| 摘要: |
| 通勤绿道对于鼓励居民健康低碳出行、缓解城市交
通拥堵具有非常重要的作用。随着互联网的发展和数据的公
开，获取人们日常通勤数据，优化城市通勤绿道成为可能。
对此，以杭州市未来科技城核心片区为例，探讨基于居民通
勤行为大数据的绿道选线方法，首先通过人们的出行行为分
析确定绿道关键接驳点，其次通过建设适宜性分析建立综合
阻力模型，运用Linkage Mapper工具进行选线模拟，最
后对选线模拟结果优化确定最终选线。根据通勤绿道所依托
道路的道路类型，将通勤绿道分为三级，形成了“八主七次
十二支”的绿道通勤网络。这为未来城市通勤绿道的规划提
供了一种新的思路，将有利于实现居民绿色健康通勤，完善
城市绿道网络体系。 |
| 关键词: 风景园林 通勤绿道 通勤行为 选线 多源数据 |
| DOI：10.19775/j.cla.2024.08.0097 |
| 投稿时间：2023-07-26修订日期：2023-10-30 |
| 基金项目: |
|
| Commuter Greenway Route Selection Study Basedon Multi-source Data Research |
| LI Linke,WU Xiaohua,YING Jun,ZHAO Ruoxi,LI Angyang |
| Abstract: |
| Commuter greenways play a very important role in
encouraging residents to travel in a healthy and low-carbon way
and alleviating urban traffic congestion. With the development
of the Internet and the disclosure of data, it has become possible
to obtain people's daily commuting data and optimize urban
commuting greenways. In this regard, this paper takes the core
area of Hangzhou Future Science and Technology City as an
example to explore the greenway routing method based on the
big data of residents' commuting behavior, firstly, to determine
the key connection points of the greenway through the analysis of
people's travel behavior, secondly, to establish a comprehensive
resistance model through the analysis of the construction suitability,
to conduct routing simulation by using Linkage Mapper tool, and
finally, to optimize the results of the routing simulation to determine
the final route selection. According to the road type of the road on
which the commuter greenway is based, the commuter greenway
is categorized into three levels, forming a greenway commuter
network of "eight main, seven secondary and twelve branches". This
provides a new way of thinking for the future planning of urban
commuter greenways, which will be conducive to the realization of
green and healthy commuting for residents and the improvement of
the urban greenway network system. |
| Key words: landscape architecture commuter greenway commuter
behavior route selection multi-source data |
