A COMPARATIVE ANALYSIS OF ENVIRONMENTAL AND SOCIO-ECONOMIC
IMPACTS OF MIGRATION ON URBAN GROWTH IN PLATEAU AND NIGER
STATE OF NIGERIA
BY
ISYAKU, Muhammed Bello
MTech/SPS/2019/10396
DEPARTMENT OF GEOGRAPHY
FEDERAL UNIVERSITY OF TECHNOLOGY, MINNA
SEPTEMBER, 2023
CHAPTER ONE
1.0
1.1
INTRODUCTION
Background to the Study
A world demographic shift is occurring as cities and towns promise new opportunities for
personal development, upward mobility, and greater access to social infrastructures and services.
In this shift, villagers and rural inhabitants are moving towards urban areas and shape the urban
environment, leaving footprints in the form of vertical cities and sprawling metropolises.
Environmental and socioeconomic impact of migration on urban growth to national development
cannot be over-emphasized. Environmental impact constitutes a critical indicator in socioeconomic and demographic discourses in any nation and constitutes a major migration impact to
development in many developing countries including Nigeria. Castelli (2018) identified the
drivers for migration on urbaninization growth as micro factors. Micro drivers are those that
include the policies, demography, socioeconomic and environmental factors can influence urban
growth . Nigeria is the most populous country in Africa with over 160 million population, land
surface area of 923,768 km2, and a national growth rate of 3.2 per cent per annum1.
In Nigeria, rural people migrate in quest of social and economic opportunity, in response to
environmental and socio-economic reasons, all of which contribute significantly to urban growth
and urbanization process United Nation (2017). However, the factors that lead people to migrate,
voluntarily or involuntarily, permanently or temporarily, and that perpetuate movement
influenced by Socio-economic and demographic drivers, environmental drivers, and human
crisis. Carling and Talleraas stated in 2016 that migration is driven by a desire for change, as
well as blockage of transition to independent adulthood. In the UN (2019) report it indicates that
the number of people living in urban areas and cities worldwide increased from 1.731 billion
(39.35%) in 1980 to 3.968 billion (53.91%) in 2015, and it is anticipated that this number will
exceed 9.7 25 billion (68%) by the year 2050. Globally, in recent time as of 2022, migration and
natural increase in population resulted in rapid growth of urban area where Tokyo-yokohama in
japan was the largest world urban agglomeration, with 37,732 thousand people living there. The
Russian capital, Moscow was the second largest city in same year (Statista Research Department,
2023).
The rapid growth in urban as a result of the migration of people from rural to urban areas in
search of opportunities brings about effectiveness in developing the urban areas it affects
adequate planning. In this case, schwars et al., (2018) came up with the idea of using a remote
sensing approach to integrate multispectral layer information factors such as population size
source destination, pull and push factors, and employment. Muhammadu, et al., (2020) used
remote sensing and GIS technique to detect land used and land cover in Minna between 1976 and
2016.
Comparative analysis of the environmental and socioeconomic impact on urban growth can be
done through the integration of spatial analyses because different locations within the urban
experience different transformations. Remote sensing and GIS technology can be applied in
many scientific fields to solve numerous problems. Example in solving environmental problems
(Bonham Carter 1994). Blaschce et al., (2008) Tner, et al., (2015) frohn and Lopez, (2017) and
Clifford (2016) suggest that GIS is not only limited to geographical applications but also
monitoring of people, infrastructural and movement.
Even though comparative analysis of migration growth impact from Africa to Europe and North
America receives the majority of attention, the majority of African migration occurs within the
continent as people seek economic opportunities. Therefore, in contrast to what the media would
have you believe, the majority of current international migration movements from Africa are still
predominantly intra-regional. Analysis based on the most recent data from the Global Bilateral
Migration database, the migration and visa databases from the Determinants of International
Migration (DEMIG) project (Flahaux and Den Hass, 2016), and census data from 15 ECOWAS
countries (Awumbila et al., 2014) indicates that the majority of African migrants persist in
migrating within the continent. The high rate of migration within and outside of Africa is said to
be caused by several factors. According to Marie-Laurence and Hein (2016), poverty, violent
conflict, and environmental stress frequently lead to mass migration and displacement in Africa.
