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Research on spatial data mining based on uncertainty in Government GIS

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3 Author(s)
Bin Li ; Center of Gov. GIS Res., Chinese Acad. of Surveying & Mapping, Beijing, China ; Lihong Shi ; Jiping Liu

Uncertainty is the intrinsic property of spatial data and one of important factors affecting the course of spatial data mining. There are diversiform forms for the essentiality and aspect of uncertainty in the spatial objects of geographic information system. Essentiality of uncertainty may consist of the components of randomicity, fuzzy, chaos, etc. And the latter, i.e. aspect of uncertainty, may include error uncertainty, location uncertainty, attribute uncertainty, topology uncertainty, inconsonance uncertainty, immaturity uncertainty and so on. Spatial data mining, which is based on uncertainty, is the course of discovering knowledge in the spatial data including the attribute of uncertainty. Spatial data is the necessary object operated by spatial data mining and its uncertainty can exist in the whole process of data input, data processing, data output, etc. Uncertainty can affect directly or indirectly the quality of spatial data mining. Specially, uncertainty of spatial data can affect directly or indirectly the veracity and reliability of ultimate decision-makings and may lead to produce false results and even reverse conclusions. Spatial data mining based on uncertainty has taken synchronously into account the two associated factors of uncertainty of data and spatial data mining. Therefore, due to considering the uncertainty, it can enhance the reliability of discovering knowledge and improve the veracity and reliability of spatial as well as raise the efficiency and practicability for the decision-makings made by operation departments. In this paper, aiming at massive spatial data belonging to the Government Geographic Information System, some work has been done under the conditions of summarizing existing relevant theory and technology of spatial data mining and uncertainty and carry out necessary practice.

Published in:

Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on  (Volume:6 )

Date of Conference:

10-12 Aug. 2010