Abstract Lagos is Africa's most populous megacity and one of the world's fastest-growing urban areas. Lagos city's land use and land cover (LU/LC) classes have changed dramatically in recent decades as a result of its continuing population growth and other human and anthropogenic activities. The UN 2030 Agenda for Sustainable Development must be adopted in order to preserve the available land cover classes in Lagos. Goal 11 of the Sustainable Development Goals aims to make cities and human settlements more inclusive, safe, resilient, and long-term. The use of remote sensing and geographic information systems (GIS) to track the progress of SDG 11 is an essential strategy. Remote sensing and geographic information systems were used to model and analyze the data in this study. To achieve this aim, remotely sensed data, such as Landsat 7 ETM + and 8 OLI, was used to determine the rate of changes in Lagos from 2010 to 2020 by adopting the Maximum Likelihood Classifier (MLC) and then project the likely changes that may occur by 2025 and 2030. Observed ground truthing information was adopted for validation and for checking the accuracy of the classification. The result shows that from 2010 to 2015 and to 2020, built-up area had increased from 11.73 % to 12.81 % and finally to 29.51 %, while agricultural land declined by 11.84 % to 3.37 % and then to 2.99 %. Water bodies and wetland percentages decreased from 19.00 % and 19.50 % in 2010 to 17.39 % and 8.48 % in 2015, and to 18.37 % and 16.92 % in 2020. Forest land and bare land classes have also changed from 25.4 % and 12.52 % in 2010, to 33.37 % and 24.58 % in 2015, and to 18.10 % and 14.11 % in 2020. The study shows that remote sensing and GIS are excellent tools for monitoring the environment and for the development of a sustainable city.


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    Title :

    Modeling and mapping the spatial–temporal changes in land use and land cover in Lagos: A dynamics for building a sustainable urban city



    Published in:

    Advances in Space Research ; 72 , 3 ; 694-710


    Publication date :

    2022-07-17


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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