Geovisualization and Exploratory Data Analysis

Geo-visualization provides an intuitive means to identify spatial patterns that may be hidden in data presented in tabular forms and to support exploratory data analysis (EDA). The ability to perform EDA is critical for developing appropriate research questions in the big data era. My research interest in geovisualization and exploratory data analysis focuses on the combine use of self organizing map and the spatial metaphors in geography (i.e., nearness and hierarchy) to help identify patterns in the input data.

Feng C-C, Wang Y-C, and Chen C-Y, 2014, Combining Geo-SOM and Hierarchical Clustering to Explore Geospatial Data, Transactions in GIS, 18(1), 125-146

Wang Y-C and Feng C-C, 2011, Patterns and Trends in Land Use Land Cover Change Research Explored Using Self-Organizing Map. International Journal of Remote Sensing, 32(13), 3765-3790