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Detection of Urban Development in Uyo (Nigeria) Using Remote Sensing

by Etido Essien 1,* and Samimi Cyrus 1,2,3,*
1
Climatology Research Group, University of Bayreuth, Zapf building 4, 95448 Bayreuth, Germany
2
Institute of African Studies, University Bayreuth, Klimatologie, 95440 Bayreuth, Germany
3
Bayreuth Centre of Ecology and Environmental Research (BAYCEER), University Bayreuth, Klimatologie, 95440 Bayreuth, Germany
*
Authors to whom correspondence should be addressed.
Land 2019, 8(6), 102; https://doi.org/10.3390/land8060102
Received: 29 March 2019 / Revised: 20 May 2019 / Accepted: 24 June 2019 / Published: 25 June 2019
(This article belongs to the Special Issue Monitoring Land Cover Change: Towards Sustainability)
Uyo is one of the fastest-growing cities in Nigeria. In recent years, there has been a widespread change in land use, yet to date, there is no thorough mapping of vegetation change across the area. This study focuses on land use change, urban development, and the driving forces behind natural vegetation loss in Uyo. Based on time series Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) image data, the relationships between urban land development and its influencing factors from 1985 to 2018 were analyzed using remote sensing (RS) and time series data. The results show eight land use cover classes. Three of these (forest, swamp vegetation, and mixed vegetation) are related to natural vegetation, and three (sparse built-up, dense built-up, and borrow pit) are direct consequences of urban infrastructure development changes to the landscape. Swamp vegetation, mixed vegetation, and forest are the most affected land use classes. Thus, the rapid growth of infrastructure and industrial centers and the rural and urban mobility of labor have resulted in an increased growth of built-up land. Additionally, the growth pattern of built-up land in Uyo corresponds with socioeconomic interviews conducted in the area. Land use changes in Uyo could be attributed to changes in economic structure, urbanization through infrastructure development, and population growth. Normalized difference vegetation index (NDVI) analysis shows a trend of decreasing vegetation in Uyo, which suggests that changes in economic structure represent a key driver of vegetation loss. Furthermore, the implementation of scientific and national policies by government agencies directed at reducing the effects of urbanization growth should be strengthened, in order to calm the disagreement between urban developers and environmental managers and promote sustainable land use. View Full-Text
Keywords: Land use; remote sensing; urban expansion; Landsat; NDVI Land use; remote sensing; urban expansion; Landsat; NDVI
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Essien, E.; Cyrus, S. Detection of Urban Development in Uyo (Nigeria) Using Remote Sensing. Land 2019, 8, 102.

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