Ethiopian Journal of Environmental Studies & Management 9(6): 780 – 792, 2016. ISSN:1998-0507 doi: http://dx.doi.org/10.4314/ejesm.v9i6.10 Submitted: August 22, 2016 Accepted: November 10, 2016

SPATIO-TEMPORAL ANALYSIS OF LANDUSE DYNAMICS IN UPPER OPA CATCHMENT, SOUTHWEST NIGERIA

*IBITOYE, M.O., 1 ABOYEJI, O.S. 2 AND ADEKEMI, S.O.A. 2 1Department of Remote Sensing and Geoscience Information System, Federal University of Technology, Akure, Nigeria 2Regional Centre for Training in Aerospace Surveys (RECTAS), Ile-Ife, Nigeria

Abstract This study explored the use of geospatial techniques to assess land use change within upper Opa catchment area in Ile-Ife, Osun State, Nigeria for a period of 28 years between 1986 and 2014. To accomplish this, Landsat TM 1986, ETM 2002 and OLI 2014 were acquired from the USGS Earth Explorer in Global Land Cover Facility (GLCF) web site and subjected to supervised classification using the Anderson classification Scheme. Six land use/landcover classes were identified: Built-up, Bareland, Riparian, Forest Vegetation, Rock Outcrop and Water body using ENVI 5.1 Software. A change detection analysis of LULC was carried out to provide the necessary understanding of changes over the period and prediction for expected change in future was carried out. Result showed remarkable changes in all the land uses. For instance, Built-up increased from 7.01 km 2 (6.4%) in 1986 to 11.92 km 2 (10.8%) and 20.86km 2 (18.8%) in 2002 and 2014, respectively while vegetation reduced from 61.72km 2 (61.30%) in 1986 to 55.41km 2 (50.2%) in 2014. The study further confirmed that if the current rate of reduction in the vegetation cover is allowed to continue unabated, there may be no vegetation again in the area in the next 30 years, thus, jeopardizing the need of the future generation and causing greater harm to the environment. In view of the above, efforts should be made to control land use activities within upper Opa catchment by enforcing the “Green Policy” of the Environment Act of the Federal Government of Nigeria which will check the indiscriminate land uses particular the encroachment of other uses into vegetation land.

Key words: Opa Catchment, LULC, Anthropogenic activities, Southwestern Nigeria

Introduction about gross entry into areas which was Many developing countries of the previously occupied by natural forests. world today could be said to be suffering People are now concern about the raising from serious environmental degradation problem as a result of deforestation, resulting from human and natural causes. which is the temporary or permanent An important human factor is rapid clearing of forest either for agriculture growth in population which has brought purpose or any other purposes. Since

*Corresponding Author: Ibitoye, M.O. 780 Email: [email protected]

Spatio -Temporal Analysis of Landuse Dynamics ...... IBITOYE et al. prehistoric times, forest serves various such as Osun state. It is a problem purposes and will continue to do so as because of the present experience in long as life continues on this planet climate change, biodiversity loss and (Abbiw, 1990). The forest houses and pollution. Knowing that forest protects game, stabilizes the communities have a vital role to play in environment, prevents soil erosion and maintaining balanced eco-system of the serves as a source of medicinal plants for world, still pressures from the exploding curing diseases. Forests also provide the population and the subsequent growing greatest diversity of plant life, yet they needs of industries, food, fuel wood, continue to be felled through logging and fodder, timber activities etc., depletion faming activities and at times through and degradation of forests and burning and they are seldom replaced. In subsequently severe negative changes in many parts of Nigeria, the forestry sector ecosystem (Andreas and Hugh, 2009; contributes significantly to the internally Omiyale, 2001). Omiyale (2001) was of generated revenue (IGR) in some state the opinion that if 6.1 million hectares of (Akindele, 2001). Ajayi (2001) opined tropical forests are destroyed annually in that between 1996 and 2001, this sector 170 years, the total tropic forest would generated N608, 460,455.78 from the have completely wiped out. sales of timber alone. Uncontrolled human (anthropogenic) Nigeria is about 923,770 km 2, and activities has led to significant forests accounted for only 9.61%, while modification of the natural biodiversity in grassland 48.53%, fresh and inland Southwestern Nigeria as in the case of wetlands 1.05%, tree crop plantations upper Opa catchment, which has led to 0.3% and farmlands 20.33% (Omiyale, abrupt change in land use and land type 2001). He observed that an estimate of without adequate consideration for 43.48% of the total forest ecosystem in sustainable developments. Monitoring Nigeria has been destroyed by human and assessing the effect of anthropogenic activities between the period of 1980 and activities especially those that has to do 1990. Popoola and Akande (2001) argued with land use changes is helpful in order that the annual rate at which forest is to catalogue the diverse effects of this been destroyed for farming and other land use change on forested areas and anthropogenic activities averagely is other human endeavours. Hence, about 3.5% and forest area losses from information on land use and possibilities 14.9 million to 10.1 million hectares for their optimal use is essential for the annually. In 2001, about 5.34% of the selection, planning and implementation total land area of Nigeria was under of land use schemes to meet the forest as against the international increasing demands for basic human requirement where 25% of the total land needs and welfare without jeopardizing area of each country was mandated to be the need of future generation. under forest (Popoola and Akande, Several studies have been carried out 2001). on LULC in various parts of the world Land expansion and modernization (Adeoye, 2012; Aduah and Aabeyir, has become a major problem in Nigeria 2012; Fernandez and Dhorde, 2014; especially, in the tropical forest region Oyinloye and Oloukoi, 2012; Shiferaw, 781

