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American Journal of  
Geospatial Technology (AJGT)

Geospatial Analysis of  the Spatio -Temporal Growth of  Kwali Area Council, 
Federal Capital Territory, Abuja

Umar Faruk Bello1*, Dr. Benedine Akpu2

Volume 1 Issue 1, Year 2022
ISSN: 2833-8006 (Online) 

DOI: https://doi.org/10.54536/ajgt.v1i1.359
https://journals.e-palli.com/home/index.php/ajgt

Article Information ABSTRACT

Received: July 01, 2022

Accepted: July 06, 2022

Published: July 07, 2022

This study analyzed the spatio-temporal growth of  Kwali Area Council in Federal Capital 
Territory Abuja, Nigeria from 1998 to 2017. The study used Landsat Thematic (TM) of  
1997, Landsat Enhanced Thematic Mapper Plus (ETM+) of  2007 and Landsat 8 Opera-
tional Land Imager (OLI) of  2017 all with a spatial resolution of  30 meters. Those data sets 
were accessed from United States Geological Survey (USGS) website Supervised Classifica-
tion-Maximum Likelihood Algorithm was used to establish the land use-land cover situations 
for 1997, 2007 and 2017; subsequently the extent and rate of  the urban growth of  the study 
area between 1998 and 2017 were determined. The findings revealed that urban landuse 
covered 265.9 hectares in 1998, 304 hectares in 2007 and 1100.3 hectares in 2017. The ur-
ban landuse increased by 38.2 hectares from 1998-2007 which represent 14.3% growth in 9 
years and corresponds with 4.24 hectares increase per year. The aforementioned growth rate 
was the lowest recorded in the period (1998-2017) of  study as 2007-2017 showed that the 
urban landuse increased by 796.1 hectares which represent 261.8% growth in 10 years, this 
gives a corresponding growth rate of  79.61 hectares per year. The study recommends that 
there is the need for ecosystems restoration for areas that have suffered terrible degradation 
especially bare lands and local ingenuity, indigenous technology and know-how, and local 
community-centered efforts should be made and supported to restore the environment. 
That Government should as a matter of  urgency embark on landuse /land cover mapping 
in the region in order to facilitate accurate base map production of  Kwali Area Council as 
well as digitize and update all analogue maps of  the area of  study for effective planning for 
all physical developments. Land use is a term indicating the use to which a portion of  land 
is put. Land is used for all of  man‟s economic activities, and so the use of  a portion of  land 
determines the economic productivity of  the land. Therefore, it is necessary to regulate and 
coordinate land use for optimum productivity and benefit of  all people whose livelihood 
depends on the land.

Keywords

Urban Growth/expansion, 
GIS, landuse/Landcover(LU/
LC), Image Classification, 
Kwali

1 Ahmadu Bello University Zaria. Nigeria.
2 Faculty Of  Physical Sciences Ahmadu Bello University, Zaria. Nigeria
* Corresponding author’s e-mail: bufaruuk@gmail.com

INTRODUCTION 
The world is becoming an increasingly urban place. Some 
65% of  the world’s population is expected to be urban 
by the year 2025 (Schell & Ulijaszek, 1999). As a result 
of  rapid urbanization, natural ecosystems are increasingly 
replaced by urban development. Urbanization, which 
means a population shift from rural to urban areas, is 
often accompanied by urban expansion and land use 
change. With worldwide land use land cover change, 
biogeochemical cycles, hydrologic systems and climate 
and biodiversity change driven by urbanization, increasing 
numbers of  ecologists have accepted that urban areas are 
hot spots that drive environmental change on multiple 
scales (Grimm et al, 2008). These hot spots are estimated 
not only to be current threats for ecosystems but also will 
probably last for a long period in developing nations. The 
global urban population will reach 5 billion by 2030 (UN-
HABITAT, 2006) and will increase by 2.7 billion by 2050 
(United Nations, 2010), which indicates that the dramatic 
urbanization phenomenon will continue. 
Urbanization is the dynamic process and it is one of  the 
more important indicators of  development. Though it is 
happening rapidly, in developing countries like Nigeria, 
the process of  urban expansion is underestimated, due to 
use of  traditional administration boundaries to demarcate 
urban area. But in the developing countries the urban 

