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Geospatial Analysis of Land Use/Cover Dynamics in Awka Metropolis, Nigeria: a Sub-Pixel Approach

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Geospatial Analysis of Land Use/Cover Dynamics in Awka Metropolis, Nigeria: a Sub-Pixel Approach Journal of Geography, Environment and Earth Science International 11(4): 1-19, 2017; Article no.JGEESI.35209 ISSN: 2454-7352 Geospatial Analysis of Land Use/Cover Dynamics in Awka Metropolis, Nigeria: A Sub-pixel Approach S. D. Musa1, S. U. Onwuka2 and P. S. U. Eneche1* 1Department of Geography and Environmental Studies, Kogi State University, Anyigba, Nigeria. 2Department of Environmental Management, Nnamdi Azikiwe University, Awka, Nigeria. Authors’ contributions This work was carried out in collaboration between all authors. Author SDM designed the study and the first draft of the manuscript. Author SUO managed the analyses and managed the literature searches. Author PSUE performed the geospatial mapping and geostatistical analysis, wrote the protocol, and prepared the final manuscript. All authors read and approved the final manuscript. Article Information DOI: 10.9734/JGEESI/2017/35209 Editor(s): (1) Kaveh Ostad-Ali-Askari, Department of Civil Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Iran. Reviewers: (1) Angela Terumi Fushita, Federal University of São Carlos, Brazil. (2) Nurhan Kocan, Bartin University, Turkey. Complete Peer review History: http://www.sciencedomain.org/review-history/20747 Received 30th June 2017 Accepted 23rd August 2017 Original Research Article th Published 30 August 2017 ABSTRACT This study aimed at characterizing the urban Land Use/Cover (LU/C) types and their spatio- temporal changes in Awka Metropolis, Anambra State from a sub-pixel perspective. The study made use of Landsat satellite imageries for three epochs (1986, 2001 and 2016) covering a total of 30 years. The Ridd Model of Vegetation (V), Impervious surfaces (I), Soil (S) and Water (W) was employed by applying the Linear Spectral Mixture Analysis (LSMA) to characterize satellite image fractions for each epoch. Cellular Automata Markov (Ca-Markov) chain and the Land Change Modeller (LCM) were used to predict future LU/C for the year 2031 and the transition of each LU/C categories between 2016 and 2031, respectively. ArcGIS 10.5 and Idrisi Selva software were used for the analyses. The findings of this study indicated that vegetation reduced over the years from 181.79 sq.km in 1986 to 110.89 sq.km in 2016 while impervious surface on the other hand increased from 16.79 sq.km in 1986 to 73.34 sq.km in 2016. Areas classified as soil experienced an increase from 26.15 sq.km to 36.519 sq.km within the same period while (exposed) water fractions increased from 0.961 sq.km in 1986 to 2.748 sq.km in 2016. The prediction analysis performed revealed that by the year 2031, Awka Metropolis will be reduced to about 88.20 sq.km of vegetation; impervious surfaces is expected to increase by an additional 17.780 sq.km in 2031; soil _____________________________________________________________________________________________________ *Corresponding author: E-mail: [email protected]; Musa et al.; JGEESI, 11(4): 1-19, 2017; Article no.JGEESI.35209 cover also predicted to increase to 42.75 sq.km in 2031. The transition map produced in this study (between 2016 and 2031) did not only locate areas expected to transform from each LU/C category to another or areas where they may persist but also indicated that the transition of vegetation to impervious surface was most pronounced than any other category of LU/C. LU/C changes of this nature have been held as a principal cause of Urban Heat Islands (UHIs), high urban surface temperature and a major proponent of climate change. The study therefore recommends the use of sub-pixel approach in characterizing LU/C fractions especially when the level of objectivity is highly needed and/or in the modelling of non-linear and chaotic environmental phenomena, e.g. Land Surface Temperature (LST), soil moisture, erosion and flood vulnerability, etc. Keywords: Linear Spectral Mixture Analysis; Cellular Automata; Markov Chain; maximum likelihood algorithm. 1. INTRODUCTION expansion at the detriment of the environment and other ecosystem services that abound [5,6]. Urbanization is a process of shift from rural to This has become the scenario in Awka, since it urban areas in which an increasing proportion of was named the capital of Anambra State [7]. It an entire population live in cities as well as can however be expected that with such suburb of cities [1]. According to Trivedi, Sareen, increases in population sizes, much land has and & Dhyani [2], urbanization is now driving the still will be converted into residential and economy of most nations causing them to yearn commercial uses, amongst others [8], hence, a for increased urbanization. However, the rate of serious need for objective assessment. urbanization in developing countries has been noted for its