Detection,” In: Introductory Digital Image Processing—A Remote Sensing Perspective, Pearson Prentice Hall, Upper Saddle River, 2004, pp. 467-494.
[18]	G. Rosenfield and K. Fitzpatrick-Lins, “A Coefficient of Agreement as a Measure of Thematic Classification Accuracy,” Photogrammetric Engineering and Remote Sensing, Vol. 52, No. 2, 1986, pp. 223-227.
[19]	R. G. Congalton, “A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data,” Remote Sensing of Environment, Vol. 37, No. 1, 1991, pp. 35-46. doi:10.1016/0034-4257(91)90048-B
[20]	R. G. Congalton and K. Green, “Assessing the Accuracy of Remotely Sensed Data: Principles and Practices,” Lewis Publishers, Boca Raton, 1999.
[21]	M. Story and R. G. Congalton, “Accuracy Assessment: A User’s Perspective,” Photogrammetric Engineering and Remote Sensing, Vol. 52, No. 3, 1986, pp. 397-399.
[22]	T. M. Lillesand and R. W. Kiefer, “Remote Sensing and Image Interpretation,” 4th Edition, John Wiley & Sons, New York, 1994.
[23]	J. B. Campbell, “Introduction to Remote Sensing,” 3rd Edition, The Guilford Press, New York, 2002.
[24]	W. Hudson and C. Ramm, “Correct Formula of the Kappa Coefficient of Agreement,” Photogrammetric Engineering and Remote Sensing, Vol. 53, No. 4, 1987, pp. 421422.
[25]	J. R. Thomlinson, P. V. Bolstad and W. B. Cohen, “Coordinating Methodologies for Scaling Landcover Classifications from Site-Specific to Global: Steps toward Validating Global Map Products,” Remote Sensing of Environment, Vol. 70, No. 1, 1999, pp. 16-28.
[26]	J. R. Anderson, E. E. Hardy, J. T. Roach and R. E. Witmer, “A Land Use and Land Cover Classification System for Use with Remote Sensor Data—No. Professional Paper 964,” U.S. Geological Survey Washington, DC, 1976.
[27]	A. Shalaby and R. Tateishi, “Remote Sensing and GIS for Mapping and Monitoring Land Cover and Land-Use Changes in the Northwestern Coastal Zone of Egypt,” Applied Geography, Vol. 27, No. 1, 2007, pp. 28-41. doi:10.1016/j.apgeog.2006.09.004
[28]	M. Pax-Lenney, C. E. Woodcock, J. C. Collin and H. Hamdi, “The Status of Agriculture in Egypt: The Use of Multitemporal NDVI Features Derived from Landsat TM,” Remote Sensing of Environment, Vol. 56, No. 1, 1996, pp. 8-20. doi:10.1016/0034-4257(95)00152-2
[29]	A. M. Hay, “Sampling Designs to Test Land Use Map Accuracy,” Photogrammetric Engineering and Remote Sensing, Vol. 45, No. 4, 1979, pp. 529-533.
[30]	A. S. Goudie, “Land Transformation,“ In: R. J. Johnston, Ed., The Challenge for Geography, A Changing World, A Changing Discipline, Black Well, Cambridge, 1993, pp. 17-137.
[31]	R. M. Turner, “Long-Term Vegetation Change at a Fully Protected Sonoran Desert Site,” Ecology, Vol. 71, No. 2, 1990, pp. 464-477. doi:10.2307/1940301
[32]	G. Gutman, “Land Change Science,” In: Monitoring and Understanding Trajectories of Change on the Earth’s Surface, Kluwer Academic Publishers, Dordrecht, 2004, pp. 329-350.
[33]	COSPAR, International Council of Scientific Unions, “Potential of Remote Sensing for the Study of Global Change: COSPAR Report to the International Council of Scientific Unions (ICSU),” Pergamon Press, Oxford, 1987.
[34]	S. Ustin, “Manual of Remote Sensing: Remote Sensing for Natural Resource Management and Environmental Monitoring,” John Wiley and Sons, Chichester, 2004.
[35]	N. Bakr, D. C. Weindorf, M. H. Bahnassy, S. M. Marei and M. M. El-Badawi, “Monitoring Land Cover Changes in a Newly Reclaimed Area of Egypt Using Multi-Temporal Landsat Data,” Applied Geography, Vol. 30, No. 4, 2010, pp. 592-605. doi:10.1016/j.apgeog.2009.10.008
[36]	M. F. Abdalla and M. A. Abdulaziz, “Monitoring LandUse Change Associated Land Reclamation Using Multitemporal Landsat Data and Geoinformatics in Kom Ombo Area, South Egypt,” International Journal of Remote Sensing, 2011. (in Press)