Spatiotemporal Interpolation Methods in GIS

Exploring large data sets with the aim of extractinguseful information for decision making can be challenging. If the datawere collected at different locations and times one important questionis how to obtain reliable estimates for missing data in space or time.For example measurements such as ozone concentrations are usuallycollected only by a limited number of monitoring stations and atdifferent time instances. In order to estimate the values atunmeasured locations or time instances interpolation in continuous space andtime is needed. New and old interpolation methods for exploringspatiotemporal data are discussed in this book. The selected methods areuseful for Geographic Information Systems (GIS). This book alsoincludes comparisons of selected methods for several GIS casestudies as well as some visualization and query examples.