An Integrated Remote Sensing and GIS in Monitoring Landuse and Land Cover Change in Egbeda Local Government Area, Oyo State, Nigeria ()
1. Introduction
Land use change is arguably the most pervasive socio-economic force driving change and degradation of ecosystems. Deforestation, urban development, agriculture, and other human activities have substantially altered the Earth’s landscape. Such disturbance of the land affects important ecosystem processes and services, which can have wide ranging and long term consequences (Bala, 2017).
According to Wu (2008), farmland provides open space and valuable habitat for many wildlife species. However, intensive agriculture has potentially severe ecosystem consequences. Czech, Krausman and Devers (2000) pointed out that habitat destruction; fragmentation and alteration associated with urban development have been identified as the leading causes of biodiversity decline and species extinction.
Efficient urban information system is a vital prerequisite for planned development and there is need to adopt remote sensing and geographic information systems approach in urban development and monitoring process for implementing pragmatic plan. This plan must integrate a spatial model using remote sensing and GIS database (Balogun, 2009). Satellite image data provides the potential to obtain land cover information at more frequent intervals which are more economical than those obtained by traditional methods (Martin & Howarth, 1989; Treitz, Howarth, & Gong, 1992; Trotter, 1991).
Extensive research efforts have been directed to urban change detection by using remotely sensed imagery (Yeh & Li, 1996; Yang & Liu, 2005; Loft, 2001; Adebayejo & Abolade, 2006). In the studies carried out by Ramadan, Feng and Cheng (2004) in Shaoxing City in China using satellite imageries for the year 1984, 1997 and 2000, one of the goals of the study was to produce a land use map of Shaoxing City and its surroundings. The result shows that there are undoubtedly a lot of changes that occurred between 1984 and 19997 when compared with those of 2000. Eiter and Potthoff (2007) conducted study that focuses on understanding the driving forces affects land use changes in Norway. He found out that better knowledge was achieved when the source of the force and the force itself are separated from each other. Similarly, Brandt et al. (1999) conducted a study about land use development in urban rural areas in Denmark, focusing on changes in the urban fringe and marginalization of agricultural areas. He identified the five driving key factors that influenced the categorization which are technology, natural environment, socio economic environment, policy and culture. These categories have a general character, which can lead to less detail information about the driving forces in a specific area. Andrej, Rosemarie and Tim (2015) studied suitability in land management in Northern Germany and concluded that differences in attitudes toward suitability were driven to a great extent by differences in the regional socio-economic setting particularly with regard to production issues. Balayneh and Eyasu (2021) investigated the driving forces influencing the landuse and land cover changes in Shenkolla watershed in South Central Ethiopia. The results disclosed that Shenkolla watershed has changed significantly during four decades between 1973 and 2017. The observed changes indicated that agricultural expansion, policy change and social unrest, population pressure, shortage of farmland, and biophysical factors were major driving forces of land use and land cover changes. Hundu et al. (2021) established the uniqueness of satellite remote sensing and GIS technique in producing accurate land use and land cover maps and changing statistics for Katsina-Ala Local Government Area Benue, Nigeria. The results clearly show constant positive increase in built-up area, and the farm land but a decrease in forest land cover. In response to the increasing urbanization, many local governments have imposed strict land use control in Oyo State. Some of the efforts have been quite successful in slowing down development. Results from this research will assist the public, land use planners, and policy makers to anticipate and plan for the future.
The objectives of this study include to:
1) Analyze the land use and land cover change of the study area at different times (1984, 2006 and 2018).
2) Analyze the driving forces responsible for landuse change.
3) Predict the land use change and its development in the study area.
2. The Study Area
The study area is Egbeda Local Government Area of Oyo State. It is located on the Longitude 30˚56'54.753''E and 40˚8'58.585''E and Latitude 70˚27'23.532''N and 70˚18'34.578''N. The Local Government (Egbeda L.G.A.) shared boundary with Ona, Ara L.G., Lagelu L.G., Ibadan North East L.G. and Irewolede L.G. in the State of Osun (see Figure 1).
Egbeda is one of the oldest communities in the ancient city of Ibadan that originated from Awaye compound/village. The Awaye people were known to be warriors, farmer, and accommodating in nature. The population of Egbeda Local Government Area, according to 2006 population census reached the size of 283,643 (NPC, 2006). In projected 2016 census, it rose to 398,500. This growth has been more phenomenal since the creation of the Local Government Area. The annual average temperatures range between 23.9˚C and 28.3˚C, and its mean annual relative humidity is about 77.1%. It is located within the tropical rain forest region of Nigeria where rainfall is high throughout the year. The area has an undulating terrain underlain by metamorphic rocks and characterized by
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Figure 1. Maps of Nigeria showing Oyo State and Egbeda local government area.
two types of soils, deep brown clay soils and sandy soils. These soils have laudably supported the growing of cash crops such as cocoa, bread fruit, palms and cassava. Others common crops which are mostly, staple food include cocoyam, sugar cane, banana, plantain and vegetables. The topography of the area rises up to 500 meters and above the mean sea level in some places with the highest hill occurring in the northern part of the mapped area (Olatunji, 2022).
