Uncertainty modeling for spatial data fusion and mining

Author(s):  
Boris Kovalerchuk ◽  
Leonid Perlovsky
2012 ◽  
pp. 105-111 ◽  
Author(s):  
Patrik Skogster

Geographic information is created by manipulating geographic (or spatial) data (generally known by the abbreviation geodata) in a computerized system. Geo-spatial information and geomatics are issues of modern business and research. It is essential to provide their different definitions and roles in order to get an overall picture of the issue. This article discusses about the problematic of definitions, but also the technologies and challenges within spatial data fusion.


2011 ◽  
Vol 460-461 ◽  
pp. 404-408
Author(s):  
Yue Shun He ◽  
Jun Zhang ◽  
Jie He

This paper mainly analyzed the principle of multi-source spatial data fusion, and expounded the multi-source spatial data fusion of the distributed model structure. The paper considers a distributed multi-sensor information fusion system factors, A performance evaluation model was established which was suitable for distributed multi-sensor information fusion system, It can estimate the system's precision, track quality, filtering quality, and the relevant between Navigation Paths and so on. Meanwhile, we had a lot of experiments by the datum which generated by the simulation test environment, experiments show that this evaluation model is valid.


2012 ◽  
Vol 263-266 ◽  
pp. 3274-3278
Author(s):  
Hui Ming Yu ◽  
Jian Zhong Guo ◽  
Yi Cheng ◽  
Qian Lou

Spatial data fusion is an important method of spatial data acquisition. The aim of multisource spatial data integration and fusion is to improve the information precision and information's utilization efficiency. Vector and raster are the two main spatial data structures. This article discusses vector data fusion from of data model fusion, semantic information fusion and coordinates unification, reviews the main methods of raster data fusion and discusses the key technologies of vector and raster data fusion, and proposes the future developments of spatial data fusion technique.


2013 ◽  
Vol 21 (4) ◽  
pp. 1-12 ◽  
Author(s):  
R. Ďuračiová

Abstract This paper deals with uncertainty modeling in spatial object-relational databases by the use of Structured Query Language (SQL). The fundamental principles of uncertainty modeling by fuzzy sets are applied in the area of geographic information systems (GIS) and spatial databases. A spatial database system includes types of spatial data and implements the spatial extension of SQL. The implementation of the principles of fuzzy logic to spatial databases brings an opportunity for the efficient processing of uncertain data, which is important, especially when using various data sources (e.g., multi-criteria decision making (MCDM) on the basis of heterogeneous spatial data resources). The modeling and data processing of uncertainties are presented in relation to the applicable International Organization for Standardization (ISO) standards (standards of the series 19100 Geographic information) and the relevant specifications of the Open Geospatial Consortium (OGC). The fuzzy spatial query approach is applied and tested on a case study with a fundamental database for GIS in Slovakia.


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