Africa's urban growth rate is nearly eleven times higher than Europe's. Conflicts and natural
disasters, as well as the annexation and reclassification of rural areas and the spatial expansion of
urban settlements, are all major contributors to this rapid urbanization (UN HABITAT, 2016).
The internal migration in Nigeria is as a result of many factors which include; Employment
opportunities. The high deficit of employment opportunities in rural areas in most is a major
push factor and a driver of the increasing flow of people from rural to urban centers in Nigeria,
in search of employment opportunities. Cities such as Plateu, Niger, Lagos, Kano, Kaduna, and
Port Harcourt which are part of the nation's industrial hub, are cities of attraction with the large
employment opportunities that exist in these urban centres. Furthermore, the number of urban
centres has increased in number with the creation of states and local government areas in Nigeria
since her independence in 1960. Today the country has 36 states and a Federal Capital Territory
and 774 Local Government Areas. The capital and/or headquarters of each of these states and
LGAs have grown into urban administrative centres, with socio-economic services and sectors
that provide employment opportunities (Godwin, 2016).
The migration of rural people to urban area increases population which triggers the growth of the
urban area. Urban growth is the rate at which a city's population is increasing. Urban growth
extensively uses land for the placement of structures and impermeable surfaces which may result
from natural population growth, reclassification of the urban and rural systems, or rural-urban
migration as the main source of urbanization (Agbola, 2004). By 2020, 100 million people are
expected to reside in Nigeria's urban areas, according to projections. Although it has decreased
from 5.7% in 1985 to current rates of 4.0%, Nigeria's urban population growth rate is still much
greater than the country's total population growth rate (Onokerhoraye and Omuta, 1994). Urban
growth is an indicator of a country's ourr an area's economic condition as well as development.
The growth of urban areas is often influenced by certain factors such as surplus resources,
development of infrastructure, commercialization, education, and mining, among others (Ojo et
al., 2017).
Due to inadequate housing delivery system, urbanization is to blame for the dramatic increase in
cities' population growth rates that occurred in the 20th century as a result of rural-to-urban
migration (Aluko, 2010). According to National Geographic (2021), "Intensive urban growth can
result in greater poverty as local governments struggle to meet the needs of everyone, and Risks
from environmental hazards like flash floods might be increased as a result of urban growth.
Plateau State and Niger State are located in North- Central Nigeria, of Africa both are having
strategic drifts and economic growth. It is necessary to determine what major impacts of
migration in both states as Plateau is known for its favorable weather condition and the presence
of minerals and Niger is also known for its large cultivable land.
Due to the University of Jos' presence in the northern region, which attracted students and people
from all over the nation, as well as the fact that the city's central business district is located there
and is home to a variety of socioeconomic activities, Jos experienced rapid growth. As a result,
the populations of AngwaRogo, AngwaRukuba, Gangare, and Tudunwada increased.
Additionally, the religious strife from September 2001 to October 2010 caused unplanned and
unchecked growth in every direction, leading to significant urban growth and urban land use
(Adzandeh, et al., 2015). Similar to Lapai, where fast urban growth resulted in the loss of several
land uses, most notably agricultural lands. According to Etudaiye and Emigilati (2019), the
existence of the university Ibrahim BadamosiBabangida University is to blame for the city's
quick urban growth.
The direct effects of urban growth on natural, ecological, and social resources have raised
interest in urban sprawl study. Traditional census sources are very helpful in that they record
changes in the socioeconomic and demographic composition of cities, but they are not frequently
updated and lack spatial details(Adzandeh, et al., 2015).. On the other hand, remote sensing
makes a huge amount of data accessible with continuous temporal and spatial coverage and can
thus offer a successful method for monitoring urban growth and changes. In this study, the
application of remote sensing and GIS will be employed to investigate comparative analysis of
environmental and socioeconomic impacts of migration on urban growth in Jos North Local
Government Area and Lapai Local Government Area.
1.2
Statement of Research Problem
Migration as well as population growth helps the economy grow and gives industries and brands
an endless target market to grow their enterprises. On the other hand, overpopulation is a threat
that presents significant problems like high unemployment, a lack of infrastructure that results in
subpar living conditions, an increase in crime, an increase in pollution and waste, and the most
infamous of them all is the implacable housing shortage that major cities in Nigeria experience.
