STRATEGIC LANDUSE LANDCOVER ASSESSMENT OF NIGERIA-BENIN REPUBLIC INTERNATIONAL BORDER CORRIDOR

S ettlement along border lines have historically evolved along socio-economic and cultural lines. Over the years these settlements evolved and undergo a lot of changes which significantly affects socio-economic, cultural and security management along borderlines. In Nigeria, there have been lots of economic and security issues which are occasioned by human activities and unplanned settlement patterns along our borders. Mapping and having a precise knowledge of the Landuse/Landcover (LULC) data of these areas are essential for effective economic planning and tackling of security and environmental challenges. Unfortunately, these seems to be non-existent along the Nigerian southwest borderline with other countries. Against the backdrop of current challenges along our borderlines, there is an urgent need to map and analyse LULC changes in these areas

In response to these challenges, the National Space Research and Development Agency (NASRDA) through her Cooperative Information Network: Southwest Advanced Space Technology Application Laboratory (ASTAL); embarked on this study to analyse the pattern and change of LULC across the Nigerian Western border (borders with Republics of Benin and Niger) between 2015 and 2020. The aim of the project is to map the strategic land use land cover along the Nigerian Western border in order to provide effective information for socio-economic, environmental and security management ofthe borderline.

Fifteen (15) kilometres on both sides of Nigeria western international borderline was delineated as the study area with a total land mass of 212,329.064km2. The delineated study area was divided into 54 rectangular grids of 30 kilometres each (this includes 15km on both sides of the international borderline). This was done to enable detail study of the individual rectangular grids and the study area as a whole. The analyses employed visual interpretation and supervised classification on the GIS software to classify six classes of LULC using Landsat 8 imagery. The classes used are vegetation, cultivation, settlement, rock outcrop, waterbody and bare surface. Route mapping (roads and footpaths) was also carried out across each ofthe 30km rectangular grid and the study area as a whole, using high resolution satellite images.

Results were obtained for the individual 30 km rectangular study areas used across the international borderline. General results obtained from the LULC change across the whole study area during the fiveyear period indicates a marginal increase of 0.9% (14.99km2) in settlement across the study area. Cultivation experienced a decline from 112,630.29km2 in 2015 to 112,988.94km2 in 2020 (3.69%). There was an increase of 2.07% (264.1km2) in vegetation. Similarly, there was a corresponding increase of 0.61% (23.93km2) in bare surface across the study area over the five-year period.

Information from the results will facilitate a better understanding ofhuman activities along our borderlines and reflect the dynamics of this activities. It will also provide critically needed data for effective socioeconomic and security management ofour borderline.

H istorically, the border region has always been a major centre of economic activities among countries and Nigerian western international borders with Republics of Benin and Niger has not been an exception. Anthropogenic activities around the borders regions contribute immensely to the nature and trends in the Landuse/Landcover (LULC) changes of these regions over time. Issues relating to LULC changes across these borders are known to be strategic in maintaining security, socio-economic and political stability of the country. Therefore, information on pattern and changes of LULC across these areas are crucial in understanding human activities and its effect in an area over a specific time period.

Humans depend on land for settlement, agriculture, road, infrastructure, and others. Climate change, increasing population are major drivers ofchanges across these areas. This has also contributed immensely in compounding the arduous task ofsecuring and governing these areas. It is therefore important to embark on a study that will provide information on LULC changes across these areas. This is important in mitigating emerging socio-economic, environmental and security challenges along these areas.

S Security issues along our borderlines occasioned by unplanned settlement patterns, climate change and human activities has been on the increase. Precise data, maps and knowledge of LULC changes and trends across these areas are scanty or virtually non-existent. Based on recent events, there is an urgent need to carry out LULC change analysis in these areas using geospatial technology. This is crucial in providing much needed information for effective planning and appropriate actions.

S The aim ofthis project is to map the strategic land use land cover along Nigerian Western border to provide effective information for socio-economic and security management ofthe borderline.

• to map the land use/land cover change (2015 to 2020) along the Nigerian Western border.
• route mapping along the Nigerian Western border.

Study Area

T he study area is Western Nigerian International border. It is a buffer zone of30km inward and outward of the Nigerian Western international borderline which stretches from the northern edge to the southern edge ofthe country. The buffer zone was divided into 54 grids with the index number which ranges from [0-4] for the first grid at the southern edge to [316-320] at the northern edge. The reason for griding system is to produce the atlas at a scale that will be suitable enough for better visualization.

Data Types and Sources

S atellite images were used for the project. These include landsat-8 OLI of the year 2015 and 2020 and Google earth image. The landsat-8 OLI of30m resolution was acquired from the Copernicus archive while the Google Earth Image was acquired Google Earth Platform.

Data Analysis

D igital image classification was carried out on the acquired landsat image using supervised image classification technique. A maximum likelyhood was used as a parametric rule for features extraction into various landuse and landcover classes across the study area. The area square kilometre ofeach landuse and landcover class for the year 2015 and 2020 were generated and was put on the maps.

Roads Network Capturing for Trans-Border Movements

R oad networks of the area were digitized from the Google Earth Satellite image within Geographic Information System platform in order to have the idea of spatial pattern of the trans-border movement between Nigeria and the neighbouring countries at the western international border. The digitized roads networks include both the footpath and the major roads. The reason for including the footpath is because most ofthe border movement occur through the footpaths. The settlements and their names were overlaid on the map for the proper identification of places.

Map Composition

T The map layout for the project shows landuse landcover maps ofthe year 2015 and 2020, the entire study area map and the statistics table for the landuse landcover statistics ofthe year 2015 and 2020.