growth is happening beyond the traditional boundaries 
and without proper planning (United Nations, 2010). 
Therefore the identification of  urban expansion and 
direction of  urban expansion are important for urban 
planning and to measure the level of  urban growth. 
Statistical information alone is difficult to measure urban 
growth because, it is physically observable phenomena 
on the earth surface, both horizontally and vertically. 
Therefore, spatial and temporal analysis is important 
to understand urban growth, and for this both RS 
(Remote Sensing) and GIS techniques provide unrivalled 
opportunity to analyze urban growth. 
Spatial information of  land use over time is an important 
means for city planning and undertaking development 
activities. Analyzing the spatial and temporal changes 
in land use is one of  the effective ways to understand 
the current environmental status of  an area and ongoing 
change. Urban expansion is a major cause of  land use 
changes (Singh and Kumar, 2012).
Urban growth indicates a transformation of  the vacant 
land or natural environment to construction of  urban 
fabrics including residential, industrial and infrastructure 
development. It mostly happens in the fringe urban areas 
(Shenghe and Sylvia, 2002). 
Geospatial technologies had been applied to investigate 
the effects of  urbanization on expansion variables and 

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to quantify urban growth in different parts of  the world. 
Remote Sensing and Geographical Information Systems 
(GIS) as modern technologies are increasingly used due 
to their cost effectiveness and technological soundness 
to develop useful sources of  information and to support 
decision making in connection with a wide array of  
urban applications (Lo and Yang 2002).  Due to the 
rapid influx of  people in search of  affordable lands and 
accommodation as when compared with expensive and 
high cost of  housing in Abuja, Kwali Area, as a result 
of  the proximity to Abuja attracts people and due to 
pressure on lend development is extending into prime 
agricultural land resulting to various environmental and 
social problems.
this research work proposes the following research 
questions; What are the land use and land cover classes 
in the areas?, What is the extent of  urban land use in 
the study area between 1998 and 2017? And What is the 
rate of  urban growth in the study area between 1998 and 
2017? 

Aim and Objectives 
The aim of  the study is to analysis the spatio-temporal 
growth of  Kwali between 1998 and 2017. The aim is 
achieved through the following objectives which includes 
to; Examine the landuse and landcover classes into areas 
, determine the extent of  urban Landuse in 1998, 2007 
and 2017 and determine the extent and rate of  the urban 
growth of  Kwali Area Council between 1998 and 2017.
 
LITERATURE REVIEW
Urban places include areas within or near a city considered 
to share broad characteristics such as population 
concentration; shared and distinct employment pattern, 
lifestyle and land use; as well as the existence of  different 
institutions that coordinate the use of  public facilities 
(Hartshorn, 1991). According to Week (2010), urban 
centre refers to the concentration of  people who are 
engaged in non-agricultural activities.
Opeyemi (2006) examined Change Detection on Land 
use and Land cover Using Remote Sensing Data and GIS 
(a case study of  Ilorin and its environs in Kwara State). 
The study made use of  multi-temporal satellite imageries 
and secondary data to map LandUse and Land- Cover in 
Ilorin between 1972 and 2001, using GIS techniques and 
statistical analysis to detect the changes that have taken 
place in its status between these periods.
Ishaya, Ifatimehin and Okafor (2008) carried out a 
study on urban expansion and loss of  vegetation cover 
in Kaduna town, deployed the use of  GIS and Remote 
sensing techniques with survey to identify the various 
land use and their transformations over time, recorded 
significant increase in the built-up area between 1990 and 
2000. Such expansions were mostly at the fringe of  the 
town area and are mainly due to population growth and 
development in its formal and informal sector of  the 
economy. 
Ojanuga and Ekwoanya (2008) studied Spatio-Temporal 

