Job-housing space evaluation method and system under different scales based on multi-data integration

An evaluation method and multi-data technology, applied in data processing applications, instruments, computing, etc., can solve problems such as the inability to comprehensively obtain the spatial characteristics of urban jobs and residences, and achieve the effect of layout optimization.

Active Publication Date: 2018-10-30
深圳市数字城市工程研究中心 +1
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Problems solved by technology

[0005] In the existing methods, only one scale (region or city) is studied, and the application of traditional data and big data are

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  • Job-housing space evaluation method and system under different scales based on multi-data integration
  • Job-housing space evaluation method and system under different scales based on multi-data integration
  • Job-housing space evaluation method and system under different scales based on multi-data integration

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Embodiment Construction

[0040] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0041] A method for evaluating occupational and housing space at different scales based on multi-data fusion, including the following steps:

[0042] Step A: Data collection and processing. First, through the city statistical yearbook, collect the year-end resident population data and employee data at the city level, and unify the units. Secondly, collect POI data. For example, the POI data of Gaode map can be crawled by crawler software. Each piece of data contains the basic spatial information and attribute information such as the name, category, address, longitude and latitude, and administrative area of ​​the point; then according to the longitude and latitude information of the POI data for visualization.

[0043] Step B: Evaluation of macro-scale occupation and housing space based on traditional da...

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Abstract

The invention discloses a job-housing space evaluation method under different scales based on multi-data integration. The method comprises the steps of collecting year-end permanent resident population data, employee data and POI data of a target city; carrying out data processing for a macro level of the city and a medium level of each district; and carrying out an analytic hierarchy process fordifferent types of POI data, differentiating weight of different scales and properties of POI data of the same function, and establishing job-housing space evaluation standards under the different scales. A job-housing space evaluation system under different scales based on multi-data integration comprises a data collection processing module and a job-housing deviation degree index evaluation module. According to the method and the system, job-housing space evaluation technologies under the different scales are established, the city job-housing place space distribution can be identified comprehensively, timely and accurately, the relatively scientific reference basis for city job-housing space and infrastructure layout optimization is provided, and the method and the system can be widely applied to the field of city job-housing space evaluation.

Description

technical field [0001] The present invention relates to the field of occupational and housing space evaluation, specifically a method and system for evaluating occupational and housing space at different scales based on multi-data fusion. Background technique [0002] With the rapid development of the economy and the continuous advancement of the urbanization process, the scale of the city has a tendency to gradually expand outward. The spatial relationship between the place of residence and the place of employment has evolved from "combination of occupation and residence" to "separation of occupation and residence", and the degree of separation between occupation and residence has intensified. At the same time, the contradiction between residents' growing public service demand and the shortage of public service supply The accessibility and convenience of residents' transportation, entertainment, medical care, and shopping facilities have all declined significantly. The rat...

Claims

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Application Information

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IPC IPC(8): G06Q50/26
CPCG06Q50/26
Inventor 张文晖岳隽陈小祥徐雅莉郜昂李嘉诚汪维录童岩冰
Owner 深圳市数字城市工程研究中心
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