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Land Use/Land Cover Identification from Landsat ETM+ Data Using Band Ratio in Atbara Area, Sudan
Current Issue
Volume 3, 2015
Issue 6 (December)
Pages: 243-248   |   Vol. 3, No. 6, December 2015   |   Follow on         
Paper in PDF Downloads: 34   Since Nov. 12, 2015 Views: 981   Since Nov. 12, 2015
Authors
[1]
Khalda Y. Ibrahim, Remote Sensing and Seismology Authority, National Center for Research, Khartoum, Sudan.
[2]
Insaf S. Babiker, Department of Geology, Faculty of Science, University of Khartoum, Khartoum, Sudan.
[3]
Abd Alhafiz G. El Mula, Department of Geology, Faculty of Science, University of Khartoum, Khartoum, Sudan.
[4]
Abu Elela A. Mohammed, National Institute of Astronomy and Geophysics, Cairo, Egypt.
Abstract
Land use/land cover analysis are becoming increasingly important as every decision making process requires complete description of the land surface. The main objective of this research is to qualitatively identify the land use/land cover of Atbara area, Sudan, based on Landsat ETM+ data. The band ratio technique was applied in order to present unique information that is not available in single bands. The resultant image was supposed to highlight differences between various land use/land cover classes in the study area. Several band ratios were created and two band ratio sets were assigned to the RGB of the color composite where the combined result of band ratios has allowed a better discrimination of land use/Land cover features. Twenty five ground truthing points were collected from the study area to confirm the identification of these features. Clearly, the processed images were able to highlight water bodies, vegetations, urban area and land where the highest concentration of vegetation was observed mainly along the banks of the river Nile and river Atbara. 95% of the ground truthing points were found to coincide with the previously identified land surface features. This indeed, represents the first step towards performing a successful supervised classification and generating Land use/Land cover maps.
Keywords
Vegetation, Cropland, Forest, Color Composite, Ground Truthing, River Nile, River Atbara
Reference
[1]
Arab Authority for Agricultural Investment and Development. 2006. Groundwater resources study. Atbara Fodder Project Hydromaster In. Interim report.
[2]
Avery, T. E., Berlin, G. L. 199. Fundamentals of Remote Sensing and Airphoto Interpretation. Macmillan, N Y. pp.433-436.
[3]
Berberoglu, S., Akin, A. 2009. Assessing different remotesensing techniques to detect land use/cove r changes in theeastern Mediterranean. International Journal of Applied Earth Observation and Geoinformation, 11, pp. 46–53.
[4]
Jensen, J. R. 1996. Introductory Digital image processing: are mote sensing perspective. 2nded. Prentice - hall Inc. New Jersey, USA.
[5]
Lillesand, T. M., Kiefer, R. W. 1994. Remote sensing and image interpretation. 3rd edition. - 750 pp., New York, N Y (Wiley).
[6]
Lu, D. and Wend, Q.2007. A Survey of Image Classification Methods and Techniques for Improving Classification Performance. International Journal of Remote Sensing, 28 (5), 823 - 870.
[7]
Mahbub Rahman, M. 2009. Identification of land use and land cover using band ratioingtechnique. Department of Geoscience. Murray State University (www.murray.).
[8]
Musick, B., Pelletier, R. E. 1986. Response of some thematicmapper band ratios tovariation in soil water content. Photogrammetric engineering and remote sensing. 52 (10):1661–1668.
[9]
Nelson, R.F. 1983. Detecting forest canopy change due to insectactivity using Landsat MSS. photogrammetric engineering and remote sensing. 49 (9): 1303-1314.
[10]
Osei, E. M., Zhou, Y. X. 2004. Land Cover Change detection in West Jilin using ETM+ images. Journal of Geoscientific Research in N. E. Asia, Vol. 7 (1), pp. 74-84.
[11]
Qu, S., Bao, W., Shi, P., Yu, Z., Li, P., Zhang, B., Jiang, P. 2012.Evaluation of Runoff Responses to Land Use Changes and Land Cover Changes in the Upper Huaihe River Basin, China. J. Hydrol. Eng. 2012.17: 800-806.
[12]
Saadat, H., Adamowski, J., Bonnell, R., Sharifi, F., Namdar, M., Ale - Ebrahim, S. 2011. Land Use and Land Cover Classification over a Large Area in Iran Based on Single Date Analysis of Satellite Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 66 (5):608–619.doi: 10.1016/j.isprsjprs.2011.04.001.
[13]
Sabins, F. F. 1996. Remote sensing Principles and interpretation. 3rd ed. San Francisco, Freeman. pp. 426.
[14]
Satterwhite, M. B. 1984. Discriminating vegetation and soils using Landsat MSS and thematic mapper bands and band ratios. Proceedings of American Society of Photogrammetry. 2: 479-485.
[15]
Singh, A. 1989. Digital change detection techniques using remotely sensed data. International journal of remote sensing. 10 (6): 989-1003.
[16]
Tehrany, M. S., Pradhan, B., Jebu, M. N. 2013a. A comparative assessment between object and pixel - based classification approaches for land use/land cover mapping using SPOT 5imagery. Geocar to Int. doi: 10.1080/10106049.2013.768300.
[17]
Todd, W. J.1977. Urban and regional land use change detected by using lands at data.
[18]
Yuan, F., Kali, E., Sawaya, A. 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, pp. 317-328.
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