A dynamic human activity-driven model for mixed land use evaluation using social media data

作者：Xing, Hanfa; Meng, Yuan^*; Shi, Yan^*

来源：Transactions in GIS, 2018, 22(5): 1130-1151.

DOI：10.1111/tgis.12447

Massive amounts of social media data have enabled the evaluation of mixed land use from the human activities perspective. While most studies have focused on approaches to better measure mixed land use, the dynamic activity patterns used to distinguish land use types have seldom been discussed. In light of this, in this study, a mixed land use evaluation model is constructed, which is driven by dynamic human activities hidden in social media data. Specifically, temporal topics related to human activities are first extracted from Twitter messages. On this basis, these topics are clustered with successive measurements of both temporal and semantic similarities, and then, they are further transformed into dynamic features. In addition, the dynamic feature-based Shannon entropy is employed for mixed land use evaluation. For verification, the building classes from OpenStreetMap are referenced to investigate their correlations with dynamic features in mixed land uses. Finally, a strong correlation demonstrates the effectiveness and power of the proposed method in the evaluation of mixed land uses.

• 出版日期2018-10
• 单位中南大学; 武汉大学; 山东师范大学