Changes in Land use Pattern in the Benue River Floodplain 
and the Adjoining Uplands at Makurdi, Nigeria. Makurdi 
and its environs were studied to assess the land use changes 
that occurred between 1967 and 1980’. The material and 
method used were two sets of  panchromatic (black and 
white) aerial photographs for 1967 and 1980 at scales of  
1:40,000 and 1:10,000 respectively. The landforms and 
land use patterns were interpreted and mapped with the 
aid of  the mirror stereoscope. Detailed ground truthing 
was done in a sample area of  18.8km2 to characterize the 
component soil units, and document the cultural land use 
that has occurred between 1980 (representing the most 
recent aerial photograph of  the area) and the present. 
The result has shown that the amount of  land converted 
to non-agricultural uses in Makurdi increased from about 
21% in 1967 and 32% of  the total land area in 1980. 
Presently, substantial part (estimated at more than 50%) 
of  the land in the Makurdi environs has been converted 
to urban use. 
Akpu and Tanko (2012) examined the rate and pattern 
of  the spatio-temporal Growth of  Kaduna Metropolis, 
Kaduna State Nigeria, using GIS and Remote Sensing 
techniques. Visual interpretation method was used to 
sort the various datasets into land use and land cover 
classes. The result of  the study showed that the built-up 
area increased from 6,410.4Ha in 1973 to 19,611.5Ha in 
2009. The was growing at a rate of  5.72% annually and 
the areas towards the southern part of  the River Kaduna 
were growing at a higher rate of  11.24% while the growth 
rate of  the northern part was 3.71%.
Aguda and Adegboyega (2013) evaluated spatio-temporal 
dynamics of  urban sprawl in Osogbo, Nigeria. The 
research made use of  remotely sensed satellite images 
of  1962, 1972 and 2013, using GIS techniques of  
classification, overlay and area calculation.  The study 
shows that the spatial extent of  the total urban built-up 
areas of  Osogbo city in 1962 was estimated at 3.95 km2. 
The total urban built-up areas increased to 6.61km2 in 
1972. This indicates that urban expansion has engulfed 
2.66km2 of  rural areas between 1962 and 1972. Thus, the 
rate of  urban expansion within the period was estimated 
at 4.0 % with land consumption rate and land absorption 
coefficient estimated at 0.0036 and 0.0076 respectively. 
This rapid rate of  urban expansion has been found to 
have encroached on agricultural lands thereby accounting 
for a total loss of  57.01 % in agricultural land.
Olusegun (2013) carried out a study on urban expansion 
in Ado Ekiti, Nigeria, using GIS and Remote sensing 
techniques. The results showed the expansion that has 
resulted over the years. It was discovered that Ado-Ekiti 
had an area of  2.5 square kilometres in 1956, which 
increased to 6.9 square kilometres in 1996, and 36.7 
square kilometres in 2006. The study suggested that if  
nothing is done to stem the uncontrolled expansion, the 
area may increase to 134.7 square kilometres in 2030. 
Odjugo, Enaruvbe & Isibor (2015) examined the spatio-
temporal pattern of  urban growth in Benin City, Nigeria 
for a period of  26 years (1987-2013) using remote sensing 

