Assessment of Change in the Built-Up Index of Uyo Metropolis and Its Environs Using Remote Sensing

The research was aim at assessing the change in the Built-up Index of Uyo metropolis and its environs from 1986 to 2018, using remote sensing data. To achieve this, a quantitative analysis of changes in land use/land cover within the study area was undertaken using remote sensing dataset of Landsat TM, ETM+ and OLI sensor images of 1986, 2000 and 2018 respectively. Supervised classification, using the maximum likelihood algorithm, was used to classify the study area into four major land use/land cover types; built-up land, bare land/agricultural land, primary swamp vegetation and secondary vegetation. Image processing was carried out using ERDAS IMAGINE and ArcGIS software. The Normalised Difference Built-up Index (NDBI) was calculated to obtain the built-up index for the study area in 1986, 2000 and 2018 as -0.20 to +0.45, -0.13 to +0.55 and -0.19 to +0.63 respectively. The result of the quantitative analysis of changes in land use/land cover indicated that Built-up Land had been on a constant and steady positive growth from 6.76% in 1986 to 11.29% in 2000 and 44.04% in 2018.


I. INTRODUCTION
In recent times, urban areas within Uyo metropolis have expanded in an exponential proportion and the rates of urban population growth are higher within the city as a locus of economic activities.The extent of this urbanization or its growth drives the changes in land use/land cover pattern within the city.Uyo Capital City, just like most Nigerian cities is growing at a very fast rate, both in population and spatial dimensions, thereby increasing the demand on its scarce land resource.Just like many other State Capitals in Nigeria, urban growth has extended beyond the geographical boundaries of Uyo Capital City/Metropolis to adjoining environs like parts of Itu, Ibiono Ibom, Ibesikpo Asutan, Nsit Ibom and Uruan Local Government Areas.This has therefore resulted in increased land consumption and a modification and alterations in the status of her land use/land cover over time.This research therefore sought to provide a detailed and comprehensive attempt (using Remote Sensing data and GIS) to evaluate the Land use/Land cover of Uyo metropolis as it changed over time, with a view to ascertaining the change trend with emphasis on the rate of urban growth and expansion.
Understanding the spatial distribution and growth of urban areas is essential for urban planning and resource Published on June 19, 2019.Dr. Aniekan Eyoh and Dr. Akwaowo Ekpa as at the date of this publication are senior Lecturers in the Department of Geoinformatics & Surveying, Faculty of Environmental Studies, University of Uyo, Nigeria (e-mail: aniekaneyoh@uniuyo.edu.ng,aniekaneyoh@gmail.com,akwaowoekpa@uniuyo.edu.ng)management, and one of the basic activities required for this purpose is mapping the built-up areas.Urban land accounts for a small fraction of the Earth's surface area but has a disproportionate influence on its surroundings in terms of mass, energy and resource fluxes [2].The identification (location, distribution and size) of the built-up area is of prime significance in urban, and suburban studies.The calculation of its change throughout the time to the detriment of the non-built-up area constitutes a highly important indicator of urban change and environmental degradation [5].Therefore, information on land in relation to how it is being used as well as changes in such land use has become a prime pre-requisite for the growth and development of any nation.
A wide variety of digital change detection techniques have been developed over the last two decades.A number of techniques for mapping urban land cover using satellite imagery have been formulated, applied and evaluated.These techniques can be broadly grouped into two general types: (1) those based on the classification of the input data, including pixel-and object-based classifications [1] and (2) those based on directly segmenting the indices, such as the commonly used normalized difference vegetation index (NDVI) [6].However, the spatial and spectral variability of urban environments present fundamental challenges to deriving accurate remote sensing-based products for urban areas [3].The basis of using remote sensing data for change detection is that changes in land cover result in changes in radiance values which can be remotely sensed.Techniques to perform change detection with satellite imagery have become numerous as a result of increasing versatility in manipulating digital data and increasing computer power.This research seeks to assess the rate of urban growth of Uyo metropolis using Landsat archived data of 1986, 2000 and 2018 for both Image Classification and the Normalized Difference Built up Index (NDBI).Secondary data: These included administrative maps, land use maps and topographic maps of Uyo metropolis acquired from Uyo Capital City Development Authority (UCCDA), Akwa Ibom State.Also, Google Earth was used to obtain images of the study area at higher resolution to support satellite image interpretation, classification, accuracy assessment and as a reference to the different Landsat images used.The administrative map was used to create a shape file of the study area used to subset the Landsat images.This reduced the data sizes and increased computer storage space and also reduced the run time of the different processes.

