Cursos De Formación.

38 Research works were reviewed and effort was made to identify methods and procedures used by researchers and identify gaps in literature.

The reviewed literatures cover aspects of landcover / landuse change, monitoring and prediction of urban growth, application of growth models in monitoring and forecasting urban growth and development.

39 The future prediction analysis was performed using Idrisi Land Change Modeler algorithm which runs on the multi-layer perception neural network and Markov chain modeling.

The results of 10 years future prediction for the study area, based on urban growth trends between 2000 and 2006 indicated that the spatial extend of urban growth was 2,220 hectares.

Given the current trends of urban growth and results of the future simulation, it was recommended that the Lagos State government take urgent measures to mitigate the occurrence of this trend in the study area.

Adebayo (2007) in their study, noted that the recent upsurge in urban growth and decentralization of economic activities has made urban fringe a topical issues in both local and international debates, however, the problem once visible in the city center has moved to the suburbs due to globalization forces that culminated into mega city development.

There were lots of transformations in the urban fringe landscape in the last two decades making it highly vulnerable to risks, as much as expected of the city itself owing to large agglomeration of people and economic activities in this area. Lack of dependable institutions and absence of government has caused problems on jurisdictional administration of these urban hinterlands. The border line between urban and rural landscape is called the urban fringe.

Often times, a conflict zone with neither rural nor urban features, lying outside the corporate existence of the city. Because of proximity to the city, it experiences much of urbanization processes and serves as buffer for urban development. One-prominent force that shape urban fringe landscape in the developing countries is the informal sector activities, and these constitute about 65% of the urban economy. Informal sector response to the failure of urban governance has various dimensions. Notable among them, are the uncoordinated

40 residential development, emergent transition in demographic re-agglomeration different form the hitherto initial population and restructuring of economic activities at the fringe areas.

This research workwas a part of a larger ongoing study on urban fringe structural characteristic in developing countries and indeed, Ibadan-Nigeria in particular. It therefore, exposed ways toward mainstreaming risk reduction and vulnerability in the area.

It also examined the attendant role of informal sector activities in shaping the urban fringe environment and impact of globalization forces on the urban fringe local landscape with a view to fill the gaps in the areas of urban policy development, governance and planning in developing countries.

Adewale, et al., (2014) examined the growth pattern of settlements in Oke-Ogun area of Oyo State, Nigeria between 1984 and 2011; and predicted the future growth pattern of settlements in the study area. Both primary and secondary data were used for this study.

Primary sources of data included Global Positioning System (GPS), Landsat TM and ETM+ imageries of 1984, 1990, 2000, and 2011. Secondary data included administrative map and population data of the study area. Descriptive statistics and geospatial technique were used to analyze the data collected.

Their results showed a random pattern of settlement distribution in the study area. Results revealed that settlements covered about 0.52% of the total land area in 1984; 1.32% in 2000; and 3.78% in 2011. Whereas linear pattern of growth characterized the periods between 1984 and 1990; clustering, infilling, and fringes were the patterns of growth that characterized the periods between 1990 and 2011.

They predicted that, at an average 1.2% of annual growth rate, settlements will occupy about 44.37% of the total land area by 2031. The study concluded that settlements in the study

41 area varied in the patterns of distribution; the area was dominated by indigenous settlements type with overconcentration of social and economic infrastructures in few centers.

Aniekan, et al, (2012) explored the implementation of a loosely coupled logistic regression model and geographic information systems in modeling and predicting future urban expansion of Lagos from historical remote sensing data (Landsat TM images of Lagos acquired on 1984, 2000 and 2005). ArcGIS and MATLAB software were used for the modeling.

Three Landsat images were classified using the k-means unsupervised algorithm in MATLAB. Ten salient explanatory landuse variables were extracted for the calibration of the model. The model was calibrated by running a simulation for period 1984 to 2000. The computed logistic coefficients of the 10 explanatory variables showed that all the 10 explanatory variables are significant at 95% confidence level based on a two-tailed test, since all the 10 variables yields p-values <0.05.

The simulated map in 2000 was compared with the reference data in 2000; and evaluated using the Kappa statistic. The computed Kappa statistic was 0.7640; which implied a substantial agreement between the predicted and the reference data. The calibration model for 1984-2000 was used to predict 2005 map. A comparison of the predicted and reference data in 2005 yielded Kappa statistics estimate of 0.6998; which indicated a substantial agreement between the predicted and the reference data. A prediction of 2030 was derived upon satisfactory result obtained for the 2005 prediction based on the 1984 2000 calibrated models. An urban expansion of 129.49% was predicted between 1984 and the forecasted 2030.

Ezeomedo (2012) through his study aimed to identify, model and analyze urban growth in Onitsha Metropolis using Remote Sensing and GIS Techniques. The study area is Onitsha North and South area and its environs (Obosi, Nkpor and IyiowaOdekpe). The data used for this

42 study includes: Topographic map of the study area, NigeriaSat-1 image, LandSat ETM+ image, SPOT 5 image and IKONOS image

The digitized topographical map and SPOT 5 were co-registered at a sub-pixel level to the coordinate system of IKONOS. The digitized map and NigeriaSat-1 were also co-registered at a sub-pixel level to the coordinate system of the LandSat ETM+. Sub-map was created in ILWIS 3.3 to define the area of interest from the full scene of the images (IKONOS, SPOT 5 and LandSat ETM+. The image was re-sampled with reference to the multispectral band using nearest neighbor interpolation to preserve the original values of the pixels. The supervised classification method was adopted.

The nature of urban change structure was studied and quantified using the Shannon entropy. The results of the growth measurement indicated that there has been high rate of growth and dispersed nature of urban development between 1964 and 2008; using the computed average annual rate 0.876% and yearly rate of change of 1.56%, the result shows increase of 38.54% and 68.64% respectively.