Assessment of Land Cover Dynamics and Drivers of Urban Expansion Using Geospatial and Logistic Regression Approach in Wa Municipality, Ghana

Mawuli Asempah, Wahib Sahwan and Brigitta Schütt
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Mawuli Asempah: Department of Earth Sciences, Institute of Geographical Sciences, Freie Universität Berlin, Malteserstraße 74-100, 12449 Berlin, Germany
Wahib Sahwan: Department of Earth Sciences, Institute of Geographical Sciences, Freie Universität Berlin, Malteserstraße 74-100, 12449 Berlin, Germany
Brigitta Schütt: Department of Earth Sciences, Institute of Geographical Sciences, Freie Universität Berlin, Malteserstraße 74-100, 12449 Berlin, Germany

Land, 2021, vol. 10, issue 11, 1-19

Abstract: The current trends of land use dynamics have revealed a significant transformation of settlement spaces. In the Wa Municipality of Ghana, the changes in land use and land cover are inspired by a plethora of driving forces. In this study, we assessed the geo-physical drivers of settlement expansion under land use dynamics in the Wa Municipality of Ghana. The study employed geospatial and remote sensing tools to map and analyse the spatio-temporal dynamics of the landscape, using Landsat satellite imageries: thematic mapper (TM), enhanced thematic mapper (ETM) and operational land imager (OLI) from 1990 to 2020. The study employed a binomial logistic regression model to statistically assess the geo-physical drivers of settlement expansion. Random forest (RF)–supervised classification based on spatio-temporal analyses generated relatively higher classification accuracies, with overall accuracy ranging from 89.33% to 93.3%. Urban expansion for the last three decades was prominent, as the period from 1990 to 2001 gained 11.44 km 2 landmass of settlement, while there was 11.30 km 2 gained from 2001 to 2010, and 29.44 km 2 gained from 2010 to 2020. Out of the independent variables assessed, the distance to existing settlements, distance to river, and distance to primary, tertiary and unclassified roads were responsible for urban expansion.

Keywords: savannah vegetation; random forest classifier; regression analyses; receiver operating characteristics (ROC); urbanisation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:10:y:2021:i:11:p:1251-:d:680139

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