Given a data structure for regular raster-based space-time field data, where attribute is continuous or categorical, a prerequisite for doing powerfull spatio-temporal analysis is to have access to the most elementary operations on these fields. The first is selection: functions and are needed to subset a full ST imagery by (i) selecting a spatial region, (ii) selecting a time period, (iii) subsampling at a lower spatial resolution, or (iv) subsampling at a lower time-resolution. The second function is filtering; one would like to be able to write filters in the spatio-temporal domain that allow the usual analytical operations of smoothing and differencing. Especially differencing in space-time is a promising new tool. The resulting space-time gradient, a 3D vector with a direction in ST and a length, is a promising tool for finding temporal changes in spatial gradients, or for finding space time interactions such as region growth. To make these instruments useful in integrated, unconditional spatio-temporal data analysis, the research requires the choice of useful, intuitive semantics as well as efficient implementation.

Supervisors: Prof.dr. Edzer Pebesma, dr. Lubia Vinhas, Karine Reis Ferreira

Mobility measure: the ifgi MSc student should spend 2-3 months at INPE to get familiar with the space-time imagery data base structures and currently existing functions currently available in TerraLIB.