Revealing the User Behavior Pattern Using HNCORS RTK Location Big Data

Abstract

Hunan continuously operating reference station network is one of the most important infrastructures of the regional geospatial datum in Hunan province, China. It provides the official 24-h RTK service to the public. How to reveal the user behavior pattern by spatiooral analysis on location-based big data is significant for the service promotion. With procedures, such as cleaning, sampling, and so on, the usage count, fixing rate, and network delay data from August 2017 to July 2018 are first analyzed on multiple spatial and temporal scales. The results show that user behavior is strongly correlated to the surveying field work habits. Overall, the usage count is much more in the central and eastern, developed, and plain or hill area, while it is less in the western, underdeveloped, mountain and lake area. The suburbs are the most popular area. The usage count is also correlated to the local economic profile. Meanwhile, the Huaihua and Shaoyang cities need to be paid more attention to promotions. The hot spots revolution in 24 h can be divided into six stages as sleeping, recovery, first and second busy stages, adjustment, and dormancy when the hot spot successively increased and decreased around the Changsha-Zhuzhou-Xiangtan urban agglomeration and other 11 urban centers in the Hunan province.