Operational overviews of cadastral information system

Pao Yue-kong Library Electronic Theses Database

Operational overviews of cadastral information system

 

Author: Chu, Hing-bong
Title: Operational overviews of cadastral information system
Degree: M.Sc.
Year: 2000
Subject: Cadastres -- Data processing
Information storage and retrieval systems
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Dept. of Land Surveying and Geo-Informatics
Pages: vi, 156 leaves : ill. ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1559483
URI: http://theses.lib.polyu.edu.hk/handle/200/4450
Abstract: The dissertation reviewed the operational performance of Cadastral Information System (CIS) of Land Information Center in Hong Kong. Boundary uncertainty had long been the problem in both conventional land boundary records and CIS. The most problematic area was the old schedule lots in the New Territories. Conventional boundary correlation exercises did not resolve the problem. A recently proposed New Territories wide systematic survey was deemed to be the only clear-cut solution. Current CIS model was not able to handle spatially or temporally overlapping objects. It did not preserve historical data either. Neither polygon nor line model performed effectively in representing such phenomena. Region model or lookup table representation were viable alternatives to ease the problem. Redundancy and inconsistency incurred in CIS database. Some redundancy devices such as polygon lookup tables were deliberately introduced to trade space for processing speed. Others were either the result of schema defect or data merging discrepancy between adjoining districts. Database schema should be normalized. Thematically defined feature keys was not unique item in most CIS layers. Spatially defined Geo-referencing identifier was an alternative to pursue the object uniqueness. CIS was fully implemented since 1996. The total number of land parcels and proposal records stored in the CIS database amounted to around one million units. The costs on running the system were high. Rationalization of the input resources was crucial. Software, hardware and procedures in various areas could be economized. Various operational issues were identified. Improvement measures including program routines were suggested to either improve data quality or improve operational productivity.

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