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CADASTRAL POSITIONING ACCURACY IMPROVEMENT (PAI): A CASE STUDY OF PRE-REQUISITE DATA QUALITY ASSURANCE

机译:地籍定位准确性改进(PAI):对先决条件数据质量保证的案例研究

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摘要

Nowadays, there is an increasing need for comprehensive spatial data management especially digital cadastral database (DCDB). Previously, the cadastral database is in hard copy map, then converted into digital format and subsequently updated. Theoretically, these legacy datasets have relatively low positional accuracy caused by limitation of traditional measurement, adjustment technique and technology changes over time. With the growth of spatial based technology especially Geographical Information System (GIS) and Global Navigation Satellite System (GNSS) the Positional Accuracy Improvement (PAI) to the legacy cadastral database is inevitable. PAI is the refining process of the geometry feature in a geospatial dataset through integration between legacy and higher accuracy dataset to improve its actual position. However, by merely integrating both datasets will lead to a distortion of the relative geometry. Thus, an organized method is required to minimize inherent errors in fitting to the new accurate dataset. The focus of this study is to design a comprehensive data preparation for legacy cadastral datasets improvement. The elements of datum traceability, cadastral error propagation and weightage setting in adjustment will be focused to achieve the targeted objective. The proposed result can be applied as a foundation for PAI approach in cadastral database modernization.
机译:如今,尤其是数字地籍数据库(DCDB)尤其是综合空间数据管理的需求。以前,Cadastral数据库处于硬拷贝映射,然后转换为数字格式并随后更新。从理论上讲,这些传统数据集具有相对较低的位置精度,由于传统测量,调整技术和技术随时间的改变而导致的位置。随着空间基础技术的增长,尤其是地理信息系统(GIS)和全球导航卫星系统(GNSS)的位置准确性改进(PAI)对传统的地籍数据库是不可避免的。 PAI是通过在传统和更高的精度数据集之间集成来改善其实际位置的地理空间数据集中的炼油过程。但是,通过仅集成两个数据集将导致相对几何的失真。因此,需要一个有组织的方法来最小化拟合到新的准确数据集的固有错误。本研究的重点是为遗产地籍数据集改进设计全面的数据准备。调整中的基准可追溯性,地籍误差传播和重量设定的元素将集中于实现目标目标。拟议的结果可作为扎地区数据库现代化中PAI方法的基础。

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