Predicting urban sprawl and land use changes in Akure region using markov chains modeling

Abstract

This study makes use of Markov chains modeling to predict sprawl and pattern of land use change in Akure region. Efforts were made to examine the trend of the expansion using Aerial Imagery Interpolation (AII). It focuses on overlaying of Landsat TM imageries of 1986, 2002, 2007 and 2014 to determine the land use changes and extent of expansion between 1985 and 2014. The land use were classified and displayed in colors for better visualization. With the aid of Markov chain modeling, the study made a projection of possible land use area and extent of expansion by the year 2034. Findings revealed continuous expansion in the growth of the city as evident in percentage increase of the builtup area. There were incompatible conversions in land uses and unguided expansions leading to undue encroachment into green areas at the suburbs. It was observed that without appropriate attention to adequate planning for effective measures, the trend of changing agricultural and forested lands to builtup areas will continue to increase with attendant effects on regional environment. Consequently, the study suggests effective zoning strategy and sustainable monitoring measures by different stakeholders in urban planning to check indiscriminate urban expansion in the study area.

Dynamics of Land Use and Land Cover Changes in Harare, Zimbabwe: A Case Study on the Linkage between Drivers and the Axis of Urban Expansion

“…The spectral differences and characteristics between Landsat 5 TM and Landsat 8 OLI sensors may have affected the accuracy of the thematic maps [23]. Despite these potential discrepancies, the classification and results obtained in the current study have relatively high accuracy considering urban area spectral heterogeneity characteristics and spectral confusion from land cover classes, and the results agree with other published scientific studies carried out at the national and regional level (Supplementary Materials Table S1) [6,24,26,27]. The use of hyper-spectral data and aggregation of urban built-up areas have been observed to improve and enhance the analysis of remote sensing data in urban areas [50,52].…”

“…An increase of 219.5% in LULC change, mainly attributed to land development at the expense of cropland, fallow land, water, shrub and bare land, was revealed in the Shanghai metropolis between 1997 and 2008 showing the impact of land use change and population growth in urban areas [51]. Akure city in the southwest of Nigeria experienced a similar loss of areas covered by vegetation and water bodies as the Harare Metropolitan Province due to the fact of built-up area expansion, from 5.1% in 1986 to 53.41% in 2014 for the total area under investigation [6].…”

“…Such actions result in the transformation of natural landscapes into agricultural landscapes [3]. Consequently, this leads to environmental degradation through deterioration of vegetation and sealing, often resulting in increasing surface runoff, soil erosion, surface water contamination, and exploitation of natural habitats [4][5][6]. Muller et al [7] highlights that urbanization is one of the greatest factors contributing to biodiversity loss due to the expansion of industrial, residential and commercial business areas.…”

“…To further understand the relationship between urbanization and environmental alteration, LULC changes need to be assessed and evaluated to determine the extent and the rate at which human activities are contributing to shifts in the environment. The integration of remote sensing data to monitor the state and dynamics of the Earth's surface provides reasonable results in a short space of time [6], compared to on-site surveying techniques [14,15]. Moderate resolution Landsat Thematic Mapper images (TM) are a standard tool used for urban mapping and change detection analysis and were used, for example in Minnesota, USA between 1986 and 2002 for LULC changes [16].…”

Spatio-temporal distribution and classification of utilization of urban bare lots in low-slope hilly regions

“…Because of their scattered distribution and small areas, urban bare lots are often ignored during the monitoring, research, and LULC planning in urban locations [ 26 , 27 ]. In addition, in the current land use classification system in China, urban bare lots are classified under unused land, while traditional research on urban bare lots has mainly focused on the physical characteristics and functions of urban bare lots such as soil-water-heat exchange [ 28 , 29 ], with hardly any research exploring the formation, transformation, redevelopment, and utilization of urban bare lots.…”