Predictive Modeling of Transport Infrastructure Space for Urban Growth Phenomena in Developing Countries’ Cities: A Case Study of Kano — Nigeria

Suleiman Hassan Otuoze,Dexter V L Hunt,Ian Jefferson

doi:10.3390/su13010308

Suleiman Hassan Otuoze, Dexter V L Hunt + Show 1 more

Open Access

https://doi.org/10.3390/su13010308

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Journal: Sustainability	Publication Date: Dec 31, 2020
Citations: 4	License type: CC BY 4.0

Affiliation: University of Birmingham, Ahmadu Bello University

Abstract

Global urbanization has the most tremendous negative effects on the changing landscapes in many developing countries’ cities. It is necessary to develop appropriate monitoring techniques for tracking transport space evolution. The work explores the impacts of urban growth dynamics of transport space over the past decades as a basis for predicting future space demands in Kano, Nigeria. Three epochs of Landsat images from 1984, 2013 and 2019 were processed, classified and analyzed. Spatial classifications of land-use/land-cover (LULC) types in Kano include transport space, built-up areas, vegetation, farmland, bare land and water. The data analysis involves model calibration, validation and prediction using areas using the hybrid modeling techniques—cellular automata-Markov (CA-Markov) in IDIRISI SELVA 17.0 and remote-sensing ARC-GIS 10.7 softwares. The result finds significant expansion of transport and built-up areas while other LULC receded throughout the entire study period. Predictive modeling of transport infrastructure shows spatial expansion by 345 km2 (3.9%) and 410 km2 (11.7%) in 2030 and 2050 respectively. Kappa reliability indices of agreement (KIA) classified images and ground maps were 85%, 86% and 88%, respectively, for 1984, 2013 and 2019 time series. The calibration quality met the 80% minimum suggested in literature for the spatial-temporal track and prediction of urban growth phenomena.

Highlights

Urbanization has produced a variety of endemic structural changes in land-use/landcover (LULC) characteristics
LULC highlights the causal relationships between spatial transformations involving land conversion and adverse environmental ramifications
We developed a Markov probability transition matrix implemented in IDRISI SELVA 17 to forecast likely future scenarios of transport infrastructure and land-use ecology to Kano city’s urban form in 2030 to 2050 temporal periods after model validation

Summary

Introduction

Urbanization has produced a variety of endemic structural changes in land-use/landcover (LULC) characteristics. LULC highlights the causal relationships between spatial transformations involving land conversion and adverse environmental ramifications. Urban agglomerations inches closer to worrisome milestones, as cities assume new roles of de facto national economies of many countries [1]. The cities have become increasingly attractive to all strata of human society because of their strategic economic and political advantages, employment opportunities and availability of relevant infrastructures and facilities. Urbanization exerts a chain anthropogenic process on the natural environment and is arguably the major contributor to global land-use transition. LULC change is a complex mechanism that transforms natural landscapes, climate conditions and a major source of threat to environmental biology, ecological ‘flora and fauna’

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