Authors :
Bikie Gerald Anicet; Dongmo Hile Bertrand; Aba Nkasse Alain; Elime Boubouama Aime; Berka Afofeyuf Christian; Mohammed Achab
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/2bpsexz3
Scribd :
https://tinyurl.com/ymbd334u
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR2157
Abstract :
Over the past years, humans have directly or
indirectly affected the Earth’s surface through various
activities. These changes in terrestrial ecosystems are
closely linked with the issue of the sustainability of socio-
economic development since they affect essential parts of
our natural capital such as climate, soils, vegetation,
water resources and biodiversity. Land Cover has
undergone several changes in Cameroon since its
independence in 1960. One of the major drivers of this
change is urbanization. Uncontrolled, rapid
urbanization has had many negative impacts on the
center region of Cameroon, around the continuum of its
headquarter and in Cameroon metropolises such as
anarchical constructions, pollution and traffic
congestions. Faced with these urbanization issues,
planners need to know the spatiotemporal trends of
Land Use Land Cover for the past, present and have
predictions of possible future patterns in order to better
orient their planning. This is possible through the
establishment of Land Use Land Cover maps. Remote
sensing and Geographic Information Systems represent
a cost-effective method for accomplishing this. In this
work, we examine the case of Monatélé, a growing city
around the Yaoundé metropolis. Satellite images from
2010, 2017, 2022 were downloaded and classified into
five classes using the Support Vector Machine algorithm
of image classification. It was found that between 2010
and 2022, settlements have increase continuously from
1.61% to 4.28%, water has decreased continuously from
9.81% to 6.72%, forest has experienced a net decrease
from 73.77% to 68.25%, agriculture has experienced a
net increase from 12.44% to 16.92%, while Bare Land
has had a net increase from 2.38% to 3.82%. of the total
surface area of the subdivision of Monatélé. Predictions
made for 2029 and 2035 show that by 2035, settlements
would have increased to 6.58%, water would have
decreased to 4.58%, forest would have decreased to
61.22%, agriculture will take 25.19%, and bare land
would have almost remained unvaried, taking up 2.43%
of the surface area from 2010 to 2035. This will
represent for Monatélé an increase in anarchical
settlements, an increased loss in biodiversity, an
increased pollution, an increase in demand for basic
commodities, and an increased pressure on natural
resources, if no planning measures are put in place,
though it may represent an increase in human capital,
an increase in local employment opportunities, a
reduction of groceries expenditures.
Keywords :
Land use Land Cover, Support Vector Machine, Remote Sensing, Geographical Information Systems, Urbanization.
Over the past years, humans have directly or
indirectly affected the Earth’s surface through various
activities. These changes in terrestrial ecosystems are
closely linked with the issue of the sustainability of socio-
economic development since they affect essential parts of
our natural capital such as climate, soils, vegetation,
water resources and biodiversity. Land Cover has
undergone several changes in Cameroon since its
independence in 1960. One of the major drivers of this
change is urbanization. Uncontrolled, rapid
urbanization has had many negative impacts on the
center region of Cameroon, around the continuum of its
headquarter and in Cameroon metropolises such as
anarchical constructions, pollution and traffic
congestions. Faced with these urbanization issues,
planners need to know the spatiotemporal trends of
Land Use Land Cover for the past, present and have
predictions of possible future patterns in order to better
orient their planning. This is possible through the
establishment of Land Use Land Cover maps. Remote
sensing and Geographic Information Systems represent
a cost-effective method for accomplishing this. In this
work, we examine the case of Monatélé, a growing city
around the Yaoundé metropolis. Satellite images from
2010, 2017, 2022 were downloaded and classified into
five classes using the Support Vector Machine algorithm
of image classification. It was found that between 2010
and 2022, settlements have increase continuously from
1.61% to 4.28%, water has decreased continuously from
9.81% to 6.72%, forest has experienced a net decrease
from 73.77% to 68.25%, agriculture has experienced a
net increase from 12.44% to 16.92%, while Bare Land
has had a net increase from 2.38% to 3.82%. of the total
surface area of the subdivision of Monatélé. Predictions
made for 2029 and 2035 show that by 2035, settlements
would have increased to 6.58%, water would have
decreased to 4.58%, forest would have decreased to
61.22%, agriculture will take 25.19%, and bare land
would have almost remained unvaried, taking up 2.43%
of the surface area from 2010 to 2035. This will
represent for Monatélé an increase in anarchical
settlements, an increased loss in biodiversity, an
increased pollution, an increase in demand for basic
commodities, and an increased pressure on natural
resources, if no planning measures are put in place,
though it may represent an increase in human capital,
an increase in local employment opportunities, a
reduction of groceries expenditures.
Keywords :
Land use Land Cover, Support Vector Machine, Remote Sensing, Geographical Information Systems, Urbanization.