spontaneity. For instance, in Nigeria, Land use/cover (LU/C) changes, especially the population growth has been spectacular, moving attendant conversion of greenery into built-up from a growth rate of about 2.8% per annum to surfaces has been held as being the principal about 5.8% per annum, with more than 60% of cause of high urban surface temperatures, urban her population projected to reside in urban heat islands (UHIs) and a major proponent of centres by year 2025 [3]. With this increasing climate change [9,10,11,12]. The devegetation or population, migration and function of urban areas fragmentation of urban greeneries such as parks as caused by urbanization, land use is affected also inhibits atmospheric cooling due to and this in turn affects land cover as well. horizontal air circulation generated by the Consequently, agriculture or primary forested temperature gradient between vegetated and land and grassland is replaced by the urban urbanized areas thereby resulting in the landscape characterised by growing impervious development of cool island spots due to surfaces such as roads, sidewalks, parking lots, advection. On the other hand, due to the high rooftops etc. [3]. built-up cover of land at the core and the often narrow arrangement of buildings forming Land cover according to Rawat and Kumar [4] canyons inhibits the escape of the reflected refers to the physical characteristics of earth’s radiation from most of the urban surface, thus surface which are expressed in vegetation, are absorbed by the building. This is a prime water, soil and other physical features of land reason for the high urban heat island effects while land use simply refers to the actual use to (UHIEs) experienced in different cities of the which land is used by humans and their habitat – world. usually with accent on the functional role of land for economic activities. Although as suggested There exist several models often adopted for by Rawat and Kumar [4], land use affects land LU/C studies, however, one of the most cover and that changes in land cover affects land quantitative adopted continuum-based approach use as well. used for LU/C studies is the Ridd’s Model, otherwise known as the V-I-S model. This model According to UN-Habitat [5], Anambra State with is based on the assumption that the urban fabric a growth rate of 2.21% per annum and 60% of is complex and heterogeneous and that the her population residing in urban centres, has urban land cover (as tele-connected as it can be) been noted as the third most urbanized state in is a linear combination of three (3) biophysical Nigeria. The state has also experienced rapid components: Vegetation, Impervious Surface population increase and attendant urban and Soil, hence the name, V-I-S Model [13]. 2 Musa et al.; JGEESI, 11(4): 1-19, 2017; Article no.JGEESI.35209 Proposed as a fundamental theory, the V-I-S 2. METHODOLOGY model was developed to simplify the quantification of different surface components 2.1 Description of the Study Area which are not often times orthometrically or spatially separated in satellite imageries [14,15]. Awka is the administrative capital of Anambra The components of the VIS models as adopted State. It is located absolutely between Latitude in this study are represented as a range of 6°06'N and 6°16'N, and Longitude 7°01'E and values where features or pixels can be shown as 7°10'E of the Greenwich Meridian [7]. See Figure a set of combination of the components within 1a. It is majorly an annex of two Local certain thresholds. Thus, it has been recognized Government Areas (Awka North and South) as that the spatial varying character of land cover as shown in Fig. 1b. For the purpose of this study, shown in the study of Ridd [13], can be better however, the delineation of Awka Metropolis was described by probability surfaces [16]. In other achieved by gridding the whole State using a 5 words, each pixel is allowed to have a “class km by 5 km system, from which a 3 x 3 grid member” probability rather than a single class blocks were then used to demarcate the urban label and the result of this operation has been area of Awka as seen in Fig. 1b. The towns in idealized by Eastman [17] in his soft Awka Metropolis (as delineated) include classification basis. This is said to offer more Amawbia, Enugwu Agidi, Enugwu-Ukwu, Isiagu, meaningful information to planners in better Amansea, Ifite, Nawfia, Okpuno, Nibo, etc. See understanding land use patterns and changes the Maps in Fig. 1c. Although there are local over time. Hence, from this basis, land use variations, Awka town according to Ezenwaji, classification could then be based on the degree Phil-Eze, Otti, & Eduputa [22], has an average of membership rather than just a member and elevation of 99m. Meanwhile, Rivers that drain again, such a perspective can be more objective the area, Awka, are Haba, Obizi and Obibia in relating land use/cover to other surface Rivers in the South, Obizi Okpuno River in the phenomena.
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