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data and geographic information systems techniques. The 
studies also examine the factors driving the observed 
pattern of  growth in the city. The results show that 
Benin City is growing more towards the north, east and 
south along the major transportation routes. The land 
use pattern in Benin City is compact and radial from the 
city centre while the growth pattern makes Benin City a 
monocentric city. The settlement expanded from 220 km2 
in 1987 to 359 km2 in 2013 with a mean annual growth 
rate of  1.5%. The growth of  Benin City was observed 
to be influenced by the siting of  public institutions such 
as schools, hospitals, government offices and industries. 
While the study demonstrates the importance of  using 
geospatial technology in the acquisition of  data for urban 
planning and management, the results highlight the 
influence of  infrastructure development on urban growth 
pattern. 
Wakirwa (2015) analyzed Urban Sprawl in Gombe 
Metropolis using geospatial techniques between 1991 and 
2014. The data used for the study were Landsat 5 Thematic 
Mapper (TM) of  1991, Landsat Enhanced Thematic 
Mapper plus (ETM+) data of  2005 and Enhanced 
Thematic Mapper plus (ETM+) of  2014.The extent of  
urban land use was determined by using the attribute and 
statistics data generated from the classification result and 
used for post-classification comparison among the years. 
The built-up was also extracted for each of  the periods 
and the extent of  the built up area was calculated in 
hectares. The extent of  the urban sprawl was analyzed 
by subtracting the reference year of  land cover of  2014 
from the base year 1991. The study explored urban 
sprawl in terms of  the spatial extent of  urban landuse, 
spatial extent of  urban sprawl and, the rate and pattern 
of  urban sprawl in the study area between 1991 and 2014.
It was found that urban landuse occupied: 12.78km² 
(13.55%); 33.02km² (35.01%) and; 48.49km² (51.43%) in 
1991, 2005 and 2014 respectively. Annual growth rate of  
1.45km² (11.31%), 1.72km² (5.21%), 1.55km² (12.15%) 
were witnessed between 1991 and 2005, 2005 and 2014, 
1991 and 2014 respectively. making. The results obtained 
from this study revealed that there has been a continuous 
increase in build-up areas throughout the study period. 
Al Mashagbah (2016) quantified the urban growth and 

trend in Zarqa city during between period 1990 and 2014 
using GIS and Remote Sensing techniques with Shannon’s 
Entropy statistical method. Three Landsat images for 
1990,2005 and 2014 were used for land use classification 
by using supervised maximum likelihood classification 
techniques to extract and assess the changes of  urban 
lands. The result indicated that the urban areas in Zarqa 
city increased by 22.15% in the period from 1990 to 2005 
and 14.86% from 2005 to 2014, with the entropy value 
for the NE, NW, SE and SW zone showed high values, 
which confirmed that urban expansion and sprawling had 
existed in the past twenty-four years in the study area. 
Bununu (2017) simulated urban expansion using Kaduna 
in North-West Nigeria as a case study. Hybrid model that 
integrates the similarity-weighted instance-based machine 
learning algorithm for transition potential modelling and 
the Markov chain model to quantify and allocate land-use 
change was used to overcome the identified weaknesses 
of  known modelling techniques such as the cellular 
automata, Markov chain and standard logistic regression 
models. Environmental and urban physical variables that 
act as constraints and/ or incentives to urban expansion 
were operationalized to create transition potentials for 
spatio-temporal states of  built-up land use for the year 
1990 and 2001. Model evaluation and validation was 
carried-out using the relative operating characteristic and 
Kappa index of  agreement statistics. 

METHODOLOGY
Kwali Area Council is located between Latitudes 80 30’ 
and 80 55’ North of  the Equator and Longitudes 60 47’ 
and 70 13’ East of  the Greenwich Meridian as shown 
in Figure 1. It is bounded on the North by Gwagwalada 
LGA, the West by Abaji LGA and to the East Kuje LGA.
 Kwali LGA consist of  10(ten) political wards, namely; 
Ashara, Dafa, Gumbo, Kilankwa, Kundu, Kwali,   Pai, 
Wako, Yangoji,  Yebu wards. Kwali Area Council 
experiences annually both the rainy and dry season. The 
rainy season begins in April and end in October when 
daytime temperature reaches 28-30ºC and nighttime lows 
over around 22-23ºC. According to National Population 
Commission (NPC) (2006), Kwali Area Council has 
population of  86,174. Using Exponential population 

Fig.1: Kwali Area Council
Source: Administrative map of  the study Area (2019)

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projection formula, at annual growth rate of  6.11%, the 
population of  Kwali Area Council is estimated to about 
179, 391.

