Spatio-temporal data are inherently unstructured and uncertain due to their heterogeneous nature, and are non-uniformly distributed in space resulting in extremely dense and sparse regions. Visually analysing geospatial data sets have proven to be a challenge. Our research tackles and solves the inherent problems ranging from developing methods to deal with the non-uniformity of geographic data, visual analytics to solve geographic data distortion and dealing with various uncertainties in these data. Particular applications of ongoing research are animal movement analysis, quality assessment of volunteered geographic information, and reducing overplotting issues.

Publications