Vehicle tracking data for thousands of urban vehicles and the availability of digital map provide urban planners unprecedented opportunities for better understanding urban transportation. In this paper, we aim to detect traffic hot spots on urban road networks using vehicle tracking data. Our approach first proposes an integrated map-matching algorithm based on the road buffer and vehicle driving direction, to find out which road segment the vehicle is travelling on. Then, we estimate travel speed by calculating the average the speed of every vehicle on a certain road segment, which indicates traffic status, and create the spatial weights matrices based on the connectivity of road segments, which expresses the spatial dependence between each road segment. Finally, the measure of global and local spatial autocorrelation is used to evaluate the spatial distribution of the traffic condition and reveal the traffic hot spots on the road networks. Experiments based on the taxi tracking data and urban road network data from Wuhan have been performed to validate the detection effectiveness.
As the development of the theory and technology of geographical information, Geographical Information System (GIS)
has been widely applied in variety of industries. It usually refers to the analytical problem of multi-factor in GIS thematic
application. In this field, the determination of factors' weight is a common and important problem. It actually deals the
data when processing the spatial analysis applying GIS, for example, according to the importance of some factor, assign
some value to it then process spatial overlay operation using the values and finally conclude some evaluation or result. In
reality, there are many factors that affect the some kind of evaluation. Usually, we choose several more important factors
as the evaluation criterion in order to make convenient for research. Then we assign some weight values to these factors
and process spatial analysis then conclude some decision or evaluation to make support for decision-making. We can
choose the factors that can make more impaction on the evaluation or decision-making using the method of Analytical
Hierarchy Process (AHP). However, it has strong subjectivity of the factors' weight values assigned by this method.
Rough set theory, which can effectively remove the impaction made by artificial factors, can make up the deficiency. It
can make the spatial analysis more objective and more effective combining the two methods in GIS spatial analysis.
Object selection is an important technical problem in the process of map generalization. Considering creative-thinking
characteristic of map generalization process, the paper bring the Rough Set theory from spatial data mine field to map
generalization field, put forward a new thought for map generalization based on classification idea of Rough Set. The
method of Rough Set which has the benefit on enormous data with the imperfection and non-precision character has
become a new tool to make research on spatial data mining. The paper analyzes the imperfection characters of
geo-spatial data processing based on Rough Set and the selection problem in the processing of map generalization with
classification thought; presents the thought that map generalization is a kind of classification for map objects. The
method mentioned in this paper use different spatial and attribute information as different point of view to observe the
map objects. The result of the classification is ordered by the weightiness of all kinds of factors. In the end, a river
objects selection test validates the rough set map generalization method mentioned in this paper.
Networked Virtual Reality (NVR) is a system based on net connected and spatial information shared, whose demands cannot be fully meet by the existing architectures and application patterns of VR to some extent. In this paper, we propose a new architecture of NVR based on Multi-Agent framework. which includes the detailed definition of various agents and their functions and full description of the collaboration mechanism, Through the prototype system test with DEM Data and 3D Models Data, the advantages of Multi-Agent based Networked Virtual Reality System in terms of the data loading time, user response time and scene construction time etc. are verified. First, we introduce the characters of Networked Virtual Realty and the characters of Multi-Agent technique in Section 1. Then we give the architecture design of Networked Virtual Realty based on Multi-Agent in Section 2.The Section 2 content includes the rule of task division, the multi-agent architecture design to implement Networked Virtual Realty and the function of agents. Section 3 shows the prototype implementation according to the design. Finally, Section 4 discusses the benefits of using Multi-Agent to implement geovisualization of Networked Virtual Realty.