Authors: Mengling Qiao*,
Topics: Human-Environment Geography
Keywords: human activity; collective activity space; economic segregation pattern; ICE; TFIDF
Session Type: Paper
Presentation File: No File Uploaded
Research on the realistic and comprehensive identification of the spatial patterns of economic segregation in a city range is valuable for the sustainable development of cities. The consideration of human activities in segregation research provides the inspiration to develop an alternative method to contribute to this type of research. In our method, we emphasize the combination of collective activity spaces (CASs) and spatial economic data, which are both obtained from dynamic human activities. In detail, we first reveal the realistic use of urban spaces from human mobility patterns to generate multilevel CASs as basic analytical units. Then, we use a type of realistic economic data generated from human activities to measure the segregation level of each CAS. We realize this measurement by tailoring a segregation index, named the Term Frequency-Inverse Document Frequency-Index of Concentration at the Extremes-based (TFIDF-ICE-based) segregation index, for our economic data. Through these methods, we can realistically and comprehensively uncover the multilevel spatial patterns of economic segregation in a city range. Using Beijing and Wuhan as cases, we demonstrate and discuss the applicability and value of our method.