The pace of urban growth in Nigeria's towns and cities has continuously surpassed 2% annually
(UNDESA, 2019). As a result, Nigerian cities have rapidly grown in size, sometimes in an
unplanned and unregulated manner (Cities Alliance, 2007).
The National Population Commission (2015) noted that the majority of Nigeria's urban areas had
developed beyond their ability to support the environment and their current infrastructure. Data
from the National Population Census (2006), showed that the majority of Nigeria's urban centres
with tiny land masses have already reached their capacity limits or have very little room for
additional population growth.
The high influx of people into the jos from the rural areas to take advantage of the perceived
opportunities offered by these urban centres, without adequate planning and effective
management strategies to accommodate this influx by the government, results to serious pressure
on both the socio-economic supporting infrastructure and the environment. For instance,
urbanization has been identified as the cause of numerous environmental problems, which
include and not limited to air, water, land and noise pollution, deforestation, local climate
alteration, and traffic congestions, which ranges from local to the global scale. Simplarly, Lapai
has had significant urban growth, which has resulted in the loss of various types of landuse, most
notably agricultural land. Consequently, Despite predictions UNDESA (2019) indicate that by
2030 there will be approximately 5 billion people living in urban areas worldwide, little is known
about the future locations, sizes, and rates of urban expansion. There is the urgent need to assess
the environmental impact of these developments.
The impact of migration on the urban growth in north central have not been studied exhaustively.
Regarding relevant studies on Jos, and Lapai the available literature tend to focus on the
migration on rural area, food security (Alarima 2018; Gbemiga, 2015; Akinyele, 2015; Taylor
and Dyer, 2016;) less attention has been paid to the urban area. It is certain that the urban growth
occurring due to flow of thousands of migrant has a direct impact on the environment and
socioeconomic of the destination areas. Rural-urban migration can significantly influence the
welfare of the populations in the urban area.
This therefore, suggests that the necessity for accurate up-to-date data on the environmental and
socioeconomic impacts of migration on urban growth is needed to help policy makers in
addressing any negative consequences. Cooperation both within the state and across regions
which is crucial to addressing data gaps in migration hasn't been done. Again, due to a lack of
reliable, time-series data we do not have a clear picture of the extent and patterns of rural urban
migration within Nigeria. However, by piecing together the available information and combining
it with what is generally known about migration in the region, we can identify some broad trends
and dynamics, and dispel some myths
While attempting to provide the needed data, cost-effective, labor-saving methods are key.
Consequently, remote sensing and Geographic Information System (GIS) which come in the
form of geospatial datasets comprised of satellite imagery and census data. are employed in the
current work to ascertain and compare the level and impacts of these migrations on urban growth
in the two states of Niger and Plateau.
1.3 Aim and Objectives
The study will attempt to compare the changes in landuse/landcover due to urban growth and
socio-economic impact of migration in the two study areas, the plateau and Niger state. To
achieve the aim, the following specific objective will be pursued:
i.
Analyses of the urban land cover and existing land use changes in selected locations with
the States for 2005 – 2021.
ii.
Determine the spatial extent and rate of expansion of the study areas.
iii.
Examine the socio-economic impact of migration in the study area using the survey
method.
iv.
Examine the future impact of migration of the study areas by 2030.
1.4 Research Questions
i. What are the in-migration's impacts to the urban growth, notably in terms of land use in
Jos North and Lapai LGA between 2005 and 2021?
ii. What is the spatial extent and rate of expansion of settlement?
iii. What are the socio-economic effects of migration on destination areas?
iv. What will be the expected future scenario of migration in the study area by 2030?
1.5
Justification of the Study
Remotely sensed data taken with satellite imagery may be a strong alternative to provide insight
for researchers and city planners to anticipate spatial extent and rate of expansion of settlement
on environmental and socioeconomic impacts of migration on the changing landscape of
growing urban areas in developing countries around the world.
This study will conduct a critical analysis of the current migration, urban development, and
environmental protection policies that can help improve policy coherence by pointing out areas
of contradictions, or gaps. For efficient governance and integrated decision-making processes,
policy consistency is essential.
