多尺度的省级地籍管理综合数据库整合研究

发布时间：2018-07-07 23:45

本文选题：多尺度 + 省级　；参考：《吉林大学》2017年硕士论文

【摘要】：随着我国对地籍信息的需求不断加大,越来越凸显了地籍管理的重要性。计算机技术以及互联网技术的不断进步,使地籍管理也逐渐走向了信息化的道路。根据国土资源管理部门对地籍数据的需求,国家决定实行地籍数据库的建设工作,并制定了相应的数据库建设标准。随着第二次全国土地大调查的全面开展,城镇地籍、农村地籍调查,农村集体所有权确权的不断推进,全国范围内以县级为最小行政单元开展并完成了各类地籍数据库的建设。包括土地利用现状数据库、城镇地籍数据库、农村地籍数据库、农村集体土地确权登记发证数据库、土地登记数据库等。近几年国家对耕地后备资源进行全面大调查,又建设了耕地后备资源数据库。但是,虽然我国已经基本完成了地籍数据库的建设,但是各类数据库是以县级为单位进行分开存储、分类管理的,数据类型单一、现势性低、更新缓慢、不同类型数据库之间不能实现数据共享,已经难以满足省级国土部门对土地利用数据的全面、高效的使用需求。因此,建立集合省、市、县三级行政粒度的综合管理数据库对于国土资源管理部门对数据的统一管理和高效利用具有重要的意义。但是,不同类型数据库存在建库标准不一致、空间基准、数据格式不统一的现象,特别是比例尺精度存在很大的差异。例如土地利用现状数据库的比例尺为1:1万、城镇地籍数据库的比例尺为1:500、农村集体土地所有权确权数据库的比例尺为1:2000。数据精度的差异严重影响了地籍数据的统一调用和展示,不利于数据的宏观统计和分析。因此,如何解决多尺度地籍数据库整合问题是省级地籍管理综合数据库建设的主要问题。本文立足省级层面,并以吉林省数据库建设情况为参考对象,论述了多尺度地籍数据产生的原因、特征以及多尺度地籍数据的表现形式。制定了多尺度地籍数据库的整合流程,探讨了多尺度地籍数据的整合方案,解决了多尺度地籍数据的整合关键技术,以吉林省地籍数据为参照,从理论和实践相结合的角度,对整合后的结果进行了展示和分析。此外,在数据整合的基础上构建了省级地籍管理综合数据库的框架体系。通过对多尺度地籍管理综合数据库的整合研究过程,本文得出了以下几点结论:1、使地籍数据具有多尺度表征特性的主要影响因素主要来源于地籍数据获取的不确定性、建库需求的差异性、数据来源的多样化以及数据时间、空间的多尺度性。2、地籍数据存在建库标准不统一,数据格式、数学基础、参考投影等不一致现象。此外,行政范围多尺度性以及数据多尺度性妨碍了各级行政粒度之间数据的交流和共享,是建立省级地籍管理综合数据库的关键技术问题。3、对于整合过程中坐标投影转换方式以及数据格式统一方法,以吉林省地籍数据为基础,验证了采用投影参数转换法对坐标系进行统一以及基于FME技术的多种数据格式转换方式实现数据格式的一致性转换的方式具有可行性,为实现多尺度地籍数据整合提供了数据基础。4、根据各类基础数据应用的特点,提出了构建多尺度派生空间属性图层的方法解决多尺度地籍数据整合问题。研究实验表明,通过建立派生的属性关系表能够实现在不改变原数据的基础上对变化的图斑要素进行标记,对整合后变化的数据进行了记录,实现了数据的统计和汇总。此外,可以根据派生图层变化要素的属性信息对变化要素进行追溯,对数据的分析具有重要意义。
[Abstract]:With the increasing demand for cadastre information in China, the importance of cadastral management is becoming more and more important. The continuous progress of computer technology and Internet technology makes cadastre management gradually to the road of information. According to the demand of land and resources management departments on cadastral data, the state has decided to implement the construction of cadastral database. With the overall development of the second national land survey, urban cadastre, rural cadastre investigation, and the continuous promotion of rural collective ownership right have been carried out at the county level as the smallest administrative unit in the country. Urban cadastral database, rural cadastral database, rural collective land confirmation registration database, land registration database, and so on. In recent years, the country has carried out a comprehensive survey on cultivated land reserve resources, and also built up a database of cultivated land reserve resources. However, although China has basically completed the construction of Cadastral database, but all kinds of databases have been completed. It is at the county level for separate storage and classification management, the data type is single, the current situation is low, the update is slow, the data sharing can not be realized between different types of databases. It is difficult to meet the comprehensive and efficient use demand of the land use data at the provincial level. Therefore, the three level administrative granularity of the province, city and county is set up. Management database is of great significance for the unified management and efficient utilization of data by land and resources management departments. However, there are different database standards in different types of databases, spatial datum and data formats are not uniform, especially the scale accuracy. For example, the scale of the land use database For 1:1 million, the scale of the urban cadastre database is 1:500, the scale of the rural collective land ownership right database is the difference of the 1:2000. data precision, which seriously affects the unified call and display of the cadastral data, which is not conducive to the macro statistics and analysis of the data. Therefore, how to solve the multi-scale cadastral database integration problem is the provincial cadastre In this paper, based on the provincial level, and taking the database construction in Jilin as the reference object, this paper discusses the causes of the multiscale cadastral data, the features and the representation of multi-scale cadastral data. The integration process of multi-scale cadastral database is formulated, and the multi-scale cadastral data are discussed. The integration scheme has solved the key technology of multi-scale cadastral data integration. Taking Jilin cadastre data as reference, the integrated results are displayed and analyzed from the angle of combination of theory and practice. In addition, the framework of the comprehensive database of provincial cadastre management is built on the basis of data integration. The following conclusions are drawn as follows: 1, the main factors affecting the multi-scale characterization of cadastral data are mainly from the uncertainty of cadastral data acquisition, the difference in the requirement of the database, the diversity of the data sources, the data time, the multi-scale.2 of the space, and the data storage of cadastral data. In addition, the multiscale of the administrative scope and the multiscale of data hinders the exchange and sharing of data between administrative granularity at all levels. It is the key technical problem of establishing the comprehensive database of provincial cadastre management,.3, and the coordinate projection of the integration process. The unified method of exchange and data format, based on the cadastral data of Jilin Province, validates the feasibility of using the projection parameter conversion method to unify the coordinate system and the conversion of data format based on various data format conversion methods based on FME technology. It provides a number of data integration for multi-scale cadastral data. According to the characteristics of basic.4, according to the characteristics of various basic data applications, the method of constructing multi-scale derived spatial attribute map layer is proposed to solve the problem of multi-scale cadastral data integration. The change data is recorded and the data is collected and collected. In addition, it can be traced to the change elements according to the attribute information of the changing elements of the derived layer, and it is of great significance to the analysis of the data.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：D922.32

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