1. Introduction

wale falls within the Niger Delta region of Nigeria. The area is located within latitudes 5º40 1 N and 5º50 1 N and longitudes 6º15 1 E and 6º30 1 E (Figure 1a, b) (Anonymous, 2011 and Avbovbo and Ogbe, 1978). The Niger Delta is located within the southern part of Nigeria. It is home to numerous creeks, rivers and possesses the world's largest wetland with significant biological diversity (Twumasi and Merm, 2006). Okpai/Aboh region is within Ndokwa East Local Government Area and is situated within the Sombriero Warri deltaic plain deposit invaded by mangroves. The geographical Niger Delta has been said to cover an estimated area of between 19,100 km 2 to 30,000 km 2 based on hydrological, ecological as well as political boundaries (Keddy, 2010;Ibe, 1988;Merki, 1972 and Murat, 1972). Okpai/Aboh region is a low-lying area with elevation of not more than 3.0 metres above sea level and generally covered by fresh water, swamps, mangrove swamp, lagoonal marshes, tidal channels, beach ridges and sand bars along its aquatic fronts (Dublin-Green et al, 1997). The area has a characteristic tropical monsoon climate at the coast with rainfall peaks in June and September/October with prevailing tropical maritime air mass almost all year round with little seasonal changes in wind directions (Olaniran, 1986). Annual mean total rainfall is about 2,500mm. The mean monthly temperature range from 24-25 o C during the rainy season in August to 27-29 o C during the end of dry season in March/April. Leroux (2001) reported that maximum temperatures are recorded between January and March (33 o C) while minimum temperature are recorded in July and December (21 o C), respectively. Temperatures are moderated by cloud cover and damp air. It experiences a humid tropical equatorial climate consisting of rainy season (April to November) and dry season (December to march). The average annual rainfall is about 2,500mm while the wind speed ranges between 2-5m/s in the dry season to up to 10m/s in the rainy season especially during heavy rainfall and thunderstorms. The region is criss-crossed with distributaries and creeks. This area has been classified geomorphologically as tidal flat and large flood plains lying between mean, low and high tides. Three different highs exist within the Kwale, in Ndokwa-East Local Government block, namely a central high where most of the wells have been drilled, an eastern high housing one well and a north western high whose extent has not been clearly defined. The area lies within the freshwater forested region of the Niger Delta. The coastal areas of the Niger Delta are the home to oil exploration and exploitations in Nigeria (Nwilo and Badejo, 1995). This is largely due to the huge deposits of crude oil and natural gas deposits within the region. The World Bank report of 2002 succinctly stated that Rivers and Delta states alone produced about 75% of Nigeria's petroleum, which represents over 50% of national government's revenues. The report also rated, Nigeria as the fifth largest supplier of crude oil to the United States (EIA, 2003). Nigeria's proven oil reserves drives the economy because it is almost exclusively dependent on earnings from the oil sector, which generates about 20% of GDP, 95% of foreign exchange and about 65% of budgeting revenues (CIA World fact Book, 2008). No doubt, human activities like oil exploration and production have impacted negatively on the delicate balance of nature and the fragile ecosystems of the study area.

Land use and land cover have become very important parameters in highlighting such environmental changes that have taken place over time within the earth's surface (Matiko et al, 2012). It has become one of the major parameters for environmental change monitoring and natural resource management (Zhang et al, 2008). Thus, Fuchs (1996) aptly stated that land use and land cover and impacts on terrestrial ecosystems including forestry, agriculture, and biodiversity have been identified as high priority issues at global, national, and regional levels. The indirect impact of landuse and land cover is altering climate on the waters (Weng, 2001) while the direct effect could be compromising water quality (Rogers, 1994). Kwale region is not alone with respect to deterioration of its landscape. Woodgate and Black (1988) reported that an estimated 66% of Victoria's native vegetation has been cleared as a result of the growth and economic development of the State. Geographic Information Systems (GIS) Global Positioning System (GPS) and Remote Sensing (RS) have become indispensable tools in almost all environmental endeavors (UN, 1986). These concepts have been employed in various studies including atmospheric studies (Fagbeja, 2008), lithospheric (Maruo et al, 2002), hydrologic (Nwilo and Badejo, 1995) biodiversity (Salami and Balogun, 2006), assessment of developmental change over time (Twumasi and Merem, 2006), land use and land cover categories (Ehlers et al., 1990; Treitz et al., 1992) as well as ground water (Maruo et al, 2002). Kwale region's landscape had undergone environmental changes over a long period of time as a result of oil exploitation in the area. This environmental change, therefore, has necessitated the need to carry out a holistic approach to land use and land cover inventory of the area with a focus of establishing the geospatial infrastructure for policy makers as well as for proper planning and management of the environmental conditions of the region.