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2011; Tran et al ., 2015; Turan et al ., 7°35 ′N and Longitudes 4°31 ′E and 2010). As regards the study area, it has 4°39 ′E and falls under Koppen’s Af been a focus for many researches because humid tropical rainforest climates. The of its location within a university daily minimum temperature is 25 oC (Obafemi Awolowo University, Ile Ife) while the mean maximum is 33 oC environment. Apart from the work of (Adejuwon and Jeje, 1975). The mean Adediji and Jeje (2004) who worked on annual rainfall is about 1400mm, with the land use and sediment delivery ratio in rainy season between April and October. Opa basin and Adediji (2005) on The rainy season is marked by two reservoir sedimentation on Opa maxima, in June/July and catchment, there is no known research September/October. These two periods record on land use land cover dynamics are separated by a short dry spell in in Opa Catchment. Thus, this study aims August. The area is characterized by in providing the information (on LULC) natural vegetation of the tropical using the advancement in space rainforest of multiple canopies and lianas technology particularly in Remote (Adediji, 2005). However, the persistent sensing and GIS applications. The result removal of the natural vegetation for of the study is hoped to provide relevant cultivation of arable crops such as yam, information for effective monitoring, cocoyam, plantain, cassava, maize etc. planning and formulation of policies that and cash crops such as cocoa, kolanut etc. would support the conservation of the in a mixed faming pattern coupled with environment and nature in the area. logging activities has led to the Study Area destruction of the original vegetation. The study area which is As evident from the above activities, approximately 110km 2 in size extends the people are predominantly Yoruba from part of Ile Ife, capital of Ife Central farmers of Ile Ife with their farmsteads, Local Government including Obafemi camps and hamlets such as Mokuro, Awolowo University campus in Ile-Ife, to Amuta, Poju, Fadugbo, Itamerin and Osu town in Atakumosa West Local Alakowe located at different areas within Government Area (Figure 1). The study the catchment. area lies within Latitudes 7°27 ′N and

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Figure: The Study area

Materials and Methods obtaining cloud-free images. The image The data used for the study consists data were used to generate the land of Landsat satellite images, ancillary data use/cover for the study period. In such as administrative and topographic addition, ancillary data consisting of maps, and GPS data collected from administrative and topographic maps fieldwork. Landsat image data are were used to derive the administrative popular data sources for documenting boundaries and topographic information spatio-temporal changes in land cover within and around the study area. and use due to their long history, Image Processing and Classification reliability, and availability and medium The Landsat satellite images data resolution (Lui and Coomes, 2015; which were delivered with UTM Zone Townsend et al ., 2009). Multi-date 31N projection using the WGS 1984 Landsat satellite image of 1986, 2002 and Datum, were pre-processed to correct for 2014 captured by the satellite during the radiometric and geometric errors. The dry season (months of November to corrections were conducted using March) were used for the study. Dry calibration tool and Fast Line-of-sight season image data were adopted in other Atmospheric Analysis of Hypercubes to avoid seasonal variations of (FLAASH) algorithm in ENVI 5.1 topographic details, particularly software environment (Hester et al ., vegetation cover, and the possibility of 2008; Lui and Coomes, 2015). The 783

