American Journal of Remote Sensing
Volume 3, Issue 3, June 2015, Pages: 37-42
Received: May 20, 2015;
Accepted: Jun. 7, 2015;
Published: Jun. 16, 2015
Views 5201 Downloads 150
Fakeye, Attah Motunrayo, Road Research Department, Nigerian Building and Road Research Institute, Ota, Ogun State, Nigeria
Aitsebaomo, Francis Omokekhai, Road Research Department, Nigerian Building and Road Research Institute, Ota, Ogun State, Nigeria
Osadebe, Charles Chuka, Road Research Department, Nigerian Building and Road Research Institute, Ota, Ogun State, Nigeria
Lamidi, Risikat Bukola, Road Research Department, Nigerian Building and Road Research Institute, Ota, Ogun State, Nigeria
Okonufua, Endurance Omamoke, Road Research Department, Nigerian Building and Road Research Institute, Ota, Ogun State, Nigeria
Landuse expansion, spatial and temporal variability of the area has been studied between 1986 and 2002 via statistical classification approaches based on the remotely sensed images obtained from Landsat Thematic Mapper (TM) and Extended Thematic Mapper (ETM+) sensors. Multi-temporal images, landuse/land cover changes were detected by means of remote sensing. From the result of supervised classification, the process of landuse/land cover changes and the model of expansion were analyzed by Geographic Information System (GIS) technologies. Seven cover classes were identified namely light vegetation, thick vegetation, swamp vegetation, settlement, sand dune, bare soil/erosional areas and water body. The confusion matrix showed a high overall classification accuracy of 77% and Ksat statistics of 71% for the classified map. Digital Elevation Model (DEM) of the area was created from digitized topographic contour lines at 1:50,000 scale. Additional information was derived from geologic and vegetation maps of the area to delineate spatial extent of landuse/land cover. Maps generated for these years were overlaid to obtain a change detection map showing the dynamic growth in land use changes for the two periods. Result also showed that during the study period from 1986 to 2002, the vegetation reduced from 47.7% to 14.4% in the study, more than double in 16 years, showing a strong trend of expansion of settlement as well as growth in baresoil area, perhaps due to sand mine or erosion. The research work shows that land use/land cover change detection using multi-temporal images by means of remote sensing and GIS modeling are good means of analyzing dynamic changes in time sequence.
Fakeye, Attah Motunrayo,
Aitsebaomo, Francis Omokekhai,
Osadebe, Charles Chuka,
Lamidi, Risikat Bukola,
Okonufua, Endurance Omamoke,
Digital Modeling of Land Use Changes in Some Parts of Eastern Nigeria, American Journal of Remote Sensing.
Vol. 3, No. 3,
2015, pp. 37-42.
Adediji, A., Jeje, L. K., & Ibitoye, M. O., Urban development and informal drainage pattern: Gully dynamics in Southwestern Nigeria. Applied Geography. 40, 90-102, 2013, http://dx.doi.org/10.1016/j.apgeog.2013.01.012
Ahmed, B. & Ahmed, R., Modeling urban land cover growth dynamics using multi-temporal satellite images. A case study of Dhaka, Bangladesh. ISPRS International Journal of Geo-information 1, 3-31, 2012, doi:10.3390/ijgi1010003.
Epstein, J., Payne, K. & Kramer, E., Techniques for mapping suburban sprawl. Photogrammetric, Engineering, Remote Sensing 63 (9), 913-918, 2002.
He, C., Okada, N., Zhang, Q., Shi, P., & Zhang, J., (2006): Modelling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China. Applied Geography. 26, 323-345, 2006, doi:10.1016/j.apgeog.2006.09.006.
He, C., Okada, N., Zhang, Q., Shi, P., & Li, J., Modeling dynamic urban expansion processes incorporating a potential model with cellular automata, Landscape Urban Planning 86, 79-91, 2008, doi:10.10/16/j.landurbplan.2007.12.010.
Igbokwe J. I., Gully Erosion mapping and monitoring in parts of south-eastern Nigeria, NASRDA News, Vol. 2. September 2004.
Jantz, C. A., & Goetz, S. J., Analysis of scale dependencies in an urban land-use change model. International Journal of Geographical Information Science, 19(2), 217–241, 2005.
Jeje, L. K., Urbanization and accelerated erosion: Examples from Southwestern Nigeria. Environmental Management Journal, 2, 1-17, 2005.
Jenerette, G. D., & Wu, J., Analysis and simulation of land-use change in the central Arizona–Phoenix region, USA. Landscape Ecology, 16, 611–626, 2001.
Jiang, Q., Monitoring and change analyzing of the temporal and spatial urban expansion pattern based on remote sensing. Beijing: Beijing Normal University, 2004.
Jianya, G., Haigang, S., Guorui, M. & Qiming, Z., A review of multi-temporal Remote Sensing data change detection algorithm. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 37, part B7, Beijing, 757 – 762, 2008.
Kocabas, V., & Dragicevic, S., Assessing cellular automata model behavior using a sensitivity analysis approach. Computers, Environment and Urban Systems, 30(6), 921–953, 2006.
Lal, R., Soil degradation by erosion. Land Degradation & Development, 12: 519 –539, 2001.
Lillesand, T. M., Keifer, R.W and Chipman, J.K., Remote sensing and image interpretation, John Wiley, New York. In Earth surface processes and landforms, Volume 26, Issue 12, pg. 1361, 2000.
Li, X. & Yeh, A. G., Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science, 16(4), 323–343, 2002.
Liu, H. & Zhou, Q., Accuracy analysis of remote sensing change detection by rule-based rationality evaluation with post-classification comparison. International Journal of Remote Sensing 25(5), pg. 1037-1050, 2004.
Liu H. & Zhou Q., Developing urban growth predictions from spatial indicators based on multi-temporal images. Computer, Environment and Urban Systems 29, pp. 580-594, 2005.
Mas, J.F., Perez-Vega, A. & Clarke, K.C., Assessing simulated landuse/cover maps using similarity and fragmentation indices. Ecological Complexity 11, 38-45, 2012, doi:10.1016/jecocom.2012.01.004.
Mundia, C.N. & Aniya, M., Analysis of land use/cover changes and urban expansion of Nairobi city using remote sensing and GIS. International Journal for Remote Sensing 26 (13), pg. 2831-2849, 2005.
Ofomata, G.E.K., Classification of soil erosion with specific reference to Anambra State of Nigeria, Environmental Review Vol. 3 No. 2, pp. 252-255, 2000.
Xu, J., Fox, J., Melick, D., Fujita, Y., Jintrawt, A., Qian J., Thomas, D. & Wyerhaeuser, H., Land use transition, livelihoods, and environmental services in montane mainland Southeast Asia. Mountain Research and Development, 26(3): 278-284, 2006.
Weber, C., Interaction model application for urban planning. Landscape Urban Plan. 63, pg. 49-60, 2003.
White, R., & Engelen, G., High resolution integrated modeling of the spatial dynamics of urban and regional systems. Computers, Environment and Urban Systems, 24, 383–400, 2000.
Wu, F., Calibration of stochastic cellular automata: The application to rural–urban land conversions. International Journal of Geographical Information Science, 16(8), 795–818, 2002.