A. Image Classification
Land cover maps of the three time periods were produced using supervised classification methods.The main objective of image classification is to place all pixels in an image into land use/land cover classes in order to draw out useful thematic information.This was done on the basis of reflectance characteristics of the LU/LC types.Standard 'false' colour composite comprising of bands 5, 4, and 3 for Landsat TM and ETM+ sensors and bands 6, 5 and 4 for Landsat OLI sensor were used.
The delineated classes were: Built-up Land, Primary Vegetation, Secondary Vegetation and Bare Land/Agricultural Land as shown below (Table 1).

B. Determination of the Normalised Difference Built-up Index (NDBI)
This was done using raster calculator in ArcGIS 10.4 software.The Normalised Difference Built-up Index (NDBI) technique was used to extract the built-up areas automatically from the satellite imagery.The index highlighted urban areas where there was typically a higher reflectance in the shortwave-infrared (SWIR) region, compared to the Near-infrared (NIR) region.The equation of NDBI are given thus according to [6]; Bands 4 and 5 of the TM and ETM+ sensors had wavelengths of 0.76 µm to 0.90 µm and 1.55µm to 1.75µm respectively, while the Band 5 and Band 6 of OLI sensor had wavelength of 0.85µm to 0.88µm (NIR) and 1.57µm to 1.65µm (SWIR) respectively.NDBI was originally developed for use with Landsat TM Bands 5 and 4.However, it works with any multispectral sensor with a SWIR band between 1.55-1.75µmand a NIR band between 0.76-0.9µm.

C. Software Used
Software used to carry out this research included ArcGIS 10.4, and ERDAS Imagine 14.0.ERDAS imagine was used to perform layer stacking to produce false colour composites, image co-registration, sub-setting, and image classification; supervised and unsupervised.These processes could also be done in ArcGIS but ERDAS was chosen since it was more convenient for these analyses.ArcGIS software was used for adding images, adding attributes to data, mosaicking different scenes of Landsat data, performing image overlay, and calculating the Normalised Difference Built-up Index (NDBI).The graph below shows that between 1986 to 2000, the built-up land was on the increase; 21.36 square kilometres to 35.63 square kilometres (19.96%).Also on the increase was the secondary vegetation class with an approximate expanse of 21.48 square kilometres (30.04%).All other land use/land cover classes were on the decrease.However, between 2000 to 2018, the same secondary vegetation class recorded a decline in coverage; from 82.14 square kilometres to 29.49 square kilometres (-25.50%)thereby passing the way for further increase in built-up land from 35.63 square kilometres in 2000 to 139.06 square kilometres in 2018 (50.00%).The overall result of change detection showed that built up land increased by 19.96% between 1986 to 2000, (14 years) and by 50.00% between 2000 to 2018 (18 years) respectively, while all other land use types were on the decrease

