International Journal of Advancements in Research & Technology, Volume 4, Issue 7, July -2015
ISSN 2278-7763
116
GEOSPATIAL MODELING AND MULTI TEMPORAL ANALYSIS OF URBAN DEVELOPMENT
TRENDS IN WARRI TOWN DELTA STATE, NIGERIA
Ojanikele, W.A., Igbokwe, J.I., Ojiako, J.C.
ABSTRACT- This paper examines the use of GIS and Remote Sensing in geospatial modeling and multi temporal
analysis of urban development in Warri town from 1987 to 2013. Thus the study is to carry out a geospatial
modeling and multi-temporal analysis of development trends, thereby detecting the changes that have taken place
between these periods. Three Landsat images, Landsat 5TM (1987), Landsat 7ETM+ (2002) and Landsat 8 OLI
(2013) were acquired, classified and change detection analysis was performed to determine the multi-temporal urban
changes between the years. The result indicated a rapid growth in built-up area between 1987 and 2013. Built up
area had 155590200m² in 1987, then increased to an area of 249725653.3 m² in 2002, then increased to an area of
334934100m² in 2013 indicating a stage of modern industrialization and urbanization. It was also observed from the
trend of change, that built up area had an annual rate of change of 1.55% from 1987 to 2002 and 1.81% from 2002
to 2013 and may likely continue to increase gradually further down the years. It was further recommended that
studies on the impact of urban development in be carried out in order to determine effects of rapid urbanization in
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Warri town and that Land Consumption Rate and Land Absorption Coefficient should be incorporated in future
research studies since built up area expansions is a combination of anthropogenic activities and one that also affects
the other classes (socially and economically).
Keywords: Change Detection, Land cover / Land use, Remote Sensing, Urban Development
1.
INTRODUCTION
Urban landscapes are composed of a diverse assemblage of materials (concrete, asphalt, metal, plastic shingles,
glass, water, grass, shrubbery, trees, and soil) arranged by humans in complex ways to build housing, transportation
systems, utilities, commercial and industrial facilities, and recreational landscape (John, 2007). Urban sprawl is
widely used in many disciplines dealing with urban development and urban form (Ezeomedo, 2013). Unprecedented
population growth coupled with unplanned development activities has led to urbanization which takes place along
highways or surrounding the city and in a rural country side (Theobald, 2001).
Warri has witnessed remarkable expansion, growth and developments such as building, road construction,
deforestation and many other anthropogenic activities. This has therefore resulted in increased land consumption and
a modification and alterations in the status of her land use land cover over time without any detailed and
comprehensive attempt (as provided by a Remote Sensing data and GIS) to evaluate this status as it changes over
time with a view to detecting the land consumption rate and also make attempt to predict same and the possible
changes that may occur in this status so that planners can have a basic tool for planning. It is therefore necessary for
a study such as this to be carried.
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International Journal of Advancements in Research & Technology, Volume 4, Issue 7, July -2015
ISSN 2278-7763
2.
117
STUDY AREA
Warri is one of the hubs of petroleum related businesses in the southern Nigeria. It is a commercial city in Delta
State Nigeria; its geographical coordinates are 5° 31’ 0”E latitude and 5° 45’ 0” N, longitude with a population over
311,970 people according to the national population census figures city for 2006. The people that reside in Warri are
mainly the Urhobos, Isokos, Itsekiris, and Ijaws with other national ethnic groups settling here. See location map of
Warri in the Nigeria map below
A
B
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C
Fig 2 (a) Map of Nigeria (b) Map of Delta State (c) Map of Warri Town
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International Journal of Advancements in Research & Technology, Volume 4, Issue 7, July -2015
ISSN 2278-7763
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118
METHODOLOGY
Three Landsat images, Landsat 5 TM (1987), Landsat 7 ETM+ (2002) and Landsat 8 OLI (2013) were acquired,
from (http://glovis.usgs.gov), sub-mapped and classified into four classes namely Built up Areas, Swamp, Forrest
and Water bodies using unsupervised classification method. Then the classified images of the different years were
overlaid together and post-classification change detection analysis was performed to determine the multi-temporal
urban changes between the years.
4.
RESULTS
The classified maps for 1987, 2002, 2013 was generated shown in figure 4
A
B
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C
Fig 4 (a) Land cover /Land use map of 1987, (b) Land cover / Land use map of 2002, (c) Land cover / Land use map
of 2013
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International Journal of Advancements in Research & Technology, Volume 4, Issue 7, July -2015
ISSN 2278-7763
119
The classification results shown in table 4.1 below indicates the land cover/land use classes in 1987 as: Forrest
(46.25%), built up area (32.92%), swamp (15.80%) water body (5.02%) respectively. In contrast, from 1987 to 2002
Forrest decreases from 46.25% to 31.94%, with built up area increasing from 32.92% to 52.86% and swamp
decreasing from 15.80% to 9.63% while water body increased from5.02% to 5.57% .
