Modeling method of characteristics of population space-time dynamic moving based on multisource data fusion

Abstract

The invention provides a modeling method of the characteristics of population space-time dynamic moving based on multisource data fusion. The modeling method comprises: A. inputting map data, mobile phone locating data and floating vehicle data into a system and managing data organization according to requirements; B. establishing a spatial analysis model of the characteristics of population moving based on the mobile phone locating data and the floating vehicle data; C. applying the spatial analysis model of the characteristics of the population moving to carry out multisource data fusion of the map data, the mobile phone locating data and the floating vehicle data to obtain integrated information of the characteristics of the population moving; and D. analyzing the characteristics of various population moving according to the integrated information of the characteristics of the population moving and publishing an analyzed result by the geographic information system. The modeling method can acquire data of urban population space-time dynamic distribution and moving characteristics with large data amount, high quality and space-time characteristics, obtain basis of accurate population distribution and population moving characteristics, and provide decision-making supports for urban planning, land use planning, transportation planning and the like.

Description

technical field [0001] The invention relates to a modeling technology of population spatiotemporal dynamic travel characteristics, more specifically, a modeling method for population spatiotemporal dynamic travel characteristics based on multi-source data fusion. Background technique [0002] A city is a complex socio-economic system, and various activities of the population in the urban system are reflected by the dynamic distribution of the population. Through geographic information system (Geographic Information System, referred to as "GIS"), traffic survey, traffic analysis and its social attributes, spatial attributes, spatial behavior, etc. are linked to conduct traffic spatial analysis, explore the relationship between population distribution characteristics and cities, and understand It is of great significance to reveal the laws and provide auxiliary decision-making for urban management, urban planning and traffic planning. [0003] Therefore, how to use high-tech ...

AI Technical Summary

Problems solved by technology

[0004] Conventional artificial distribution modeling methods are generally based on censuses and population surveys. The data quality of this survey method is poor, the cost is high, the sampling sample is limited, the cycle is long, and a comprehensive survey is usually carried out at intervals of several years. Unable to grasp the dynamic characteristics of population distribution information

At the same time, spatial analysis is generally carried out by matching the data of the original-destination ("OD" for short) to the road network or traffic area according to the shortest path, which cannot strictly reflect the spatial-temporal dynamic distribution characteristics of the population.

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