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Research Article Open access CC BY 4.0

Assessment of Urban Sprawl, Land Use and Land Cover Changes in Voi Town, Kenya Using Remote Sensing and Landscape Metrics

Samantha Kahoya Nyongesa, Marianne Maghenda, Mika Siljander

Journal of Geography, Environment and Earth Science International · pp. 50–61 · Published 13 May 2022

10.9734/jgeesi/2022/v26i430347

Abstract

  Rapid and uncontrolled urbanization is a major issue in both developing and developed countries. Uncontrolled urbanization has resulted to unplanned expansion of residential and commercial areas, informal settlements, housing shortages, and unplanned land use. Understanding and quantifying urban sprawl spatiotemporal patterns is critical for informing the development of appropriate policies for effective and sustainable land use management. Using image classification and spatial metrics, this study examines the changes in Voi town's urban land use/land cover (LULC) between 1999 and 2019. The LULC was mapped using Landsat Thematic Mapper (TM):Landsat Enhanced Thematic Mapper Plus (ETM+):and Landsat Operational Land Imager (OLI) datasets using supervised maximum likelihood classification. A post classification approach was used to detect and assess LULC changes in the study area, while selected spatial metric indices quantified urban sprawl. The results of the change detection analysis revealed that Voi town has been rapidly expanding, with an urban expansion of 187.96 percent from 1999 to 2011, 183.40 percent from 2011 to 2019, and 716.1 percent from 1999 to 2019. In 1999, the built-up area comprised 1.29 percent of the total study area, 3.72 percent in 2011, and 10.53 percent in 2019. Based on spatial metrics analysis, the number of built-up area patches in 1999, 2011, and 2019 was 154, 278, and 526, respectively. An increase in the number of patches indicated fragmentation and the emergence of new built-up areas.  As a result, city planners will need to plan ahead of time and implement additional measures to deal with the city's future rapid and unprecedented growth.    

Land use/ land cover supervised classification change detection spatial metrics

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