2. II.

3. Methodology

The types of data acquired for this study are shown in Table 1. They were sourced from global Land cover resources website (http:www.glcf.com), while the image from the Nigsat1 2008 was obtained from the

4. Data Extraction Process

Following the acquisition of the required satellite images from their respective sources for the aforementioned years, the extraction of the study area portion from the entire image covering the entire South Western /South Southern corner of the country was done using ArcGIS. The georeferencing of the satellite data as well as the subset operation using ILWIS 3.3 Academy software was performed.

IV.

5. Digital Image Processing and Analysis

The stage of analysis include a reconnaissance field survey (ground truthing) with GPS to obtain coordinates of each location; the 1975 topographic sheet (1: 25,000) covering the entire region was used to aid in identifying notable spatial features of the area. This process proved very useful in unraveling, demystifying and harmonizing the disparity between what was observed on ground and their respective spectral signatures displayed in the images. In this regard however, it was observed that both bare surfaces and settlements exhibited somewhat similar spectral characteristics as both randomly did have a mix of cyan and white color, which are the standard color representations for both settlements and bare surfaces.

The procedure developed for the sample dataset of the submap was carried out based on the supervised classification techniques using the eight (8) land use/cover classes (features) of the area as indicated in Table 2. Furthermore, the maximum likelihood method of classification (MLC) in the ILWIS 3.3 Academic software was adopted for the classification. The maximum likelihood method is a statistical decision rule that examines the probability function of a pixel for each of the classes, and assigns the pixel to the class with the highest probability. The classifier assumes that the training statistics (sample sets) for each class have a normal or 'Gaussian' distribution. The classifier then uses the training statistics to compute a probability of whether of a pixel belonging a particular land cover. This allows for within-class spectral variance. MLC usually provides the highest classification accuracies. Accordingly, it has a high computational requirement because of the large number of calculations needed to classify each pixel (Natural Resources Canada, 2005).

Three softwares were used to analyse the spatial data. ARCGIS was used for curve fitting processing while ERDAS Imagine was used for land use land cover classification, evaluating the quality of input data and ensuring that thematic maps were accurately classified. Finally, ILWIS (Integrated Land and Water Information System) was very useful in combining raster (image analysis), vectors and thematic data operations in one comprehensive phase.

6. Results and Discussion

Table 3 shows that bare surfaces rose astronomically from 35,395 km² in 1975 to 154,630 km² in 1987 representing an area change of 119,235 km² (336.87%). This could be due to the establishment of the Agip Gas Plant. which started operation within the area in 1975 (NAOC, 2007). Oil exploration and production activities abound in the region (Oboli, 1978). From 1975 to 1987 oil exploration and exploitation activities were at their peak.

Close observation reveals that areas covered by thick oil sleeks after oil spillage, do become bare with time (Fabiyi, 2008). This could be responsible for huge leap of bare surfaces from the 1975 and 1987. In 2001, there was a significant decrease in land area to 61,374 km², accounting for 25,979 km² (73.40%) area change. By 2008, there was a further significant decrease to 2,296 km representing -33,099 km² (-93.51%) area change. This gross reduction from the 1987 estimates to those of the 2001 and 2008 could be as a result of the frantic efforts of prospecting oil and gas companies at carrying out environmental remediation and mitigation mainly through phytoremediation within the study area. This showed that bare surfaces are losing their space to marshlands, cultivated lands shrub lands and water bodies (Figure 2).

