Knowledge Discovery in the Environmental Sciences: Visual and Automatic Data Mining for Radon Problems in Groundwater

Efficiently exploring a large dataset with the aim of forming a hypothesis is one of the main challenges in environmental research. The exploration of georeferenced environmental data is usually pe ...

[1]  Åke Sivertun,et al.  Spatial correlation between radon (222Rn) in groundwater and bedrock uranium (238U): GIS and geostatistical analyses , 2002 .

[2]  Mark Gahegan,et al.  Introducing geovista studio: an integrated suite of visualization and computational methods for expl , 2002 .

[3]  Robert M. Edsall The parallel coordinate plot in action: design and use for geographic visualization , 2003, Comput. Stat. Data Anal..

[4]  Menno-Jan Kraak,et al.  Geovisualization to support the exploration of large health and demographic survey data , 2004, International journal of health geographics.

[5]  Kirlna Skeppström,et al.  Radon in Groundwater- Influencing Factors and Prediction Methodology for a Swedish Environment , 2005 .

[6]  Dianne Cook,et al.  Visual Data Mining In Atmospheric Science Data , 2000, Data Mining and Knowledge Discovery.

[7]  Paula Ahonen-Rainio Visualization of geospatial metadata for selecting geographic datasets , 2005 .

[8]  Juha Vesanto,et al.  SOM-based data visualization methods , 1999, Intell. Data Anal..

[9]  Jason Dykes,et al.  Seeking structure in records of spatio-temporal behaviour: visualization issues, efforts and applications , 2003, Comput. Stat. Data Anal..

[10]  A. MacEachren,et al.  Research Challenges in Geovisualization , 2001, KN - Journal of Cartography and Geographic Information.

[11]  Mark Gahegan,et al.  GeoVISTA studio: a codeless visual programming environment for geoscientific data analysis and visualization , 2002 .

[12]  Bin Jiang,et al.  Selection of Streets from a Network Using Self‐Organizing Maps , 2004, Trans. GIS.

[13]  Bo Olofsson,et al.  A prediction method for radon in groundwater using GIS and multivariate statistics. , 2006, The Science of the total environment.

[14]  Kent B. Barnes,et al.  Indoor radon hazard: a geographical assessment and case study , 1994 .

[15]  R. Doll,et al.  Radon in homes and risk of lung cancer: collaborative analysis of individual data from 13 European case-control studies , 2004, BMJ : British Medical Journal.

[16]  Daniel A. Keim,et al.  Pixel based visual data mining of geo-spatial data , 2004, Comput. Graph..

[17]  Gennady L. Andrienko,et al.  Visual Mining of Spatial Time Series Data , 2004, PKDD.

[18]  Jukka M. Krisp,et al.  Exploring Geographical Data with Spatio-Visual Data Mining , 2006 .

[19]  Daniel A. Keim,et al.  Visual Data Mining of Large Spatial Data Sets , 2003, DNIS.

[20]  Menno-Jan Kraak,et al.  Alternative Visualization of Large Geospatial Datasets , 2004 .

[21]  Gennady L. Andrienko,et al.  Exploratory spatio-temporal visualization: an analytical review , 2003, J. Vis. Lang. Comput..