Then from 2002-2013, built up area increased massively from 52.86% to 70.86% while Forrest decreased further
from 31.94% to 11.37% and swamp increased also from 9.63% to 12.61% with water body also decreased slightly
from 5.57% to 5.16%, these stats reflects the multi-temporal change in Warri from 1987-2013.
Table 4.1 Summary of Land cover/Land use Area for 1987, 2002, 2013
Class Type
1987
2002
2013
Area (m²)
%
Area (m²)
%
Area (m²)
%
Built up Area
155590200
32.92
249725653.3
52.86
334934100
70.86
Forrest
218632500
46.25
150889651.9
31.94
53759700
11.37
Swamp
74698200
15.80
45517271
9.63
59604300
12.61
Water Body
23747400
5.02
26295578.4
5.57
24370200
5.16
472668300
100
472428154.6
100
472668300
100
TOTAL
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4.1 POST CLASSIFICATION CHANGE DETECTION
Post classification change maps were generated in order to determine the changes that may have occurred between
the years shown in figure 4.2(a) and (b)
a
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International Journal of Advancements in Research & Technology, Volume 4, Issue 7, July -2015
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b
4.1.1 Summary of Change between 1987 and 2002
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The total area of water body in 1987 was 23747400m². In 2002, the total area of water body unchanged was
16761387.9m² (3.55%), losing 5711538.9m² (1.21%) to swamp, 668481.8m² (0.14%) to Forrest, 593957.8m²
(0.13%) to built up area while swamp had a total area of 74698200m² in 1987, losing 8845605.6m² (1.87%) to
water, 32412227.1m² (6.87%) to Forrest, 3851283.4m² (0.82%) to built up area, with an unchanged area of
29478989.3m² (6.65%) in 2002. Forrest had a total area of 218632500m² in 1987, losing 255858.8m² (0.05%) to
water body, 9385142.6m² (1.99%) to swamp 96686787.9m² (20.49%) to built up area, while 111659398.3m²
(23.67%) was unchanged. Built up area had a total area of 155590200m² in 1987, losing 364903.3m² (0.08%) to
water body, 834383.8m² (0.18%) to swamp, 5840889.8m² (1.24%) to Forrest while having an unchanged area of
148439905.9m² (31.46) in 2002.
4.1.2 Summary of Change between 2002 and 2013
The total area of water body in 2002 was 26295578.4m². In 2013, the total area of water body unchanged was
16677726.2m² (3.53%), losing 8398868.1m² (1.78%) to swamp, 407140.3m² (0.09%) to Forrest, 744021.0m²
(0.16%) to built up area while swamp had a total area of 45517271m² in 2002, losing 5146009.9m² (1.09%) to
water, 4764861.6m² (1.01%) to Forrest, 8405366.1m² (1.78%) to built up area, with an unchanged area of
27093817.1m² (5.74%) in 2013. Forrest had a total area of 150889651.9m² in 2002, losing 1386916.9m² (0.29%) to
water body, 20143800.0m² (4.27%) to swamp, 93953566.7m² (19.91%) to built up area, while 35096713.3m²
(7.44%) was unchanged. Built up area had a total area of 249725653.3m² in 2002, losing 1144866.4m² (0.24%) to
water body, 3878696.8m² (0.82%) to swamp, 13299781.5m² (2.82%) to Forrest while having an unchanged area of
231248590.3m² (49.02) in 2013.
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International Journal of Advancements in Research & Technology, Volume 4, Issue 7, July -2015
ISSN 2278-7763
121
Conclusions
This research work demonstrates the ability of Remote Sensing and GIS in capturing spatial-temporal data. Attempt
was made to capture as accurate as possible four land use land cover classes as they change through time. The four
classes were distinctly produced in contrast to urban development for 1987, 2002 and 2013 An attempt was also
made at generating a the trend analysis to determine the trend of change percentage and annual rate of change.
The result shows a significant growth in built-up area between 1987 to 2013 showing a stage of modern
industrialization and urbanization with water bodies slightly increasing from 1987 to 2002 and decreasing between
2002 to 2013 along with Forrest and swamp classes, this can be said in conclusion that these classes decrease as
built up area increases along the years, giving way in order for urbanization to grow.
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Theobald, D.M. (2001), “Quantifying urban and rural sprawl using the sprawl index”,Paper Presented At The
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