Land cover change (LCC) is important to assess the land use/land cover changes with respect to the development activities like irrigation. The region selected for the study is Vaal Harts Irrigation Scheme (VHS) occupying an area of approximately 36, 325 hectares of irrigated land. The study was carried out using Land sat data of 1991, 2001, 2005 covering the area to assess the changes in land use/land cover for which supervised classification technique has been applied. The Normalized Difference Vegetation Index (NDVI) index was also done to assess vegetative change conditions during the period of investigation. By using the remote sensing images and with the support of GIS the spatial pattern of land use change of Vaal Harts Irrigation Scheme for 15 years was extracted and interpreted for the changes of scheme. Results showed that the spatial difference of land use change was obvious. The analysis reveals that 37.86% of additional land area has been brought under fallow land and thus less irrigation area (18.21%). There is an urgent need for management program to control the loss of irrigation land and therefore reclaim the damaged land in order to make the scheme more viable.
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 Brogaard, S., & Prieler, S. (1998). Land cover in the Horqin grasslands, North China. Detecting changes between 1975 and 1990 by means of remote sensing. Interim report IR-98-044/July on work of the International Institute for Applied System Analysis.
 DeFries, R., & Los, S.O. (1999). Implications of land-cover misclassifi cation for parameters estimates in global land-surface models: An example from the simple biosphere model (SiB2). Photogrammetric Engineering and Remote Sensing, 65, 1083-1088.
 Eastman, J.R., & Fulk, M.A. (1993). Time Series Analysis of Remotely Sensed Data Using Standardized Principal Components Analysis, Proceedings of 25th International Symposium on Remote Sensing and Global Environmental Change, Volume I. April, 4-8, Graz - Austria, 1485-1496.
 Eranani, M.Z., & Gabriels, D. (2006). Detection of land cover changes using Landsat MSS, TM, ETM+ sensors in YHazd-Ardakan basin. Iran: Proceedings of Agro Environ.
 Foody, G.M. (2002). Status of Land Cover Classifi cation Accuracy Assessment. Remote Sensing of Environment, 80, 185-201.
 Fung, T. (1990). An assessment of TM imagery for land cover change detection. IEEE Transactions on Geosciences and Remote Sensing, 28, 4, 681-684.
 Global Land Cover Facility (GLCF) of the University of Maryland, Maryland, USA www.glcf.umiacs. umd.edu accessed on 23rd Sept., 2011.
 Groten, S.M.E. (1993). NDVI - Crop monitoring and early yield assessment of Burkina Faso, International Journal of Remote Sensing. 14, 8, 1495-1515.
 Grove, B. (2006). Generalised whole-farm stochastic dynamic programming model to optimise agricultural water use. Report to the Water Research Commission, Pretoria.
 Jager, J.M. (1994). Accurarcy of vegetation evaporation formulae for estimating final wheat yield. Water SA, 20, 307-314.
 Latifovic, R., Fytas, K., Chen, J., & Paraszczak, J. (2005). Assessing land cover change resulting from large surface mining development. International Journal of Applied Earth Observation and Geoinformation. 7, 29-48.
 Li Rui, Yang Qinke, & Wen Zhongming, J. (2002a). Review of research on regional land use change and its environmental impacts. Bulletin of Soil and Water Conservation, 22, 2, 65-70.
 Ojo, O. I., Otieno, F.A.O., & Ochieng, G.M. (2009). Irrigation Problems and Research needs in South Africa: A review of Vaal Harts Irrigation Scheme. World Academy of Science, Engineering and Technology WCSET Conference, September 23-25, Amsterdam, Netherlands, 2009.
 Van Trinh, M., Duong, N.D., & Van Keulen, H. (2004). Using Landsat images for studying land use dynamics and soil degradation: Case study in Tamduong District, Vinhphuc Province, Vietnam, International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences, 2004.