Research Protocol
The first step, a researcher to was carried out reconnaissance 
survey for enable the researcher get a general knowledge 
of  the study area. This knowledge was very useful during 
selection of  training site and visual image interpretation 
process before and after classification.
The second step involve data collecting and data 
processing, Landsat imageries for 1997, 2007 and 2017 
was downloaded from the United States Geological 
Survey (USGS) website at www.glovis.usgs.gov. They 
include the following:

1. Landsat Thematic Mapper (TM), 1998 with spatial 
resolution of  30 meters.

2. Landsat Enhanced Thematic Mapper Plus (ETM+) 
of  2007 with spatial resolution of  30 meters.

3. Landsat 8 Operational Land Imager (OLI) of  2017 
with spatial resolution of  30 meters.

Data Processing
Image Pre-processing
Image processing techniques of  layer stacking and sub 
setting were performed on the three sets of  satellite 
images. To produce a composite image for each set of  
Landsat image, bands 1,2,3,4,5,7 of  ETM+ and bands 
2,3,4,5,6,7 of  OLI will be stacked together respectively. A 
subset covering the area of  interest will be extracted from 
the two composite images of  the study area. 

Image Classification
The satellite images were classified into land use classes. 
Anderson et al (1976) land use/ land cover Classification 
Systems was modified to classify the images into three 
land use classes: built-up (impervious layers such as 
residential and commercial services, office blocks, 
educational centres, hospitals, manufacturing industries, 
motor roads, rails etc); green areas (all cultivated areas 
such as farmlands, crop fields including vegetable gardens, 
plantations, fallow plots, protective forests, timber forest, 

Data Analysis
Rate of  Change Analysis
Post-classification comparison change detection 
algorithm will be applied to determine the changes in 
built up land use that has taken place from each classified 
image of  the study area. In order to determine the extent 
and rate of  change in built up in the study area, the 
following variables will be computed:
Total area (Ta), Changed area (Ca), Change extent (Ce) 
and Annual rate of  change (Cr)
These variables can be described by the following formula:
Ca = Ta (t2)-Ta (t1)
Ce = Ca / Ta (t1) x100%
Cr = Ce / (t2 - t1) 
Where t1 and t2 are the beginning and endin
g time of  the land cover studies conducted.
Overlay Analysis
The built-up areas for 1998, 2007 and 2017 were 
superimposed on each other to analyze the pattern of  
urban growth in the study area. This process was done 
in ArcGIS 10.5.

RESULTS AND DISCUSSION
Land use land cover classification maps for 1998, 2007 
and 2017 of  the study were generated and presented in 
Figures 2, 3 and 4. Table 1 summarizes the total land area 
for each land use land cover class across the study area 
and the corresponding percentage of  the total.
As shown in Table 1, the built-up has progressively 
increased throughout the study period from 265.9Ha in 
1998, 304.1Ha in 2007, 1100.3ha in 2017 representing 0.2 
%, 0.3% and 0.91% of  the total landuse. This progressive 
increase in built-up area is in agreement with the work 
of  Ade and Afolabi (2013), which revealed that built 
up areas in city(Abuja) increased throughout the study 
period from 78.75km2 in 1987 to 147.22km2 in 1999 and 
built up further increased to 416.22km2 in 2007 and an 
increase from 4%, 8% and 22% respectively. This growth 
extends not just inwards but outwards. This indicates that 
the continuous increase in built-up in Kwali has given rise 
to continuous increase in the urban expansion.   
Water bodies which constituted 0.3% of  the total area in 
1998 increased in 2007 to 0.9% and decreased to 0.72% in 
2017. The urban growth has also impacted on the water 
bodies negatively.  Although generally, the reduction 
could be attributed to climate change. 
Vegetation, which occupied 75400.6Ha (62.5%) in 1998 
decreased to (55.5%) in 2007 and increased to 70.08% in 
2017. Compared to 1998 vegetation cover has also been 
on the decrease. The decrease in vegetation between 1998 
and 2007 in might have been caused by the increase in 
built-up area and other anthropogenic activities, leading 
to invasion of  prime vegetal cover and conversion of  
vegetation lands to built-up land. This is in line with 
the work of  Nwafor (2006) who also found that vegetal 
lands in Owerri decreased as built-up area increased. Bare 
land was 37.0 % in 1998, 43.3% in 2007 and decreased 
to 28.29% in 2018. During the epoch, 1998 to 2007, 

Classification Scheme 
Code Class Name Description
1 Built-up Residential, commercials, 

transportation and communication.
2 Water body Rivers, stream and lakes
3 Vegetation Natural forest, natural vegetation 

like grasses, shrubs, grass-like plant, 
farmlands, deforested area and clear 
forest land.

