eng Science and Education Publishing American Journal of Environmental Protection 2328-7233 2013-11-20 1 4 112 119 10.12691/env-1-4-7 ENV2013147 article Ndabula C. 1 Averik P. D. 2 Jidauna G.G. gjidauna@fudutsinma.edu.ng 2 Abaje I. 2 Oyatayo T. K. 3 E. O Iguisi 4 Department of Geography and Regional Planning, faculty of Arts Management and Social Sciences, Federal University Dutsinma, Katsina State, Nigeria Department of Geography and Environmental Management, University of Port-Harcourt, Rivers State, Nigeria Department of Geography, College of Natural & Applied science, Kwararafa University Wukari, Taraba State, Nigeria Department of Geography, Ahmadu Bello University, Zaria, Kaduna State, Nigeria This study in addition to the conventional monitoring and mapping of Landuse/Landcover Changes (LULCC), also has as its major objective to quantitatively analyse the spatio-temporal dynamics of these LULCC structures or patterns using five (5) quantitative indices; Normalized Vegetation Difference Index (NDVI), Landuse/Landcover (LULC) Change Intensity Index (Ti), Dynamic Index (Ki), Integrated Index (Ld), and Rate of Change (Ai). These indices critically analyse the extent, rate, as well as the magnitude of change among various LULC in the study area, which provides a basis for comparisons with other places and to better explain the nature of spatio-temporal dynamics of LULC as an Index of land degradation. The NDVI on the one hand allows analysis of these LULCC in terms of change in quantity of vegetation cover or bareness of the land surface, while the other four indices on the other hand expressed the intensity with which the land surface is subjected to human activities. The methodology of RS/GIS was used for LULC mapping and NDVI analysis using multi-temporal satellite data sets. Results showed significant dynamics amongst the various LULC in both space and time with implication of decreasing vegetation cover and increasing bare surfaces and hence land degradation processes. Forest has the highest Change Intensity Index (Ti) of 5.75% followed by Built-up 4.08%, and similarly the highest contribution rates (Ai) of 49 and 35% respectively. Built-up has the highest Dynamic Index (Ki) of 2.29% followed by Floodplain Agricultural area 1.92%. Statistical analysis using different regression models as found applicable was performed to observe the trend in LULC change patterns. http://pubs.sciepub.com/env/1/4/7/env-1-4-7.pdf Keywords: analysisLanduse/Landcoverspatio-temporalindicesstructures