Ethiopian Journal of Environmental Studies and Management Vol. 9 no.6 2016 algorithm converts the original digital area for the various epochs under number (DN) data in the raw Landsat consideration. image scenes to top-of-atmosphere Analysis of Spatio-temporal Changes in reflectance values. Supervised the Land Use/Land Cover classification procedure using Maximum Changes in land cover types from likelihood classification algorithm was 1986 – 2002 and 2002 – 2014 were applied to each of the resulting determined by identifying differences reflectance images to produce the land between the classified maps of 1986, use/land cover classes. 2002, and 2014 using Intensity analysis Regions of Interest (ROIs) of six (Aldwaik and Pontius, 2012). Aldwaik land-cover classes of interest were and Pontius (2012) defined Intensity identified using visual interpretation and Analysis as the quantitative framework to spectral assessments of the Landsat account for differences among categories image and corroborated with high- as summarized by a square transition resolution Google Earth™ imagery of the matrix for which the row categories are study area. This process is commonly identical to the column categories referred to as training sites because the The areas covered at a given land spectral characteristics of those known cover type for the different times areas were used to train the classification were compared and the nature of changes algorithm for eventual land use/cover either positive or negative in each land mapping of the images. Based on cover type in 1986, 2002 and 2014 were Anderson I-level classification scheme, obtained. To provide a range of estimates six classes were identified on each image. of LULC since 1986, two independently The classes are Vegetation (V); built-up developed land cover maps were used (BU); Bare land (BL); water body (WB); (Ishaq et al ., 2012). The most Rock outcrop (RO) and riparian forest conservative LULC changes as a result of (RF). Maximum Likelihood algorithm, an anthropogenic activities estimates were effective and commonly used classifier made using the intersection of both maps, (Churches et al ., 2014; Lui and Coomes, i.e., where both agreed on a given land 2015), was used for the classification. cover type classification. The algorithm assumes a normal Prediction of Land Use and Cover distribution of reflectance values for each Changes user-defined class within each spectral Continuity of spatial and temporal band of the original satellite image, and changes of LULC in Opa Catchment assigns each pixel to a specific class from 1986 to 2014 was analysed using based on the probability of it belonging Markov chain model. Markov chain to that class. ENVI’s default refinement analysis is appropriate for forecasting parameters setting smoothing kernel size trend of land use system based on to 3 (i.e., 3 × 3 pixels) and aggregate transition probability matrix, which minimum size to 9 pixels were employed records the probability that each land to remove “salt-and-pepper” effects. The cover category will change to every other classification procedure resulted in a map category (Bottomley, 2000). The of landuse/land cover pattern of the study procedure determines exactly how much land would be expected to transit from 784

Spatio -Temporal Analysis of Landuse Dynamics ...... IBITOYE et al. the later date to the predicted date based recorded in a 16 years period between on a projection of the transition potentials 1986 and 2002. The reason for this into the future. An important assumption astronomical increase in the built up area of the procedure is that LULC change is could be as a result of the economic regarded as a stochastic process, and policy put in place by both the Federal different categories are as the states of a and State Government that brought about chain (Weng, 2002). Markov chain improvement in both social and models have been widely used to predict economic activities during this period. land use and land cover changes (Gong et This has in turn translated to al ., 2015; Ma et al ., 2012; Takada et al ., improvement in living standard of the 2010; Yang et al ., 2011; Zhang et al ., people particular the civil service 2011). For this work, MARKOV module workers, traders and artisans and one of of IDRISI 17.0 (Selva Edition) software the resultant effects is the demand for was used. The MARKOV module was residential buildings. As a matter of fact used to analyse a pair of land cover the built up area encroached into virtually images and outputs a transition all the identified land uses in the study probability matrix, a transition areas area with bare land and vegetation matrix, and a set of conditional suffered great loss. The dynamism probability images. observed in this study also conform with the result of land use land cover Result and Discussion dynamics carried out by Adeoye (2012) Temporal Pattern of Land Use/Land in the city of Lokoja, Nigeria, Ejaro and Cover between 1986 and 2014 Abdullahi (2013) in Suleja LGA, Nigeria, Six land use classes were identified in Aduah and Aabeyir (2012) in Wa the study area as shown in Table 1. Some Municipal in Ghana and Areendran et al . land uses were on continuous increase (2013) in Singrauli district, Indian. while others were steadily decreasing. Bareland occupied 29.05km 2, about For instance, in a space of 28 years (1986 26.3% which was the second largest land -2014), built up area increased from 7.1 use type, after the vegetation land use, in km 2, that is 6.4% of the total catchment 1986 in the study area. This position was area in 1987 to 11.9 km 2 (10.8%) and maintained in 2002 with 39.20km 2 20.7 km 2 (18.9 %) in 2002 and 2014, (35.5%) of the total land cover but with a respectively with an overall increase of loss of about 9.36km 2 in 2014. 13.6km 2 which translated to 195% Incidentally, it was the same period increase. It was observed that between (2002 – 2004) the built up gain more area 1986 and 2002 (16 years period), the of land, thus confirming a positive increase was 4.85km 2 translating to an correlation between the two land uses. A average of 0.30km 2/yr and between 2002 cursory look at the spatial land use maps and 2014, a period of 12 years, the (see Figure 6 and 7) of the study area for increase was 8.95km 2 averaging 2002 and 2014, will confirm this land use 0.74km 2/yr. The record further revealed dynamism. that increase of 8.95km 2 recorded in the The riparian forest land use in the space of 12 years (2002-2014) in the built study area also experienced very slight up land use, was almost double 4.85km 2 changes either as gain or loss during the 785