3. Data Acquisition and Method
This study was interested in the urban land use and land cover change of Egbeda Local Government Area, Oyo state. The methods employed for data analysis include study area mapping, mapping from remotely sensed images of land use and land cover change, driving forces and future change/development mapping using IDV analysis tool of geo-statistical interpolation. To achieve this, images of Egbeda Local Government Area, Oyo State were acquired for 1984, 2006 and 2018. The images are geometrically corrected and ground control point obtained through intensive ground surveys permitted the co-registration of all images to Universal Transverse Mercator (UTM). The Satellite imageries were made to pass through process of image enhancement, geo referencing, resampling, and image classification. A supervised classification with a Maximum Likelihood analysis was successful after creating five regions of interest with five training sites each. The map produced were: Land use/cover 1984 from TM Landsat image, Land use/cover 2006 from ETM+ Land sat image and Land cover 2018 from OLI Land sat image, based on built-up, cultivated land, bared land, natural vegetation and water body categories as regions of interest. Post classification was done using classified images for the purpose of confusion matrix, change detection and change statistics. Both classified and post classified images were converted to vector and exported to ArcMap 10.1 as shape files for statistical analysis and mapping.
4. Results and Discussion
The findings of this research shows that underlying drivers of land use an land cover are specific to a location as revealed by other similar studies elsewhere (Geist & Lambin, 2002; Lepers et al., 2004; Rudel et al., 2005). The major driving factor is environmental consequent to the expansion. There are dense agglomerations of people and economic activities associated with urban expansion impose pressure on the environment that can shape the physical landscape and the function state of the ecosystem. Another driving factor is the social ills such as unemployment, poor quality of housing, traffic congestion, poverty, poor standard of living, overcrowding which put pressures on the local government to provide basic social amenities and infrastructure for the growing population.
Another driving force of urban expansion is loss of open space which has been eaten up by this rapid expansion.
Deforestation and colonization of adjacent farm lands through uncontrolled urban expansion is another serious factor. This is likely due to population increase and therefore pressure on lands for food.
The changes that occurred in Land use and Land cover in Egbeda Laocal Government Area, Oyo State for the past 34 years are shown in the following landuse and land cover maps, tables and charts for 1984, 2006 and 2018. However, the total area of each of the landuse and land cover was calculated in 1984, 2006 and 2018. Table 1 is the summary of the area coverage in areas and percentage of land use and land cover types under study which includes the total area covered by the classification.
Figure 2 and Table 2 show the result of the land use landcover for the year 1984 with bare surface, cultivation, built up, vegetation and water body as 0.08%, 10.57%, 9.81%, 78.58%, and 0.96%, respectively. The vegetation cover was much intact with fewer patches of cleared/cultivated areas. Also, the built-up area was characterized with scatter settlement pattern with few clusters along the two (2) major roads.
Figure 3 and Table 3 show the result of the land use land cover for the year
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Figure 2. Classified Land use/cover Map of the study area for the year 1984.
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Table 1. Trend showing the landuse/cover 1984, 2006 and 2018 (km2).
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Figure 3. Classified Land use/cover Map of the study area for the year 2006.
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Table 2. Change detection for the year 1984.
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Table 3. Change detection for the year 2006.
2006 with bare surface, cultivation, built up, vegetation and water body as 0.00%, 13.42%, 21.42%, 64.03%, and 1.13%, respectively. The settlement as at 2006 became more clusters towards the central business area of Egbeda Local Government, Oyo State. However, linear settlement was also observed towards the two major high ways.
Figure 4 and Table 4 show the result of the land use landcover for the year 2018 with bare surface, cultivation, built up, vegetation and water body as 0.00%, 3.56%, 32.80%, 62.41%, and 1.23%, respectively. In 2018, Urban sprawl was observed as shown in Figure 4 as it was also observed that there were more scattered patches of settlement along the two (2) major roads than observed from the two previous years.
Figure 5 and Table 5 below show 1984 and 2006 Classified Image, it was observed that Built-up area gained from Bare Surface, Cultivation, Vegetation, and
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Figure 4. Classified Land use/cover Map of the study area for the year 2018.
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Table 4. Change detection for the year 2018.
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Figure 5. Classified Land use/cover loss and gain map of the study area for 1984 to 2006.
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Table 5. Trend showing 1984 to 2006 (km2).
Source: Field work, 2018.