The area had a forest reserve that was recognized by the Federal Government of Nigeria as far back as 1975 (Mensah and Amukali, 2000; Ekine and Iyabe, 2009). Also, the Green Revolution of Field observations revealed that the study area is exposed to massive deposition of organic agents like silt, clay, debris and a host of other decomposable materials as supported by (GGFRI, 2009 and Allen, 1972). Thus, the increase in marshlands area prior to 1987, but when oil related activities increased within this area, after the 1980's, easy formation, transportation and deposition of marshlands became affected and this could be

7. Conclusion

The delicate balance of nature and fragile ecosystem of the Kwale in Ndokwa-East Local Government area has been altered by natural and human factors over time. This study was able to model the long term land use and land cover changes between 1975 when the area was still free of exploration and exploitation activities to 2008 when oil-related activities reached their peak and provide analysis of LUCC information in the area which helped in showing significant trends. The results of this study showed that between 1975 and 2008, bare surfaces decreased by 33,099 km² representing 93.51%, forest vegetation to 14,054 km² amounting to 30.98%, settlement to 5,654 km² which is equivalent to 25.61% and woodlands 133,377 km² representing 37.19%. Furthermore, scattered cultivation, scrublands and water bodies correspondingly increased by 68,294 km² (54.45%), 77,603 km² (124.42%), 6,322 km² (3.21) and 31,274 km² (319.91%), respectively. This indicate that bare surfaces, forest vegetation, settlements and woodlands were gradually being replaced by marshlands, scattered cultivation, shrublands as well as water bodies. This study therefore, recommends the reclaiming of the areas occupied by bare surfaces and marshlands to agricultural activities to reduce poverty and improved food security in the region.

VII.

Figure 1a : Nigeria showing Delta State — Figure 1. Figure 1a :

According to Dami et al (2011) the environmental impacts of land use change are usually distinguished according to their spatial level i.e. global, regional and local. As regards global environmental impacts of land use and cover change, land use and cover are relatively new additions to the core concerns of global environmental change research (Meyer and Turner, 1996 Yemefack, 2005). Land use/cover change impacts are basic to environmental changes as the local changes cumulatively affect the whole globe. Largescale environmental phenomena like land degradation, desertification, biodiversity loss, habitat destruction and species transfer happen at local scales but they cumulatively manifest as regional and global changes. Landuse changes cause a multitude of environmental impacts at the lower spatial levels of urban, suburban, rural and open space areas, which have been extensively documented (Salami and Balogun, 2006, Odeyemi, 1999; Yuliang et al, 2004, Turner and Meyer 1994, Turner et al 1995, LUC 1988, 1999). The impacts include changes in the hydrological balance of the area, increase in the risk of floods and landslides, air and water pollution. — Figure 2.

1978 and restrictions to entrance to the forested area of the region must have encouraged the growth of plants, thus the high areal coverage of forest vegetation (45,363 km²). While the bare surface increased significantly, forest vegetation decreased from 45, 363 km2 to 10,910 km² in 1987 accounting for -34,453 km² (-75.95%) area change. The gross reduction could be due to the massive oil exploration and exploitation activities which went on without much regard to environmental consideration in the region. By 2001, forest cover increased to 46,873 km² representing an area change of 1,510 km² (3.33%) increase. Unfortunately, forest cover decreased to 31,309 km² representing an area change of -14,054 km² (-30.98) in 2008. — Figure 3.

Figure 2 : Land Use Land Cover Map for 1975, 1987, 2001 and 2008 This trend depicts a scenario where there is inconsistency in the nature and type of human activities going on in this part of the region. Thus, the 1987 estimate could be attributed to increased human and economic activities within the area partly owing to a general relaxation of the restrictions on the Forest Reserve which lost its status and the huge presence and activities of prospecting and production oil companies in the area. The global agitation for more environmentallyfriendly practices and subsequently the various mitigative tendencies of oil companies must have influenced the trend in 2001 while the further reduction in forest vegetation in 2008 could be due to increased exploration and exploitation activities of the area. Marshlands increased from 125,431 km² in 1975 to 197,752 km² representing an area change of 72,321 km² (57.66%) in 1987 but decreased to 154,105 km² in 2001 representing an area change of 28,674 km² (22.86%) and increased to 193,725 km² representing area change of 68,294 km² (54.45%) in 2008.Field observations revealed that the study area is exposed to massive deposition of organic agents like silt, clay, debris and a host of other decomposable materials as supported by(GGFRI, 2009 andAllen, 1972). Thus, the increase in marshlands area prior to 1987, but when oil related activities increased within this area, after the 1980's, easy formation, transportation and deposition of marshlands became affected and this could be — Figure 4. Figure 2 :

Figure 5. Table 1 :

S/No Satellite imagery		Year Resolution
1	Landsat MSS	1975	60m
2	Landsat TM	1987	28.5m
3	Landsat_ETM	2001	28.5m
4	Nigsat 1	2008	28.5m
III.