1.5.1 Policy Improvement
Implementing policies effectively is essential for obtaining long-term results. However, problems
frequently occur as a result of poor institutional coordination, a lack of technical experience, and
limited implementation capacity. Through the study, suggestions will be made to improve the
stakeholders' and government agencies' ability for implementation. Initiatives to enhance
capacity, better coordination techniques, and the distribution of sufficient resources. The findings
will show new direction for policy makers on the decisions and choice needed to take today, so
that new policies will be in a way resilient to the wide range of future uncertainties.
1.5.2 Performance Improvement
Similarly to policy improvement above applying the results of the study will improve operational
performance of:
i.
National Bureau of Statistics (NBS) the statistical information of migration impact on
urban area and socioeconomic survey
ii.
Urban planners would benefit from the scenario in this research in assessing urban
expansion under various land cover features and creating appropriate strategic actions.
1.5.3 Further Research
Urban growth is a big challenge confronting most the cities worldwide like Nigeria; people tend
to migrate from rural areas to urban areas due to a high rate of insecurity and also in search of
employment and other economic chances. Thus, the current study performed the comparison
between the two data types in order to inform future studies of the usability of land cover data,
particularly the National Land Cover Dataset and other data utilizing similar classification
methodologies. It is crucial to have data on migration that is disaggregated and includes
information at the local level in every part of the country will provide information that can serve
as base to social protections programs.
1.5.4 Body of Knowledge
Our understanding of mobility and diversity associated to migration has greatly benefited from
the study of migration. This study may accumulated a unique amount of information about the
impact of migration, the mechanisms by which it influence urban growth, and the general effects
of migration on both the migrants and the societies affected by it. Migration studies has
developed at the nexus of many different disciplines as a broad-based research subject. In
addition to disciplines like sociology, political science, anthropology, geography, law, and
economics, this also encompasses a wider range of subjects like health studies, development
studies, governance studies, and many more, will build on findings from this study as it will add
value to the existing literature.
1.6
Scope of the Study
The research scope of this study is comparative analysis of environmental and socioeconomic
impact of migration on urban growth in Jos north and Lapai LGA in North central Nigeria.
i. Temporal Scope: The period of temporal range of the study is 2005-2020, which was selected
because of the projection of UN that by 2020 Nigerians urban population will reach 108.7
million from 33.4 million in 2000. It’s also noted by Africapolis team estimates that the number
of settlement with 10,000 persons or more grew from 133 in 1960 to 438 in 2000 and expected to
reach 574 by 2020. In other words, urban growth in Nigeria is not simply a matter of population
growth in existing settlement; it is also involve the emergence of hundreds of new area with
urban population densities as result of migration.
ii.
Spatial Scope: This research will be conducted in Jos north Plateau and Lapai Niger
state which are located in north central geopolitical zone of Nigeria
iii.
Activity Scope: This study seek to have a cross sectional comparative analysis of socio-
economic activities of migrants in the destination area and the environmental changes that may
occur as result of the impact of migration in the two location, because the emphasis is on urban
growth.
1.7
Description of Study Area
1.7.1 Location, Position and Size
The study areas are situated in the North-Central geopolitical zone of Nigeria.
Plateau is the twelfth-largest state in Nigeria. Approximately in the centre of the country, it is
geographically unique in Nigeria due to its boundary of elevated hills surrounding the Jos
plateau.
The investigated area is in Angwan Rukuba district in Jos North Local Government Area,
plateau state Nigeria. It lies within latitudes 9°39'00''N to 09°50'00''N and longitudes 8°54'00''E
to 9°50'00''E. its average elevation is about 1500metre and covers the land area of about
850sq.km2 with a population of 3,954,581 (2006 census). Jos enjoys a more temperate climate
than much of the rest of Nigeria.
