TITLE:
Urbanization and Other Land Use Land Cover Change Assessment in the Greater Kumasi Area of Ghana
AUTHORS:
Addo Koranteng, Isaac Adu-Poku, Bernard Fosu Frimpong, Jack Nti Asamoah, John Agyei, Tomasz Zawiła-Niedźwiecki
KEYWORDS:
Urbanization, Maximum Likelihood Classifier (MLC), Urban Sprawl, Change Detection, Forest Loss
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.11 No.5,
May
31,
2023
ABSTRACT: Urbanization
posits the expression of urban expanse expansion due to population growth, rise
in built-up areas, high population density and its correspondingly urban way of
life. Unrestrained impetus of development and land use land cover change (LULCC)
portent several issues such as unlawful urban sprawl, loss of agricultural land,
forest loss and other associated complications. This study analyzed the dynamics
of urbanization and other LULCC in Ghana’s Greater Kumasi area via Landsat images
(TM 1986, OLI 2013 and OLI 2023) using ERDAS Imagine, Idrisi and ArcGIS software.
Implementing supervised classification technique, the Maximum Likelihood Classifier
(MLC) procedure was employed to categories the study area into five LULC classes.
Accuracy assessment undertaken on the resultant LULC maps was deemed very satisfactory.
The results from 1986-2023 pointed to an upsurge in a built-up extent as of 8% to 41%, a decrease
in Closed Forest from 9% to 4%, another decrease in Open Forests from 64% to 33%,
a slight increase from 16% to 20% in farmlands and a stable level of water share.
Further analysis indicated that the study area had undergone LULCC within the periods
1986-2013 and 2013-2023 at 60% and 37% respectively. The findings showed uncontrolled urban sprawling
along major roads and forest loss as deforestation outside protected areas and degradation
in protected forest. The monitoring of urbanization and other LULCC is important
for local, and national governments and other bodies charged with the implementation
of programs and policies that manage and utilize natural resources. Development
adapts to mitigate the effect on the environment.