Figure 6. Table 2 :

	the Study Area
Code	Class
1.	Bare Surface
2.	Forest Vegetation
3.	Marshland
4.	Cultivated land
5.	Settlement
6.	Shrubland
7.	Water Body
8.	Woodland
Sources : Adapted from Dami (2003)

Figure 7. Table 3 :

Main Landuse/ Cover Class		1975	1987	2001	2008
Bare Surface ( km²)		35,395	154,630	61,374	2,296
Forest Vegetation ( km²)		45,363	10,910	46,873	31,309
Marshland	( km²)	125,431	197,752	154,105	193,725
Scattered Cultivation( km²)		62,374	61,916	88,156	139,977
Settlement ( km²)		22,074	17,437	13,375	16,420
Shrubland	( km²)	196,724	79,998	267,613	203,046
Water Body	( km²)	9,776	13,215	4,556	41,050
Woodland	( km²)	355,979	317,258	217,064	225,293
responsible for the decrease in marshlands noticed in			and spread of settlement areas must have contributed
2001 while the further increase in the 2008 value could			to the initial increase in shrub lands but later
be attributed to factors like lumbering and farming as			unavoidable reduction in shrub lands in the area. This
well as those factors that earlier favored increases.			scenario depicts high amount of human and economic
Mensah and Amukali (2000) described the rural			activities within the area after 1975. But, since most
communities in the area as rural subsistence farmers. In			shrubs are seasonal plants that grow massively during
1975, scattered cultivated areas were estimated at			rainy seasons, it could be deduced that the time the
62,374 km² which slightly decreased to 61,916 km²			images were taken could have influenced the results,
representing area change of -458 km² (-0.73%) in 1987.			hence the huge jump from the 1975 to that of 1987 and
In 2001, there was a massive increase to 88,156 km²			later from 2001 to 2008 respectively. Water bodies area
representing area change of 25,782 km² (41.34%) and			were calculated to be 9,776 km² in 1975 and increased
this continued till 2008 where an increase of 139,977			to 13,215 km² representing area change of 3,439 km²
km² representing area change of 77,603 km² (124.42%)			(35.18%) in 1987 but dwindled to 4,556 km²
occurred.. The slight decline of scattered cultivated			representing area change of -5,220 km² (-53.40%) in
areas from 1975 to 1987 must have been influenced by			2001. In 2008, water bodies increased to an estimated
farmers giving up farming to taken in juicy jobs in the oil			area of 41,050 km² representing area change of 31,274
industry. Settlement areas decreased from 22,074 km²			km² (319.91%). Seasonality must have influenced the
in 1975 to 17,437 km² representing area change of -			trend as observed in the study.
4,637 km² (-21.01%) in 1987 and later to 13,375 km²			Massive accumulation of marshlands, drastic
representing area change of -8,699 km² (-39.41%) in			reduction in the number of forest vegetation, shrub
2001. However, by 2008 the areas covered by			lands and woodlands all expose surface water bodies to
settlements were shown to be 16,420 km² representing			the direct influences of the vagaries of weather, thereby
area change of -5,654 km² (25.61%), respectively. As			contributing to increased evaporation. Thus, water-
shown from the interpreted satellite images (Figure 2),			holding capacities of soils decrease, making them lose
settlements were initially seen to be scattered but in			same to ground, surface and atmospheric sources.
2008, the settlements became more concentrated within			Woodlands reduced from 355,979 km² in 1975 to
specific geographical regions. This trend could be			317,258 km²m in 1987 representing area change of -
explained by the recent resettlement of some			38,721 km² (-10.88%) and to 217,064 km² representing
communities within the study area to pave way for more			area change of -138,915 km² (-39.02) in 2001. Finally, in
oil exploration and exploitation. Shrub lands decreased from 196,724 km² in 1975 to 79,998 km² representing area change of -116,726 km² (-59.34%) in 1987. This later increased to 267,613 km² representing area change of 70,889 km² (36.04%) in 2001 but decreased 203,046 km² in 2008 representing area change of 6,322 km² (3.21%). Afforestation efforts or seasonal regeneration of plants during the 1990's as at the time the images were captured must have been responsible			2008, the VI.
for the increase noticed from 1987 to 2001. It could also
be due to decreased activities of oil prospecting and
production companies within the area owing to the
activities of militants, increased agricultural cultivation

Appendix A

Appendix A.1 Acknowledgement

The authors gratefully acknowledge the contribution of O. Amukali, a graduate student of the Department of Geography, University of Maiduguri who collected the data for this work.

Appendix B

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