美国和加拿大大都会地区的新商业边界数据集,基于开放数据构建
Byeonghwa Jeong1, Jeff Allen2, Karen Chapple3
1Postdoctoral Fellow, School of Cities, University of Toronto, Toronto, Canada. byeonghwa.jeong@utoronto.ca.
Scientific data
|April 24, 2024
概括
研究人员使用密度数据和人工智能在69个美国和加拿大大都会地区定义了商业地理边界. 这项研究确定了23751个商业区,有助于城市规划和经济发展.
科学领域:
- 城市地理 城市地理
- 地理信息系统 (GIS) 是指地理信息系统.
- 计算社会科学 计算社会科学
背景情况:
- 确定商业区对于城市规划和经济分析至关重要.
- 现有的定义往往不一致,阻碍了对比研究.
- 都市商业景观是复杂的,需要精确的地理界限.
研究的目的:
- 建立一个一致的,数据驱动的商业地理边界定义.
- 在美国和加拿大的主要大都市地区划分和绘制商业区域.
- 为城市和区域规划和经济发展提供基础数据集.
主要方法:
- 收集了69个大都会地区的办公,零售和就业密度数据.
- 应用了一个无监督图像细分模型用于边界识别.
- 利用集群方法将商业区分组和定义.
主要成果:
- 在美国和加拿大大都会地区确定了23751个不同的商业区.
- 为各种商业类型 (市中心,零售中心等) 生成精确的地理边界. ) 的情况.
- 与已建立的商业相关数据对生成边界的准确性进行了验证.
结论:
- 该研究提供了商业区的新,一致的定义和绘图.
- 这些发现为北美大都市地区的商业地理提供了宝贵的见解.
- 生成的数据和代码是公开可用的,用于城市研究和政策制定.
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