ACM Computing Surveys (CSUR)
Toward tighter integration of web search with a geographic information system
Proceedings of the 15th international conference on World Wide Web
Estimation of link speed using pattern classification of GPS probe car data
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
Exploring urban characteristics using movement history of mass mobile microbloggers
Proceedings of the Eleventh Workshop on Mobile Computing Systems & Applications
Measuring geographical regularities of crowd behaviors for Twitter-based geo-social event detection
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
Monitoring geo-social activities through micro-blogging sites
DASFAA'10 Proceedings of the 15th international conference on Database systems for advanced applications
Inferring and focusing areas of interest from GPS traces
W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
From taxi GPS traces to social and community dynamics: A survey
ACM Computing Surveys (CSUR)
| Hi-index | 0.01 |
Driven by travel demand, the distribution and density of taxi passenger pick-up and drop-off points reflect the attractiveness of an area and thus, can be used to find out hot spots and the movement of human flow, to benefit location-based services (LBS) and transport planning, etc. There exist some point pattern analysis (PPA) methods can facilitate the analysis. But most of them lack of the ability to integrate with location-based data in geo-visualization environment. We build an interactive visualization system based on mashup technique to contain diverse analysis data and applications under one framework. Two PPA methods--Kernel Density Estimation (KDE) and Agglomerative Hierarchical Clustering (AHC) are used to discover the hot spots. Microsoft Virtual Earth is used as data integration and visualization platform by combining with some other web techniques, to display analysis results in both static and dynamic effect. This study on one hand represents a novel application of vehicle trajectory data, reveals urban hot spots and traffic pattern, and addresses data integration and geo-visualization issues on the other hand. Preliminary attempt can benefit LBS and LBSN (Location-based Social Network) related web applications.