使用梯度增强决策树检查快递站空间分布的影响因素:中国南京的一个案例研究
1School of Architecture, Southeast University, Nanjing, China.
PloS one
|July 14, 2023
概括
在线购物驱动器表达了配送站的增长. 这些车站聚集在商业零售和住宅区附近,优化城市物流和消费者访问.
科学领域:
- 城市地理 城市地理
- 物流和供应链管理的物流和供应链管理.
- 空间分析 空间分析
背景情况:
- 电子商务的兴起大大推动了物流和快递业.
- 快递站是城市消费和商业服务空间的组成部分,影响居民的日常生活.
- 了解这些设施的空间分布对于高效的城市规划至关重要.
研究的目的:
- 分析影响终端物流空间空间空间分布的关键因素,特别是快递站,在网上购物的背景下.
- 建立一个分析框架,以了解快递站与其他城市功能空间之间的关系.
- 为改善快递基础设施的战略布局和管理提供见解.
主要方法:
- 利用梯度增强决策树 (GBDT) 来识别和量化影响快递站空间分布的因素.
- 分析了快递站与各种城市功能区 (包括商业零售和住宅区) 之间的空间关联.
- 为空间分布的决定因素开发了一个全面的分析框架.
主要成果:
- 该研究发现,商业零售区和住宅社区是影响快递站空间分布的主要驱动因素.
- 快递站表现出明显的集群模式,集中在消费者活动和居住密度较高的地区.
- 在快递站的位置和接近消费者和住宅空间之间发现了明确的关联.
结论:
- 快递站的空间分布与商业和住宅用地使用有很大的相关性.
- 这些发现支持在以消费者为中心和住宅区的配送站的战略定位,以提高效率.
- 这项研究有助于优化终端物流空间的规划和管理,以电子商务为驱动的快速城市化环境.
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