Water Body; 0.1611 (km2), 5.2965 (km2), 27.4167 (km2), 0.0017 (km2) respectively. It shows that in 1984, Built up area were 25.3836 (km2), while in 2006, Built up area were 55.1709 (km2). This shows that from 1984 to 2006, Built-up area gained 29.7873 (km2) and this shows how the trend of land use and land cover has been over the years.
Figure 6 shows a diagram representing categories of gain, loss and stable change that occurred in the period of 1984 to 2006, whereby stable change has the highest numbers, followed by loss change and lastly gain with the lowest numbers.
Figure 7 and Table 6, show that from the Classified Image of 2006 and 2018, it shows that Built up gained from Bare Surface, Cultivation, Vegetation, and Water Body; 0 (km2), 8.0307 (km2), 21.310 (km2), and 0.0189 (km2) respectively. In 2006, built up area were 55.1709 while in 2018, built up area were 84.5118. This shows that from 2006 to 2018, built up gained 29.3409 (km2) and this shows how the land use has been over the years.
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Figure 6. Land use/land cover loss and gain chart in the study area for 1984 to 2006.
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Figure 7. Classified land use/land cover loss and gain map of the study area for 2006 to 2018.
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Table 6. Trend showing 2006 to 2018 (km2).
Figure 8 shows a diagram representing categories of gain, loss and stable change that occurred in the period of 2006 to 2018, whereby stable change has the highest numbers, followed by loss change and lastly gain with the lowest numbers.
Figure 9 shows the three years tend pattern from 1984 to 2018. In 1984, bare surface, cultivation, built up, vegetation and water body measures 0.0788%, 10.5660%, 9.8148%, 78.5841%, and 0.9563%, respectively. In 2006, bare surface lost from 0% to 0%, cultivation gained from 10.5660% to 13.4195%, built up also gained from 9.8148% to 21.4131%, vegetation lost from 78.5841% to 64.0343% while water body also gained from 0.9563% to 1.1331%. In 2018, bare surface remains the same, cultivation and vegetation lost from 13.42% to 3.6%, and 64.03% to 62.41% respectively, while built up and water body all gained from 21.41% to 35.80% and 1.13% to 1.23 % respectively.
It shows that there is a continuous increase in built up area from 25.4565 Km2 in 1984 to 84.5118 Km2 in 2018. This shows that land use from 1984 to 2018 with an increase of 59.0553 Km2, this shows that there is an increase of more than 50% within those years.
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Figure 8. Land use/land cover loss and gain chart in the study area for 2006 to 2018.
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Figure 9. Classified Land use/cover loss and gain map of the study area for 1984, 2006 and 2018.
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Figure 10. Classified Image showing the Overlaying of three years built up area in Egbeda Local Government Area.
Figure 10 shows the future land use and land cover change prediction. It shows the direction and pattern at which the land use is taking. The overlay of the classification results provided the actual change detection analysis and direction of the landuse and land cover which is along the two (2) major roads towards the North and South of Egbeda Local Government area, Oyo State.
5. Conclusion and Recommendations
The study has been able to determine land use and land cover changes for the past 34 years in the study area. The study employed the use of remote sensing and Geographical Information Systems (GIS) to study the land use and land cover change of Egbeda Local Government, Oyo State, Nigeria. Landsat TM and Enhanced Thematic Mapping (ETM+) imageries of 1984, 2006 and 2018 were used to analyze the landuse and land cover change of Egbeda Local Government Area, Oyo State. The results of the built-up area increase from 25.4565 areas Km2 (9.8%) in 1984 to 55.1709 areas Km2 (21.4%) and 84.5118 areas Km2 (32.8%) in 2006 and 2018 respectively. It is clearly seen that vegetation decreased from 203.823 areas Km2 (78%) in 1984 to 164.98644 areas Km2 and 160.8039 areas Km2 in 2006 and 2018 respectively. Also the analysis shows that the change in the land use and land cover was noticed as the encroachment of the built-up areas into cultivation area due to demand for shelter and cultivation replacing the vegetation due to farming activities. The study therefore recommends that there should be regular monitoring of urban area using dynamic method such as Remote Sensing and Geographic Information System so as to provide current and accurate data for the urban managers. This will help to forestall the development of slums, and squatter settlement. Information and consultation programs should be established in order to improve awareness to the public and government about the implications of land use and land cover changes in an area. Government should explore and experiment private-public participation in the provision of urban services and infrastructure.
Authors’ Contributions
All authors of this work performed substantial contributions to conception, design, analysis and writing and design of this article. All authors have read the manuscript for important intellectual and approved the final version for publication.
Acknowledgments
We acknowledge Olatunji Sharafdeen Bolaji our M.Tech. student, in the Department of Remote Sensing and GIS, Federal University of Technology, Akure whose final project provided data and information for this paper.