The spatial data quality analysis in the environmental modelling.

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.

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