Niger is the largest state in Nigeria with a vast land mass of 86,000 km2. With Minna as its
capital city. Other major urban areas in the state include Suleja, Bida, and Kontagora. Lying on
latitude 3.20° east and longitude 11.30° north, the state shares a country border with the Republic
of Benin (West) and state border within Nigeria. These include the federal Capital Territory
(FCT) in the South-East, Zamfara (North), Kebbi (North-West), Kwara (South-West), and
Kaduna (North –East)
The investigated area isLapai Local Government area in Niger state. Lapai is bounded by the
Federal Capital Territory, Abuja. It is located between latitudes 9o 03, and 9o 05, and longitudes
6o 34, E and 6o 57, E. It is about 18 km west of old Lapai near the tributary or river Gurara
along Suleija road which is also about 56 km east of Minna, Niger state. It covers a total land
area of 3051 km2 with a population of 110127 (2006 Census). Lapai is located in the tropical
climate which is characterized by two distinct seasons in a year, the wet and the dry seasons.
Fig. 1.1: Map of the Study areas.
Source: National Centre for Remote sensing, 2022
1.7.2 Climate
a) Jos: The climate on the plateau is tropical but cooler than the surrounding lowlands.
Average temperatures range from 15.5℃ to 18.5℃ in the coolest months to 27.5℃ to
30.5℃ during the hottest months. Rainfall ranges from 2,000mm per year in the
southwest to 1,500mm or less in the drier northeast. Rainfall for the Jos metropolis
averages 1,411mm per year. Rainfall is highly seasonal, falling mostly between June and
august the wettest months. Moisture–bearing winds come from the south and west, and
rainfall is higher on the windward south-and west-facing slopes.
b) Lapai: the wet season is oppressive and overcast, the dry season is humid and partly
cloudy, and it is hot year-round. Over the course of the year, the temperature typically
varies from 65℉ to 94℉ and is rarely below 56℉ or above 101℉. Lapai experiences
extreme seasonal variation in monthly rainfall. The rainy period of the year lasts for 8.3
months, from March 5 to November 13, with a sliding 31-day rainfall of August, with an
average rainfall of 8.4 inches.
1.7.3 Soil, vegetation, and Hydrology
a) Jos: The plateau vegetation is open woodland with tall grasses but the native vegetation
has been considerably altered by human activities (Keay, 1953). Olowolafe and Dung
(2000) observed that Entisols, Inceptisols, Alfisol, and Ultisols are the major soils found
in the Jos area. Entisols are found on the hill and mountain crest, side slopes, and upper
foot slopes. They also occur on interfluvial crest and drainage channels. These are areas
where rates of soil erosion are faster than rates of pedogenic processes and so soils are
not allowed to form deep profiles. They are characterized by A-C or AC horizons with
structure less or weak granular to crumb structures. Inceptisols are soils that have
undergone little weathering, having cambric B-horizons with soil structure and a
significant amount of weatherable areas and alluvial minerals. They are found on the
upper foot slopes, middle foot slopes; interfluvial areas, and alluvial floodplains. Alf sols
and Ultisols are the soils found with argillic horizons in the area. They both contain
lateritic concretions with similar morphological characteristics but are distinguished from
each other on the account of their base saturation. They are found on the lower foot
slopes, and level plains. Vertigos are found in the depressions and the alluvial areas with
heavy clays but are minor soils in the area (Olowolafe and Dung, 2000).
b) Lapai: Three unique soil types are found in Niger state i.e. (ferruginous tropical soils,
hydromorphic soils, and ferrosols). Ferruginous tropical soils are the most dominant and
are derived from the basement complex and sedimentary rock like in kwara state. The
soil types coupled with favorable climate conditions support agricultural activities
throughout the year (Mayomi et al., 2014). Broadly speaking, the study areas fall within
the savannah communities known as the guinea savannah (Osunmadewa et al., 2016,
2014). The vegetation type of Niger State is the southern Guinea savannah. It is
characterized by woodland vegetation with relics of rainforests and tall grasses. Some of
the three species found in this region are Mangiferaindica (Mango), Ceibapentandra
(obeche), parkiabiglobosa, Danielliaoliveri (Mayomi et al., 2014).
1.7.4 socio-economic activities
a) Jos: It owes its origin to the introduction of tin mining on the Jos Plateau and railway
lines linking it with Port Harcourt and Lagos, thus bringing the area into the orbit of the
world economy. The tin mining led to the influx of migrants, mostly Hausas, lbos,
Yoruba's, and Europeans who constitute over half of the population of the town, making
it a highly cosmopolitan.
b) Lapai: Lapai serves as a market centre for the sorghum, yams, rice millet, shea nuts,
peanuts (groundnuts), and cotton grown by the area's Gbari and Nupe peoples. Swamp
rice is cultivated in the floodplains of the Gurara and the Niger rivers.