4 Bare land Exposed soil and rock outcrops
Source: Modified from Anderson, Hardy, Roach, and Witmer (1976)

economic forest, firewood forest and forests of  special 
use), bareland (rock outcrop, bare surfaces or places with 
scanty grass) and water (river, stream, dam, pool and 
lake). Supervised classification system using maximum 
likelihood algorithm was performed on the images.

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the increase in urban land use had not really been too 
much as the built-up area barely increased by 14.3% 

Table 1: Land Use and Land Cover Statistics
Name 1998 2007 2017

Area (Ha) % Area (Ha) % Area (Ha) %
Built up 265.9 0.2 304.1 0.3 1100.3 0.91
Water 389 0.3 1077.8 0.9 866.4 0.72
Vegetation 75400.6 62.5 66969.7 55.5 84547.6 70.08
Bareland 44589.5 37.0 52293.4 43.3 34130.7 28.29
Total 120645 100 120645 100 120645 100
Source: Author’s GIS Analysis (2019)

as shown in Figure 2-4. The increase in bare land may 
be attributed to clearing of  vegetal cover for built-up 
activities, low rainfall and the people not cultivating the 

Figure 2: 1998 Land use Land Cover Classes of  the 
Study area
Source: Author’s GIS analysis (2019) 

Figure 3: 2007 Land use Land Cover Classes of  the 
Study area
Source: Author’s GIS analysis (2019)

Figure 4: 2017 Land use Land Cover Classes of  the 
Study area
Source: Author’s GIS analysis (2019)

land and more anthropogenic activities. But as the urban 
land use increased significantly, between 2007 and 2018, 
it impacted on the bare land negatively decreasing to 
(28.29%). 
Extent and Rate of  Urban Growth
The extent of  built-up land use for 1998, 2007 and 2017 
are shown in Figure 5,6 and 7 respectively.  Table 2 shows 
the extent and rate of  the urban expansion between the 
various time periods.
The results as shown in Table 2 reveal that the built-
up area increased by 38.2 hectares from 1998 to 2007 
at an annual rate of  4.24%. The period 2007-2017 also 
recorded an increase in built-up (796.1 hectares) with an 
annual growth rate of  26.18%. 
The analysis reveals that the extent and rate of  urban 
growth in the study area increased appreciably. As shown 
in Table 2, the study area in 1998-2007 urban expansion by 
38.2Ha (14.3%) at a rate of  1.59% each year. The period 
between 2007 and 2017 witnessed a urban expansion of  
796.1Ha (261.8%) at a rate of  26.18% annually. Generally, 
from 1998 to 2017, the urban area in Kwali Area Council 
also increased by 834.3 hectares at 16.52% per annum.
This result is in agreement with the work of  Ade and 

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Afolabi, (2013) which analyzed urban sprawl in Abuja 
and the result shows that the extent of  growth increased 
not just inward but outwards. And also agreement with 
the work of  Shittu, (2018) Spatio-temporal analysis of  
urban expansion in greater Karu urban area, Karu local 

Government area, Nasarawa state.
Figure 2 to Figure 4 shows the sub-sets of  the urban land 
use in the study area for the three epoch to demonstrate 
how it has grown over time.
Pattern of  Urban Growth in Kwali Area Council

