Modeling the drivers of urban land use changes in Lusaka, Zambia using multi-criteria evaluation: An analytic network process approach
Modeling the drivers of urban land use changes in Lusaka, Zambia using multi-criteria evaluation: An analytic network process approach
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DOI：
10.1016/j.landusepol.2019.104441
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发表时间：
2020-03
期刊：
影响因子：
7.1
通讯作者：
Matamyo Simwanda;Y. Murayama;M. Ranagalage
中科院分区：
文献类型：
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作者：
Matamyo Simwanda;Y. Murayama;M. Ranagalage
遏制非洲城市历史上无计划的城市发展至关重要，需要了解城市土地利用(城市-土地利用)变化的驱动因素。然而，对于非洲城市规划者和政策制定者来说，这已成为一个复杂的决策问题，因为城市-LU司机之间的相互联系，以及规划和非规划地区复杂的混合开发。因此，这项研究提出了一个新的框架，利用地面问卷调查和分析网络过程(ANP)来模拟赞比亚卢萨卡近50年来城市-土地利用变化的驱动因素。研究考虑了六个城市逻辑单元的增长，即非规划高密度住宅(UHDR)、非规划低密度住宅(ULDR)；规划中高密度住宅(PMHDR)、规划低密度住宅(PLDR)、商业和工业(CMI)；以及公共机构和服务(PIS)。结果表明，社会经济因素(55.11%)和人口因素(27.37%)是城市土地利用变化的主要驱动因素，政治因素(13.07%)也起作用。生物物理因素的作用不显著(4.44%)。ANP模型将UHDR(第一)和CMI(第二)地区列为增长最快的地区，主要受移民、经济机会、社会服务和土地市场之间的互动推动。PMHDR、PIS和PLDR地区的增长分别排在第3、第4和第5位，这在很大程度上是由计划和政策以及政治局势推动的。ULDR地区的增长排在第六位，是最低的。该研究讨论了城市规划和土地使用政策的影响，并提出了若干战略，包括加强地方规划当局；改进土地保有权政策和交付系统；建立卫星经济区以缓解城市的拥挤；投资于绿色和蓝色基础设施；以及及时进行政策审查。
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.