CHAPTER THREE
3.0
3.1
MATERIALS AND METHODS
Description of Materials (Data) Used
This research intends to compare the changes in landuse/landcover due to urban growth and
socio-economic impact of migration in the two study areas, the plateau (Jos north LGA) and
Niger state(Lapai LGA). It will be designed to collect information from all parameters that are
needed to solve the research problems stated in chapter one.
The types of data that that will be used comprise both primary and secondary.
Primary Sources of Data:
The primary data will be collected from the study area through the field work. It involves the
personal observation, structured questionnaire and the used of GPS,
3.1.1 Reconnaissance survey
This served as an initiative for the preparation of questionnaire, interview, measurements and
photographs. This will be carried out with the aim that efficient data could be gathered which
will be essential to the achievement of the objectives of this research.
3.1.2 Questionnaires and interviews:
This would involve the use of a well-structured questionnaire to obtain data on socioeconomic
status of migrants in the study area (destination). Researcher divide the questioners into five
parts as: Personal information, Status of migrants at current location, Status of current
expenditure, Factor behind migration and impacts of migration in the study area. The other
primary data that would be used for data collection is interview which could be conducted inperson. Observational method is going to be used as well for data collection for the study.
3.1.3 Secondary Data Sources
The data that will be used for this research as secondary data are Landsat sourced from the
archive of the United State Geological Survey Agency (https://earthexplorer.usgs.gov) for 2005,
2010, 2015 and 2021.
Data will all collected for the dry season period so that cloud-free photos could be used, in order
to achieve a seasonal effect. Numerous factors, including sensor calibration, air absorption,
scattering, and illumination geometry, frequently influence the spectral images that satellite
sensors acquire. In order to adjust the numerous surface reflectance fluctuations caused by the
acquiring system, radiometric and geometric corrections were applied to the images to be
acquired.
3.2
Method of Data Collection
All the necessary coordinates will obtained using a portable GPS unit, and the LULC will be
analyzed using remote sensing data from the USGS's Earth Explorer website (Landsat 5 TM,
Landsat 7 TM+, and Landsat 8), which cover the years 2005 through 2021. In order to
georeference the Landsat pictures that will be acquired in the years 2005, 2010, 2015, and 2021,
digital maps will be created for each of these years and georeferenced to a common UTM
coordinate system. There are numerous ground control points that will be evaluated and
compared with all the photos, including intersections of roads and agricultural plots, river
courses, and utility infrastructure. Ground truthing exercises in the form of a collection of
geographical coordinates via the use of Global Positioning Receiver(GPS) and direct observation
through transect walk will be used to collect primary data on LULC. Locations of the satellite
imageries in the GIS analysis will represent by the coordinates which served as the reference
system. This will be conducted to provide ground truth of vegetation and land use, which will be
was used as a reference tool to ensure and verify the accuracy of the satellite image interpretation
and to also determine the dynamics and impact of migration in the study area.
3.2.1 Sampling
A multi-stage random sampling technique will be used to select a sample size of 300
respondents. This sample size will be used as a result of limitations in accessibility and
availability of the respondents. In the first stage, a purposive selection of the two study area jos
north and Lapai local government area respectively. Secondly,in the study area hot spots will be
selected in study area and each local government area will be partitioned into wards and
settlement around the University area that are mostly affected by land use change and migration
from each state selected will be sampled. Thirdly, 150 household will randomly selected from
each study area, giving a sample size of 300 household (i.e., 150 respondents from each state).
The information will be collected using a well-structured interview schedule prepared will be in
English language but mostly interpreted in Hausa or Nupe (languages understood and spoken by
the respondents) during interview. The data needed include demographic characteristics of
respondents, factors influencing their migration and spatial growth of the study area, and impact
of the growth of on the environment. The questionnaires administered will analyze (i) determine
the driving force behind the growth, (ii) identify villages that have been absorbed by the urban
growth and those that would be absorbed in the next ten years if the rate of growth continues.