C. Discussions
The temporal analysis of land use/land cover change of Uyo metropolis indicated that from 1986 to 2000 (14 years), Built-up Land increased by 14.28 square kilometres (19.96%),Bare land/Agricultural land decreased by 18.67 square kilometres (26.10%),Primary vegetation decreased by 17.09 square kilometres (23.90%) and Secondary vegetation increased by 21.48 square kilometres (30.04%).
The results showed a clear indication of urban growth within the metropolis as evident in the built-up land cover class.This growth could be attributed to massive infrastructural developments through construction/dualization of roads by government between the year 2000 and 2018 as well as increased urban settlements.These developments have attracted various socio-economic activities to the State capital and an obvious population growth through rural-urban migration, interurban migration and other drivers of population growth.This increased population led to corresponding increase in residential, commercial and other urban land uses.
In general, construction of roads has been a major driver of urbanisation as built-up surfaces were identified majorly around this feature.Urban surfaces have radiated outwardly from Ibom plaza (City centre) which is the centre of economic activities to other parts of the metropolis; away from the ravine, located at the North Eastern part of the study area.Due to the topography of this region, land uses within it had basically been primary vegetation, secondary vegetation and agricultural land uses.The variability of total number of test pixels selected for each class is due to the most dominating land cover type present within the years under study.The results of the Normalised Difference Built-up Index (NDBI) gave better distinction between the built-up land features in white, and grey colours while older urban surfaces were shown in dark brown and lighter brown colours.The index highlighted changes in urban surfaces with time.The variability in the bright tones indicated the differences in built-up density, where the areas with high built-up density appear the brightest and vice versa.

D. The Normalized Difference Built-up Index
Prior to the creation of Akwa Ibom State in 23rd September 1987 from Cross River State and adoption of Uyo Local Government Area as the capital of the state, several developmental activities took place within the study area in 1986, radiating from the city centre.Some of these were the creation of elitist estates, examples, the Federal low cost housing estate and Ewet housing estate.Also, in year 2000, the NDBI indicated more of such housing estates, examples, Shelter Afrique Estate, Akwa-ima Estate and several other housing estates which were as a result of the transition from military rule to civilian rule in 1999.In 2018, the NDBI indicated most recent developmental activities within the University of Uyo main campus at Nsukara Offot.

V. CONCLUSION
Remote sensing technique has proven to be a very useful tool in providing archival data for spatial temporal analysis of land use/land cover.This study has successfully explored the use of remote sensing and GIS techniques in assessing built-up index of Uyo metropolis.The results obtained indicated that from 1986 to 2018, Built-up land increased by 117.70 square kilometres (50.00% increase), Bare land/Agricultural land was depleted by 36.93 square kilometres (15.69% decrease), primary vegetation decreased by 49.51 square kilometres (21.03% decrease) and secondary vegetation also decreased by 31.26 square kilometres (13.28% decrease).The downward growth in every other land cover type aside from the Built-up land raises serious concerns of urban sprawl within the metropolis.It is strongly believed that the results from this study will be very useful for decision makers in ensuring planned development within the study area.

Fig. 1a
Fig. 1a Map of Nigeria Fig. 1b Map of Akwa Ibom state

Fig. 3 :Fig 4 :
Fig. 3: Land Use/Land Cover Map of Uyo Metropolis and its Environs as at 1986.

Fig. 5 :
Fig. 5: Land Use/Land Cover Map of Uyo Metropolis and its Environs as at 2018.

Fig. 8 :
Fig. 8: Urban Sprawl Map of Uyo Metropolis and its Environs from 1986 to 2018

TABLE I :
MAJOR LAND USE/ LAND COVER TYPES AND DESCRIPTION 2Primary VegetationDense vegetation with darker hues of red as in 'standard false colour' composite, swamps naturally growing within the ravine region, thick deciduous trees.Recently ploughed land, burrow pit/excavated lands, dredged spoil, bare soil, grasses, farm lands, crop lands, horticulture.

TABLE II
: AREA IN SQUARE KILOMETERS AND PERCENTAGE COVER FOR 1986, 2000 AND 2018 LULC

TABLE III .
ANALYSIS OF LULC CHANGES IN UYO METROPOLIS FROM 1986 TO 2018 LULC change Trend 1986 -2000

TABLE IV :
ACCURACY ASSESSMENT FOR THE CLASSIFICATIONS