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      Urban growth monitoring using spatial landscape matrices

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      ScienceOpen Preprints
      Landscape Metrices, Land use land cover, Urbanisation

            Revision notes

            Removing some of the content that was a bit irrelevant.

            Working on the maps I used to make them better visually


            With over 80% of global GDP created in cities, urbanization may contribute to long-term growth if properly managed. (The World Bank, 2021). In Uganda, the population living in urban areas are rising at a rate of 2.335% since 1990 to 2020. Cities must act fast to plan for expansion and provide the fundamental services, infrastructure, and affordable housing that their growing populations require. Urbanisation occurs at the expense of transformation of other landscapes hence the process of urbanization has a large influence on landscape and ecosystem function. For assessing policy alternatives for future growth and sustainable development of urban planning must be considered. Through mapping and analyzing land use/land cover transition in urban areas, as well as monitoring their environmental effects with the help of landscape metrices was the focus of this research. Landsat Images of 1990, 2000, 2010 and 2020 were used for this study, band ratios of NDVI, NDBI, NDWI were used for image enhancement to clearly identify the vegetated areas, built up areas and the areas that were covered with water, then a maximum likelihood classification technique was used to classify the images accordingly with an accuracy assessment of above 80% was accepted, the resulting classified images were then taken to FRAGSTATS for computation of landscape metrices. The metrices examined included class area, number of patches, total core area, core area percent of landscape, splitting Index, and landscape division index. It was discovered that the urban areas that converged between 1990 and 2020 contributed significantly to the fragmentation of predominantly the primarily vegetated regions of the research area, as well as the loss of the core portions of several habitats.


            Author and article information

            ScienceOpen Preprints
            25 April 2022
            [1 ] Department of Geomatics and land management, Makerere University
            Author notes

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

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            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            Remote sensing,Environmental change,Environmental studies
            Land use land cover,Landscape Metrices,Urbanisation


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