Table 2: Extent and Rate of  Urban Growth in Kwali Area Council
Urban Magnitude of  Expansion Rate of  Expansion
Period Year Hectares Ha % Ha/Yr %/Yr
1998-2007 1998 265.9 38.2 14.3 4.24 1.59
9Years 2007 304.1
2007-2017 2007 304.1 796.1 261.8 79.61 26.18
10Years 2017 1100.3
1998-2017 2001 265.9 834.3 313.7 43.91 16.52
19Years 2017 1100.3
Source: Author’s GIS analysis (2019)

Figure 5: Extent of  Built up in 1998
Source: Author’s GIS analysis (2019)

Figure 6: Extent of  Built up in 2007
Source: Author’s GIS analysis (2019)

Figure 7: Extent of  Built up in 2017
Source: Author’s GIS analysis (2019)

Figure 8: Pattern of  Urban Growth in Kwali Area 
Council
Source: Author’s GIS analysis (2019)

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The pattern of  urban growth of  the study area was 
derived by superimposing the built up land use of  1998, 
2007 and 2017 on each other and the result of  the overlay 
analysis is presented in Figure 8. On the bases of  the 
results obtained from the analysis, three patterns of  urban 
growth namely; cluster, radial and leapfrog were found 
which varied from different study periods (1998, 2007 
and 2017). Though, all of  the study periods witnessed 
cluster in some of  the villages in the study area, there is 
still variation within the study periods. It was found that 
in 1998 the pattern of  the urban expansion was cluster 
while 2007 and 2017 witnessed both radial and leapfrog 
pattern of  urban growth.

Summary of  Findings
This project analyzed spatio-temporal urban expansion 
in Kwali Area Council, between 1998 and 2017 using 
Geospatial techniques. Landsat Thematic Mapper (TM) 
of  1998, Landsat Enhanced Thematic Mapper Plus 
(ETM+) of  2007 and Landsat 8 Operational Land Imager 
(OLI) of  2017 all with a spatial resolution of  30 meters 
of  the study area were utilized. The land use land cover 
classes identified in the study area were built-up, water, 
vegetation and bare lands as the maps were generated 
using supervised classification. The findings revealed 
that urban landuse covered 265.9 hectares in 1998, 
304 hectares in 2007 and 1100.3 hectares in 2017. The 
findings also revealed that the urban landuse increased 
by 38.2 hectares from 1998-2007 which represent 14.3% 
growth in 9 years and corresponds with 4.24 hectares 
increase per year. However, the period 2007-2017 showed 
that the urban landuse increased by 796.1 hectares which 
represents 261.8% growth giving a corresponding growth 
rate of  79.61 hectares per year.

CONCLUSION
This study reveals that there is high rate of  urban 
expansion in Kwali Area Council. From the analysis 
carried out, the results obtained from this study revealed 
that there has been a continuous increase in build-up 
areas throughout the study period. There has also been 
a progressive increase of  urban growth both in terms of  
spatial extent and annual rate throughout the study period. 
The period of  between 2007 and 2018 had the highest 
rate of  urban expansion which could be attributed to the 
fact that it was the period within which the restoration of  
FCT master-plan. It is obvious that the selected study area 
demands attention of  planners and the FCDA to monitor 
and enforce land use policies to avoid urban sprawl.

RECOMMENDATIONS
Based on the identified changing nature and rate of  
various land-use/land-cover types identified in the study 
area especially from 1998 to 2017, the following are 
recommended:
Owing to the continual increase in urban sprawl in both 
extent and the rate in the study area, the following are 
recommended:

1. There is the need for ecosystems restoration for 
areas that have suffered terrible degradation especially 
bare lands.

2. The local communities are presently implementing 
the only adjustment mechanism they know which 
is to move away from degraded LULC. But local 
ingenuity, indigenous technology and know-how, and 
local community-centered efforts should be made and 
supported to restore the environment.

3. The tacit, informal and experienced based old natural 
community instinct needs to be rekindled to promote 
vegetation growth and maintain green countryside. 
Information, education and incentives should also 
be provided to stimulate the interests of  the local 
communities in reforestation and sustainable farming 
activities.

4. Legislations compelling environmental protection, 
restoration and remediation need to be enforced.

REFERENCES
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