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The study examined land accessibility constraints among migrants in rural border settlements of Ogun State, Nigeria. It specifically examined dimensions, extent of importance of the constraints and their joint interactive influence on land accessibility. Data were collected through questionnaires on migrant household heads. A multi-stage sampling technique was used for the selection of 492 respondents for the study. Data collected were analysed using descriptive and inferential statistics (t-test, relative important index (RII) and correlation statistics). The study revealed that the majority of the sampled migrants were within an active and productive population (31-60 years). Also, the larger percentage of the respondents were male (64.8%), married (70%), farmers (67.2%) with no formal education (51.3%). Most of the migrants have stayed above 6 years (79.8%) in the study area. This is an indication that migrants would have detailed experience about their land accessibility constraints. Findings showed that the high cost of land was the major constraint to land accessibility and non-availability of land (scarcity) was the least constraint. The study further revealed that the high cost of land, inability to transfer land, difficulty in land transaction and insecure tenure jointly influenced migrants' access to land in the study area. The study therefore recommended the need for an efficient land administration and governance at local government level in order to accommodate the attendant needs of rural migrants in the study area.

Osogbo, the state capital of Osun State is one of the rapidly urbanizing cities in Nigeria. This article examined urban expansion and the transition of agricultural land in Osogbo with the use of multi-temporal imageries between 1986 and 2018. Large amounts of cultivated land has been transformed into other land uses in the past 31 years. This paper presents the process of the loss of agricultural land and urban growth in Osogbo with the use of remote sensing and GIS. Landsat imageries for 1986, 2002 and 2018 were used to analyse land use and land cover change. Supervised image classification was applied to classify the images into different land use categories. Six land use classes were identified: built-up area, water body, cultivated area, gallery zone, dense vegetation and rocky outcrops. Built-up areas (residential, educational and industrial areas) have greatly increased while agricultural lands (i.e. farmland and wetland) have considerably decreased during the study period. Built-up area covered 7.06% in 1986 but increased to 53.61% in 2018 while agricultural land decreased from 86.28% to 41.53% in the same period. The study therefore recommends that government should integrate agricultural lands into urban land use, planning for efficient management and protection of the dwindling agricultural space.