The quantitative data will be collected and will be entered in to the computer using SPSS version
21 package and micro soft Excel. Descriptive statistics such as tables, frequencies, percentages
and averages will be used.
3.2.2
Sample Size
The sample size for the study will be determined using the Taro Yamane techniques.
The formula stated as
n=
N
1 + N (e)2
Where n = desired sample size
N = population size under study
E = level of significance of error. Assumed to be 5%
I = constant
Therefore,
n=
N
1+N(e)2
3.3
Method of Data Analysis
3.3.1 Geospatial Techniques
The mapping depends on the use of computer-assisted interpretation of satellite imagery. Field
survey will be conducted; GPS coordinates will be captured in the field GIS will be used to
develop the geospatial map of degradation in the area. Change in Land use over time will be
detected by comparing the different level of degradation in the area. Agricultural land will be
delineated in order to determine the level of degraded agricultural land.
3.3.2 Software to use in this Research
Table 3.1 basically shows four (4) main software that will be use for this study Idrisiterrset for
image processing and classification and ArcGIS 10.9 for geo-referencing and digitizing map of
the study area.
Table 3.1 Software and their uses for this research
S/N
Software
Uses
1
ArcGIS 10.9
Georeferencing and digitizing of the map of study
area
2
IdrisiTerrset
Unsupervised image classification and training site
selection
3
Microsoft excel
Generate tabulated report, charts, trends and
descriptive display and analysis.
4
Microsoft word
for typing and editing of the work
Source: Author Analysis, 2023
3.4 Methodology for Each Objectives
3.4.1 Objective I
Analyses of the urban land cover and existing land use changes in selected locations within
the States for 2005 - 2021.
For quantifying and allocating temporal changes in four dates from 2005-2010 and 2015-2021
Land sat Imageries will be acquired. Determining socio-economic and environmental changes
provides important information about the repercussion of the urban growth. These datasets will
be imported to Idrisi Terrset. Digital image analysis will be carried out. The major image
processing steps will include image layer stacking, resampling, and image enhancement of the
datasets which are of utmost importance for LULC analysis. The types of land use land cover
feature that will be identified in this study includes; (built up area, agricultural land, vegetation,
water bodies).
The study area will be
extracted from the scene, and a supervised maximum likelihood
classification method will be carried out based on level 1 classification of Anderson et al. (1976)
Three basic operations namely image reconstruction to extract area of interest from the general
satellite scene, image enhancement to improve visual interpretation by increasing apparent
contrast among various features in the image and image classification to classify the various land
use and cover types as indicated on table 3.2
Table 3.2 Land use land cover classes
S/N
Features
Land use Description
1
Built-up area
Area uses mainly for settlement, it represented by where
houses are on lots of more than an acre on land. It will
include roads, market, schools etc
2
Agricultural land
Plantations, small farmlands typical devoted to agriculture,
the systematic and controlled use of other forms of life
particularly the rearing of livestock and production of
crops to produce food for humans.
3
Water bodies
Is any significant accumulation of water, generally on
planet surface. A body of water does not have to be still or
contained; rivers, streams, canals and other geographical
feature where water moves from one place to another are
also considered bodies of water.
4
Vegetation
Vegetation area is area with distinct plant types,
determined by climate, soil, drainage, and elevation. it is a
general term without specific reference, life forms,
structure, spatial extent, or any other specific botanical or
geography characteristics like Forest areas, grasslands,
shrubs and others
5
Bare surface
The solid surface of the earth that is not permanently
covered by water. The vast majority of human activity
occurs in land areas that support agriculture, habitat, and
various natural resources.
Source: Adapted from Anderson, 1984
3.4.1.1 Image Registration
The image imported into ArcMap 10.9 for registration. The image reader extension (Tiff images)
will be activated to allow the software to read Tiff image files. The image will be geo-ferenced in
ArcMap due to its flexibility. Subsequently the study area will cut from the whole image for
four-time period. They will be broken into subset in ArcMap and saved as Tiff images.
3.4.1.2 Land cover Classification
Image classification will be done following different process; firstly the images will be imported
into Idrisi 32 for classification. Each cluster of observations is a class. A class occupied its own
area in the feature space i.e a specific part of the feature space corresponds to a specific class.
