Identification and classification of urban employment centers based on big data: A case study of Beijing

• Published in: PloS one Vol. 19; no. 5; p. e0299726
• Main Authors: Wang, Liang, Cui, He
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 24.05.2024; Public Library of Science (PLoS)
• Subjects: Accuracy; Algorithms; Beijing; Big Data; Case studies; Cities; Classification; Cluster analysis; Clustering; Commuting; Density distribution; Economic statistics; Employment; Employment - statistics & numerical data; Humans; Identification; Land use; Layouts; Local transit; Population density; Radiation; Research methodology; Retail industry; Service facilities; Social service; Transportation - statistics & numerical data; Urban Population; Urban transportation; Vector quantization; Workplace; Beijing; China; Beijing China; Los Angeles California; United States > US

The layout, scale and spatial form of urban employment centers are important guidelines for the rational layout of public service facilities such as urban transportation, medical care, and education. In this paper, we use Internet cell phone positioning data to identify the workplace and residence o...