Modeling the drivers of urban land use changes in Lusaka, Zambia using multi-criteria evaluation: An analytic network process approach. (March 2020)

• Record Type: Journal Article
• Authors: Simwanda, Matamyo; Murayama, Yuji; Ranagalage, Manjula
• Is Part Of: Land use policy. Volume 92(2020)
• Publication Date: 2020-03
• Subjects: Analytic network process -- Urban land use -- Drivers and indicators -- Planning and policy -- Lusaka -- Zambia; Land use -- Periodicals; Land use -- Government policy -- Periodicals; Sol, Utilisation du -- Périodiques; Sol, Utilisation du -- Politique gouvernementale -- Périodiques; Electronic journals; 333.7305
• DOI: 10.1016/j.landusepol.2019.104441
• Languages: English
• ISSNs: 0264-8377

Abstract

Graphical abstract: Highlights: New framework to model drivers of urban land use (urban-LU) changes using the analytic network process (ANP) is proposed. Study emphasizes the need to understand the drivers of unplanned versus planned urban-LU in sub-Saharan Africa. ANP model explains the interrelationships of urban-LU drivers and their role in the urban-LU change process of Lusaka. Migration, economic opportunities, social services and land market identified as main drivers of urban-LU changes. Study revealed that informal settlements and commercial and industrial areas had the fastest growth. Abstract: Curbing the historically unplanned urban development in African cities crucially demands that the drivers of urban land use (urban-LU) changes are comprehended. However, this has become a complex decision problem for African urban planners and policy makers owing to the interconnections among urban-LU drivers and the complicated mixed development of planned and unplanned areas. Therefore, this study presents a new framework to model drivers of urban-LU changes in Lusaka, Zambia for the last 50 years using ground questionnaire surveys and the analytic network process (ANP). The study considers the growth of six urban-LUs, namely, unplanned high density residential (UHDR), unplanned low density residential (ULDR); planned medium-high density residential (PMHDR), planned low density residential (PLDR), commercial and industrial (CMI); and public institutions and service (PIS). The results revealed that socio-economic (55.11 %) and population (27.37 %) factors have been the major drivers of urban-LU changes while political factors (13.07 %) have also played a role. The role of biophysical factors (4.44 %) has been insignificant. The ANP model ranks UHDR (1st) and CMI (2nd) areas as the fastest-growing primarily driven by interactions amongst migration, economic opportunities, social services and land market. The growth of PMHDR, PIS and PLDR areas, ranked 3rd, 4th and 5th, respectively, has been largely driven by plans and policies and the political situation. The growth of ULDR areas is ranked (6th) as the lowest. The study discusses the urban planning and land use policy implications and suggests several strategies including strengthening of the local planning authority; improvement of the land tenure policies and delivery systems; establishment of satellite economic zones to decongest the city; investment in both green and blue infrastructure; and timely policy reviews.