Sithole Shelton Mthunzi, Musakwa Walter, Magidi James, Kibangou Alain Y
Dept. of Urban and Regional Planning, Faculty of Engineering and the Built Environment, Auckland Park Campus, University of Johannesburg, Johannesburg, South Africa.
Dept. of Geography, Environmental Management & Energy Studies, Faculty of Science, Auckland Park Campus, University of Johannesburg, Johannesburg, South Africa.
Heliyon. 2024 Mar 10;10(6):e27275. doi: 10.1016/j.heliyon.2024.e27275. eCollection 2024 Mar 30.
Urbanisation is a global trend that significantly impacts sustainable urban development and the quality of urban life. Assessing urban sprawl is critical for sustainable urban planning and aligns with the key objectives of the United Nations sustainable development goals. This study employed geospatial technology and landscape metrics to comprehensively assess, map, and quantify the extent of urban sprawl in Bulawayo from 1984 to 2022. The study leveraged the Support Vector Machine (SVM) supervised machine learning algorithm coupled with landscape metrics to achieve this objective. The combined approach allowed for the classification, detection of land cover changes, analysis of urban dynamics, and quantification of the degree of urban sprawl. The results revealed a 228% increase in built-up areas between 1984 and 2022, while non-built-up areas (agricultural land, vegetation, bare land) decreased by 29.28%. The landscape metrics and change analysis indicated an encroachment of urban-like conditions into urban areas. Land use change assessment revealed that Bulawayo exhibits four district types of urban sprawl: leapfrog, strip/ribbon, low density, and infill. Urban expansion is attributed to urbanisation and evolving land use policy. Urban sprawl has numerous urban planning implications on transport management, habitat loss and deforestation, reduction and contamination of freshwater sources, and many others. This study is strategic to planners, researchers, and decision-makers/policy makers as it provides relevant, up-to-date, and accurate information for sustainable urban planning.
城市化是一种全球趋势,对城市可持续发展和城市生活质量有着重大影响。评估城市扩张对于城市可持续规划至关重要,并且符合联合国可持续发展目标的关键宗旨。本研究运用地理空间技术和景观指标,全面评估、绘制并量化了1984年至2022年期间布拉瓦约市的城市扩张程度。该研究利用支持向量机(SVM)监督式机器学习算法并结合景观指标来实现这一目标。这种综合方法能够进行土地覆盖变化的分类、检测、城市动态分析以及城市扩张程度的量化。结果显示,1984年至2022年期间建成区面积增加了228%,而非建成区(农业用地、植被、裸地)减少了29.28%。景观指标和变化分析表明类似城市的状况正在向城市周边地区蔓延。土地利用变化评估显示,布拉瓦约呈现出四种城市扩张类型:蛙跳式、带状/条带状、低密度和填充式。城市扩张归因于城市化和不断演变的土地利用政策。城市扩张在交通管理、栖息地丧失和森林砍伐、淡水资源减少和污染等诸多方面对城市规划产生了诸多影响。本研究对规划者、研究人员以及决策者/政策制定者具有重要战略意义,因为它为城市可持续规划提供了相关、最新且准确的信息。