Once the classes have been defined in the feature space, each image pixel observation can be
compared to these classes and assigned to the corresponding class. Classes to be distinguished in
an image classification need to have different spectral characteristics, which can be analyzed by
comparing spectral reflectance curve. The only limitation of image classification is that if classes
do not have distinct clusters in the feature spaces, such image classification does not give reliable
results.
Training site will be generated on the images by on-screen digitizing for each land cover classes
derived from image of different band combination. A supervised (full Gaussian) maximum
likelihood classification will be implemented for the four images. This is due to the fact that the
operator has familiarized himself with the study area through dedicated field observation,
whereby the spectra characteristics of the classes in the sample area has been identified. Ground
truth information will be use to assess the accuracy of the classification.
The methods of data analysis adopted in this study are.
i.
Calculation of area in hectares of the resulting land use types for each study year will
be generated.
ii.
Image differencing to provide for change analysis through differencing of image
pairs, to correlate the scale of each year imagery
iii.
The first two methods will be use to identify changes in the land use types. The
comparison of the land use statistics assist in identifying the percentage change, trend
and rate of change. Percentage changes to determine the trend of change will then be
calculated by dividing observed changes by sum of changes multiplied by 100.
3.5 Objective Four: project the future impact of migration on land used /landcover.
In order to achieve this objective, Markov chain analysis will be used for this study. Markov
Chain Analysis is frequently used to simulate complex processes such as land use change. It is
mainly used to study the transition probability between an initial state and a final state to
determine the transition trend among different land use states (Lipinget.al, 2018). The model
simulation process mainly produces a land use area transfer matrix and a probability transfer
matrix to predict land use change trends. Here, the Markov chain model could be described as a
set of states, S = { 𝑆0 , 𝑆1 , 𝑆2 , … , 𝑆𝑛 }, assuming that the current state is 𝑆𝑡 , and then, it changes to
state 𝑆𝑗 at the next step with a probability denoted by transition probabilities 𝑃𝑖𝑗 . Thus, state 𝑆𝑡 +1
in the system could be determined by former stage 𝑆𝑡 in the Markov chain using the formula;
𝑃11
𝑃𝑖𝑗 = [ ⋮
𝑃𝑛1
⋯
⋱
⋯
𝑃1𝑛
⋮ ]
𝑃𝑛𝑛
(7)
𝑛
(0 ≤ 𝑃𝑖𝑗 < 1 𝑎𝑛𝑑 ∑ 𝑃𝑖𝑗 = 1, 𝑖, 𝑗 = 1, 2, … , 𝑛)
𝑗=1
𝑆𝑡+1 = 𝑃𝑖𝑗 × 𝑆𝑡
Where; 𝑃𝑖𝑗 is the state transition probability matrix and n is the land use type number; 𝑆 is land
use status, t; t+1 is the time point. Thus in this study, the Markov chain analysis will be used to
model the LULC change of the study area for 2030.
3.3.4 Accuracy Assessment:
Because the data deals more with nature, the user of LULC maps need to know how accurate the
maps are in order to use the data more correctly and efficiently. According to Anderson et al.
(1984) the minimum level of interpretation accuracy in the identification of land use and LULC
categories from remote sensing data should be at least 85%. The most widely promoted
classification accuracy is in the form of error matrix which can be used to derive a series of
descriptive and analytical statistics.
3.6
Objective two: Examine the socio-economic impact of migration in the study area
using the survey method.
The quantitative data will be collected through household survey, this will be imputed in to the
computer using SPSS version 21 package and micro soft Excel. Descriptive statistics such as
tables, frequencies, percentages and averages will be used.
3.7 Method of Data Presentation
The data are presented in histograms, bar charts, pie charts, figures, plates, imageries and tables
using descriptive method of statistics.
3.8
Expected Results
By the end of this study, the following outcomes are expected;
i. Current environmental impacts of in-migration, particularly regarding land use and
landcover changes will be obtained and presented as maps and in table form.
ii. Socio-economic effects of migration on destination areas in the study area.
iii. The expected future scenario of urban growth as result of in-migration in the study area
by 2033.
iv. Two Journal papers for publication
v. The special project report
vi. The degree certificate.
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