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period of study (1986-2014). In 1986 it could be as a result of the improvement has a total of 4.64km 2 (4.2%) with a slit in the standard of living amongst the gain of 0.84 km 2 to make a total of citizen which resulted to the use of gas or 5.48km 2 in 2002. By 2014, it decreased to kerosene as against firewood for cooking 3.39km 2. The decrease might be as a and less opening of more land for result of encroachment from other land farming activity. This might have likely uses majorly from built up class. gave rise to regeneration of the As a common phenomenon in land vegetation, hence the increase observed use land cover dynamics studies, in the vegetation land use. vegetation land use class is always at the Pond, stream and wetland were mercy of other land uses such as bareland classified as water body in the study. as a result of farming and logging There was a steady decrease in the water activities and urbanization process. In the body from 0.72km 2 in 1986 to 0.46km 2 in study area, the vegetation land use lost 2002 and 0.40km 2 in 2014. Between tremendously to other land uses such as 1986 and 2002, about 0.26km 2 was built up and bareland. In 1986, vegetation encroached upon by other use such as land use had a total area of 67.72km 2 residential building (built up land use) translating to 61.30% of the total particularly along the water body situated catchment area. It means that as at 1986, within the developed areas of the study more than half of the upper Opa area. Catchment Area was covered with Rock outcrop occupied a reasonable vegetation. By 2002 it reduced to portion of the study area. For instance, in 52.59km 2 which was about 47.63% of the 1986, rock outcrop was 1.25km 2, total area of the catchment similar to the translating to 1.13% of the total land observation of Showqi and Bhot (2014) cover. This use was by 2002 and 2003 on land use land cover dynamics study in reduced to 0.77km2 and 0.56km2 the Romshi Watershed, India. respectively. The steady loss of this land Surprisingly, there was a gain of about use type might be as a result of increase 2.81km 2 from other land uses probably quarry activities and demand for land for from bareland between 2002 and 2014 to residential purpose particularly in the have a total square kilometer of 55.41 in built up area. the study area. The observed pattern

Table 1: Land use land cover on temporal basis between 1986 and 2014 Land use/ Rate per annum Area (km 2) / % Magnitude (Km 2) Land cover (km 2) 1986 2002 2014 86-02 02-14 86-02 02-14 Built-up 7.07 (6.4) 11.92 (10.8) 20.86 (18.9) 4.85 8.94 0.30 0.75 Bareland 29.05 (26.3) 39.20 (35.5) 29.84 (27.0) 10.15 -9.36 0.63 -0.78 Riparian 4.64 (4.2) 5.48 (5.0) 3.39 (3.1) 0.84 -2.09 0.05 -0.17 Forest Vegetation 67.72 (61.3) 52.60 (47.6) 55.41 (50.2) -15.12 2.81 -0.95 0.23 Water body 0.73 (0.7) 0.46 (0.4) 0.40 (0.4) -0.27 -0.06 -0.02 -0.01 Rock outcrop 1.25 (1.1) 0.77 (0.7) 0.56 (0.5) -0.48 -0.21 -0.03 -0.02 Total 110.46 110.43 110.47 786

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Figure 2: Relative land cover changes in the study area (1986-2014)

Figure 3: Gains and losses of LULC classes between 1986 and 2002

Figure 4: Gains and losses of LULC classes between 2002 and 2014

Spatial Pattern of Land Use/Land Cover under consideration (i.e.1986-2014), six between 1986 and 2014 land use types were classified and all the As evident from the land use maps uses experienced one form of change or (Figures 5, 6 and 7) for the various years the other. Apart from water body that 787

