Detection of clusters in traffic networks based on spatio‐temporal flow modeling     

Yan Shi  Min Deng  Jianya Gong  Chang‐Tien Lu  Xuexi Yang  Huimin Liu 《Transactions in GIS》2019,23(2):312-333

Spatio‐temporal clustering is a highly active research topic and a challenging issue in spatio‐temporal data mining. Many spatio‐temporal clustering methods have been designed for geo‐referenced time series. Under some special circumstances, such as monitoring traffic flow on roads, existing methods cannot handle the temporally dynamic and spatially heterogeneous correlations among road segments when detecting clusters. Therefore, this article develops a spatio‐temporal flow‐based approach to detect clusters in traffic networks. First, a spatio‐temporal flow process is modeled by combining network topology relations with real‐time traffic status. On this basis, spatio‐temporal neighborhoods are captured by considering traffic time‐series similarity in spatio‐temporal flows. Spatio‐temporal clusters are further formed by successive connection of spatio‐temporal neighbors. Experiments on traffic time series of central London's road network on both weekdays and weekends are performed to demonstrate the effectiveness and practicality of the proposed method.  相似文献   

Establishing an early warning system for flash floods in Hoang Su Phi District,Ha Giang Province,Vietnam     

Thach Ngoc Nguyen  Canh Xuan Pham  Huy Quoc Nguyen  Toan Ngo Bao Dang 《Singapore journal of tropical geography》2019,40(2):312-333

Hoang Su Phi is a mountainous district in Ha Giang province, Vietnam. When the rainy season arrives in these parts, flash floods (besides landslides), frequently occur in many areas, seriously affecting the socio‐economic condition of the district. Therefore, in this paper, we have developed an early warning system for flash floods, established based on a geomorphological and hydrological approach. The basic principle underlying this system is the fact that flash floods will often occur where there is high potential risk with sufficient rainfall. In the model, eight parameters of the basin were used to build a potential flash flood map. Using the spatial processing module in an open source software, early predictions from automatic weather stations were interpolated and processed online to produce a potential risk map. Depending on the threshold of precipitation values, the results determined locations where flash flood may occur at various flash flood risk indices (FFRI). The system may be applied to support provision of early flash flood warning up to 1?6 days in advance in the district, allowing the local government ample time to make appropriate decisions on the prevention and/or mitigation of damages caused by flash flood hazards.  相似文献