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Title: The spatial data quality analysis in the environmental modelling
Author: Li, Yang
ISNI:       0000 0001 3609 5388
Awarding Body: University of East London
Current Institution: University of East London
Date of Award: 2001
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The spatial data quality analysis is essential in environmental modelling for efficiently addressing the environmental change. As the complexity of data sets and the modelling capability of computer systems increase, the need to address the quality of both data and models is increasingly important. Integration with environmental modelling, the spatial data quality analysis and the geocomputation paradigm have been three important areas of GIS research. In this research they are brought together in the context of coastal oil spill modelling. The research covers the issues of measurement, modelling and management of spatial data quality. Coupling GIS and environmental modelling, the systematic solution is developed for coastal oil spill modelling which is representative of complex environmental models. The procedures of geospatial data quality analysis were implemented not only with existing GIS funLionality but also with various Geocomputation techniques. Spatial data quality analyses of inputs and model performances, which include sensitivity analyses, error propagation analyses and fitness-for-use analyses, were carried out for the coastal oil spill modelling. The results show that in coastal oil spill modelling, a better understanding and improvement of spatial data quality can be achieved through such analyses. The examples illustrate both the diversity of techniques and tools required when investigating spatial data quality issues in environmental modelling. The evidence of feasibility and practicality are also provided for these flexible analysis approaches. An overall methodology is developed at each stage of a project; with particular emphasis at inception to ensure adequate data quality on which to construct the models. Furthermore, the coupling strategy of GIS and environmental modelling is revised to include a geo-data quality analysis (GQA) engine. With growing availability of proprietary and public domain software suitable for spatial data quality analysis, GQA engines will be formed with the evolution of such software into tightly-coupled collection of tools external to GIS. The GQA engine would itself be tightly-coupled with GIS and environmental models to form a modelling framework.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available