Browsing by Author "Lasisi, Kayode"

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  • Publication
    Publication
    Object-based land use/land cover change detection of a coastal city using Multi-Source Imagery: a case study of Lagos, Nigeria
    (South African Journal of Geomatic, 2020-09-06) Idowu, Temitope Ezekiel; Waswa, Rose M.; Lasisi, Kayode; Nyadawa, Maurice; Okumu, Victoria
    In the wake of the burgeoning population, socio-economic and environmental issues facing coastal areas, LULC change detection has become an essential tool for environmental monitoring towards achieving sustainable development. In this study, an object-based image analysis approach using post-classification comparison technique was applied for assessing the LULC of the coastal city of Lagos from 1986 to 2016. The study describes how satellite imagery from different sources (Landsat and SENTINEL 2A) can be successfully integrated for Land use Land cover change detection. The results show that between 1986 and 2016, there were net increases in bare areas, built-up areas, and shrublands and a general decline in forestlands, waterbodies and wetlands. Over 60,000ha cover (approx. 190% increase) was converted into built-up areas while 83,541ha (835.4km2) of forestland were lost, suggesting high rates of urbanization and corresponding deforestation. About 60% loss of wetlands was also observed in the same time period. The decrease in water bodies and a steady increase in bare and built-up areas are possibly due to the prevalent land reclamation activities in the study area. Higher rates of deforestation and increase in bare areas were observed from 2001 to 2016 in comparison to 1986 to 2001. The observed trends are likely to continue, and for future management actions, predictive studies are suggested to provide more empirical evidence.
  • Publication
    Publication
    Towards achieving Sustainability of coastal environments: Urban Growth analysis and prediction of Lagos, State Nigeria
    (2022) Idowu, Temitope Ezekiel; Waswa, Rose Malot; Lasisi, Kayode; Mubea, Kenneth; Nyadawa, Maurice; Kiema, John Bosco Kyalo
    The most extensive urban growths in the next 30 years are expected to occur in developing countries. Lagos, Nigeria - Africa’s second most populous megacity- is a prime example. To achieve more sustainable and resilient cities, there is a need for modeling the urban growth patterns of major cities and analyzing their implications. In this study, the urban growth of Lagos state was modeled using the Multi-Layer Perceptron (MLP) neural network for the transition modeling and the Markov Chain analysis for the change prediction, achieving a model accuracy of 81.8%. An innovative visual validation of the model results using the ArcGIS was combined with kappa correlation statistics. The results show that by 2031, built-up areas will be the most spatially extensive LULC class in the study area with percentage coverage of 34.1% as opposed to 9% in 1986. The coverage of bare areas is also expected to increase by 53% between 2016 and 2031. Conversely, 24.9% and 68.3% loss of forestlands and wetlands respectively, are expected between 2016 and 2031. In view of the 11th goal of SDGs which focuses on achieving sustainable cities and communities, the objectives of African Union’s Agenda 2063, and based on the urban growth trends observed, the study recommends a prioritization of vertical expansion as opposed to the current horizontal urban growth trends in the study area.