Thoughts on “Spatial Data Mining Approaches for GIS – A Brief Review”

This article gives an outline of data formats, data representation, data sources, data mining approaches, related tools, and issue and challenges. The author concluded that “spatial data mining is the analysis of geometric of statistical characteristics and relationships of spatial data”, and it can be used in may fields with different applications.

In terms of spatial data mining tasks, I think other than spatial classification, spatial association rule, spatial clustering, and trend detection, terms like local statistics, spatial autocorrelation, point pattern analysis, etc. should be mentioned or included.

The author also mentioned that the issue and challenges of spatial data mining is data integration and mining huge volume of data. But the author did not explain why this two are challenges. This would be the first things that I felt confused after reading this article.

Then the author provided an architecture of the solution to this two issues and challenges. With no further explanation in detail, I find it really hard to understand why this architecture can solve the above challenges.

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