空间大数据在土地和住房领域的应用

Yeunwoo Jeong, Jong-Hun Yu
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引用次数: 0

摘要

本研究提出韩国的大数据政策和案例研究以及空间大数据在土地和住房方面的应用,以挖掘未来的业务,并提前为政府政策提出基于空间大数据的应用。因此,首先对韩国的大数据政策和案例进行了评估。以政府3.0委员会为中心,政府各部门信息正在建立基于大数据的系统,国土交通部从2013年开始建立空间大数据系统,通过全国空间信息和创造就业平台支持大数据应用。其次,以LH建立和管理的信息系统为基础,对国土信息和土地住房应用现状进行了评价。首先,将信息系统主要分为公共管理支持、统计视图、房地产信息、网上信访、国家政策支持,并将国土信息(DB)、应用需求(工作范围)、利润创造(商业模式)作为主要应用的基本方向。在基本方向设置完成后,通过对工作范围和工作流程的评估,提炼出区域开发业务候选用地选择、租赁住房管理运营、土地保存优先设置、城市生成优先设置四个应用领域。第三,为实现空间大数据在提取的四个领域的应用体系,提出了每个应用领域所需的数据和应用分析流程,并为实现空间大数据的应用解决方案,提出了LH需要改进和未来评估的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utilizing Spatial Big Data for Land and Housing Sector
This study proposes the big data policy and case studies in Korea and the application of land and housing of spatial big data to excavate the future business and to propose the spatial big data based application for the government policy in advance. As a result, at first, the policy and cases of big data in Korea were evaluated. Centered on the Government 3.0 Committee, the information from each department of government is being established with the big-data-based system, and the Ministry of Land, Infrastructure, and Transport is establishing the spatial big data system from 2013 to support application of big data through the platform of national spatial information and job creation. Second, based on the information system established and administrated by LH, the status of national territory information and the application of land and housing were evaluated. First of all, the information system is categorized mainly into the support of public ministration, statistical view, real estate information, on-line petition, and national policy support, and as a basic direction of major application, the national territory information (DB), demand of application (scope of work), and profit creation (business model) were regarded. After the settings of such basic direction, as a result of evaluating an approach in terms of work scope and work procedure, the four application fields were extracted: selection of candidate land for regional development business, administration and operation of rental house, settings of priority for land preservation, and settings of priority for urban generation. Third, to implement the application system of spatial big data in the four fields extracted, the required data and application and analytic procedures for each application field were proposed, and to implement the application solution of spatial big data, the improvement and future direction of evaluation required from LH were proposed.
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