This study makes use of Markov chains modeling to predict sprawl and pattern of land use change in Akure region. Efforts were made to examine the trend of the expansion using Aerial Imagery Interpolation (AII). It focuses on overlaying of Landsat TM imageries of 1986, 2002, 2007 and 2014 to determine the land use changes and extent of expansion between 1985 and 2014. The land use were classified and displayed in colors for better visualization. With the aid of Markov chain modeling, the study made a projection of possible land use area and extent of expansion by the year 2034. Findings revealed continuous expansion in the growth of the city as evident in percentage increase of the builtup area. There were incompatible conversions in land uses and unguided expansions leading to undue encroachment into green areas at the suburbs. It was observed that without appropriate attention to adequate planning for effective measures, the trend of changing agricultural and forested lands to builtup areas will continue to increase with attendant effects on regional environment. Consequently, the study suggests effective zoning strategy and sustainable monitoring measures by different stakeholders in urban planning to check indiscriminate urban expansion in the study area.
This study aims at assessing how riparian zones have been altered through various land use activities and the implications of its capacity to mitigate flood. The study focused mainly on examining the land use/land cover changes within the riparian zone over a period of 20 years. The vulnerability of the riparian zone to flood were analyzed using remote sensing datasets. Flood vulnerability models were created based on the elevation and land cover type. A Euclidean distance (700 m) was created using the shuttle radar topographical mapping (SRTM) digital elevation model (DEM) of the lake and its riparian zone. The flood attenuation (150 m buffer) and riparian habitat (500 m) zones (areas) within the riparian zone of the lake were then created using the extracted lake boundary. Landsat 7 (for 1999) and 8 (for 2019) covering both zones were classified using the Maximum Likelihood Classification method. The results revealed that the built-up area increased from 2.04 to 4.54 km 2 between 1999 and 2019 while water body, grassland, and forest decreased from 0.05 to 0.04 km 2 , 0.37 to 0.12 km 2 and 1.84 to 1.82 km 2 over the period of the study. The results further show that about 18.9% of built-up areas were within the very high vulnerability zone of flood as of the year 2019. The results reveal that the riparian area cover is declining in the study area, despite its ecological services in reducing the effect of floods by slowing down runoff, trapping sediments and enhancing infiltration. The pattern of distribution of the land cover classes at different flood vulnerability levels within zones indicates that the more the alteration of both zones' landscape, the more vulnerable they are to flood. The study concluded that there is a significant level of structural change of the riparian zone which increases its vulnerability level to flooding.
One of the greatest changes that have occurred in the last century in developing countries is the urban growths which have produced more slums in our cities. The study examines the physical conditions in Makoko, an urban slum in Lagos, Nigeria. Geographical information system (GIS) and remote sensing (RS) technologies were used, in a post classification, to model possible land use changes in the area overtime. It also uses questionnaires to elicit information on infrastructural and socio-economic characteristics to determine the factors responsible for the physical conditions of Makoko. Findings revealed that the rate of infrastructural provisions are lacking behind and suffer from overstress and dilapidation The residents lack good environmental sanitation as the lagoon emits a pungent smell. It is recommended that the area is entirely restructured so as to create a habitable abode for sustainable residential living.
Ancient city centres are characterised by inadequately planned/unplanned land use and unsecured tenure system, leading overtime to the development of different forms and grades of slum in and around urban core area. This research studied the slum in the urban core of Akure, Nigeria deploying tools of Geographic Information System for comprehensive analysis of slum peculiarity for guiding action. Descriptive and analytical methods based on field survey and extraction of information from satellite images were utilized. The study examined the existing situation in the study area in terms of its housing system, conditions of infrastructure, socio-economic status of respondents and adequacy of livelihood with respect to slum indicators as defined by UN-Habitat (2003). The study revealed specific areas of higher degree of slum conditions and a representation of level of changes in land uses. Another finding shows high rate of conversion, mainly from residential land uses to other uses as the major characteristic of land use changes in the area. Poverty has constituted a dominant factor for continued existence of slum conditions due to paucity of employment opportunities. The study further discovered diverse manifestations of slums within a locality attributed to factors such as strong family linkages, structure of property ownership and high level of economic dependency. Economic empowerment through aids and supports for Small Medium Enterprises (SMEs), development of market network strategy for Akure and development of a comprehensive land use plan that would ensure sustainable growth of the city core area are canvassed.
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