With the increasing availability of location‐aware devices, passively collected big GPS trajectory data offer new opportunities for analyzing human mobility. Processing big GPS trajectory data, especially extracting information from billions of trajectory points and assigning information to corresponding road segments in road networks, is a challenging but necessary task for researchers to take full advantage of big data. In this research, we propose an Apache Spark and Sedona‐based computing framework that is capable of estimating traffic speeds for statewide road networks from GPS trajectory data. Taking advantage of spatial resilient distributed datasets supported by Sedona, the framework provides high computing efficiency while using affordable computing resources for map matching and waypoint gap filling. Using a mobility dataset of 126 million trajectory points collected in California, and a road network inclusive of all road types, we computed hourly speed estimates for approximately 600,000 segments across the state. Comparing speed estimates for freeway segments with speed limits, our speed estimates showed that speeding on freeways occurred mostly during the nighttime, while analysis of travel on residential roads showed that speeds were relatively stable over the 24‐h period.
Abstract. GNSS reference station network is the core infrastructure for the establishment ,maintenance, renewal and service of national geodetic reference framework. At present ,nearly 3000 reference stations have been constructed in the national resources system ,of which about 2500 stations have the continuous observation capacity of BDS signal. In the face of daily massive observation data, the traditional sub-network and fully combined baselines can not meet the needs of rapid data processing for the maintenance of geodetic coordinate framework.In this paper, the high-precision and fast processing of BDS observation data of large-scale GNSS reference station network (≥ 300 stations) is realized through modular design, non difference model, parameter management to be estimated and flexible ambiguity processing. Through the whole network calculation of the 7-day BDS observation data of about 500 MGEX stations and national reference stations that selected all around the world from 211 to 217 days in 2017, the positioning results show that the average RMS values of the coordinates in the three directions of station N,E and U are ±2.3mm, ±2.8mm and ±4.6mm respectively. The orbit determination results show that the average accuracy of GPS satellite orbit in three directions is better than ±2cm; BDS MEO / IGSO track accuracy is better than ±20cm and GEO track accuracy is better than ±200cm.
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