Ethiopian Journal of Environmental Studies and Management Vol. 9 no.6 2016 followed a pattern, all other uses spread land use dynamism continues unabated, spatially all over the entire area. For in 30 years time, there will be no instance in 1986, the areal extent of the vegetation in the study area. Thus, built up area was limited to the south jeopardizing the need of the future western part of the catchment and was generation and causing greater harm to surrounded by bareland while the greater the environment. Forest removal has been parts of the catchment was vegetation observed as one of the key factors (Figure 5). By 2002, the built up land use enhancing global warming that threatens had taken over areas identified in 1986 the environment. Plants make use of as bareland and new bareland was created carbon dioxide (a greenhouse gas) during through anthropogenic activities such as photosynthesis thereby reducing its farming, bush burning, logging into land concentration in the atmosphere. The use area formerly regarded as vegetation environmental implication of this in 1986 (Figures 2 and 6). The bareland development is that the catchment will be spread predominantly to the eastern parts contributing negatively to the climate of the catchment. In 2014 the vegetation change problem in Nigeria. Other land land use was more or less reduced to half uses such as riparian forest, rock outcrop of what it was in 1986 (Figure 3 and 7). and water body in the study area if not This was as result of increase in properly monitored and checked may population and consequently, increase in lead to more devastating environmental the needs for food, shelter and other problems such as erosion, flooding, loss commercial activities. It is therefore a of soil fertility and impoundment of Opa common knowledge that if this pattern of water reservoir (Adediji, 2005).

Figure 5: Spatial pattern of land use and land cover in 1986 788

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Figure 6: Spatial pattern of land use and land cover in 2002

Figure 7: Spatial pattern of land use and land cover in 2014

Conclusion using remote sensing and GIS This study has generated a synthetic technologies. Six prominent land use of knowledge on land use land cover in types consisting of bareland, built up, the study area between 1986 and 2014 riparian forest, rock outcrop, vegetation

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Ethiopian Journal of Environmental Studies and Management Vol. 9 no.6 2016 and water body were identified. The Adediji, A., Jeje, L.K. (2004). Land use result clearly shows that land use land and Sediment delivery ration in the cover changes were significant during the Opa Basin, southwestern Nigeria. period under consideration (1986 to Tropical Agriculture , 81: 133-140. 2014). The most dynamic of these land Adejuwon, J.O., Jeje, L.K. (1975). Land uses were bareland and built up areas element of the environmental with urbanization process largely system of Ife area, in: Ojo, A. (Ed.), responsible for the significant change and Environmental Resources Bases modification. The study revealed an Project No. 2, Department of encroachment of about 13.16km 2 from Geology, University of Ife, Ile-Ife. built up into surrounding bareland and Adeoye, N.O. (2012). Spatio-temporal vegetation land uses. It was also noted analysis of land use/land cover that the negative change recorded in the change of Lokoja- A Confluence vegetation land use cover for the period town. Journal of Geography and (28 years) was almost by the same Geology , 4: 40-51. proportion at which the built up land Aduah, M.S. and Aabeyir, R. (2012). cover increased in 2014. Land cover Dynamics in Wa In general, the activities within the Municipality Upper Water Region catchment were driven by rapid growth of Ghana. Research Journal of of population and urbanization. The Environmental and Earth Sciences , factor gave rise to demand for the basic 4: 658-664. essential things such as food, shelters, Ajayi, B. (2001). Wood wastes thus leading to clearing of more land for management in forest industries. farming, logging for economic gain and Journal of Tropical Forest buildings to accommodate population. Resources , 17: 91-102. The result of this phenomenon brings into Akindele, S.O. (2001). Forest mind its environmental consequences and Assessment for Sustainable hence, the call for control and Development. Journal of Tropical preservation of the environment. This is Forest Resources , 17: 35-40. by ensuring that measures that will Aldwaik, S.Z. and Pontius, R.G. (2012). guarantee sustainable use of the Intensity analysis to unify catchment are put in place. measurements of size and stationary of land changes by interval, References category, and transition. Landscape Abbiw, D.K. (1990). Useful plants of and Urban Planning , 106: 103-114. Ghana. Intermediate Technology Andreas, B.B. and Hugh, D.E. (2009). Publications & The Royal Botanic Monitoring 25 years of land cover Gardens, Kew, London. change dynamics in Africa: A Adediji, A. (2005). Reservoir sample based remote sensing sedimentation: the case or the Opa approach. Journal of Applied Reservoir catchment, Southwestern Geography , 29: 501-512. Nigeria. South African Areendran, G., Rao, P., Raj, K., Geographical Journal, 89: 123-128. Mazumdar, S. and Puri, K. (2013). Land use/land cover change 790

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