This articles provides a review of recent advances in modeling spatio-temporal data. In an attempt to unify the modeling strategies we describe the primary spatio-temporal data types. We then discuss general models for point reference data only. Spatial-temporal modeling has largely been developed through applications in environmental, geostatistics, hydrology and meteorology. We review current methods for many such application areas.
Keywords: Bayesian Inference; Gibbs Sampler; Kalman Filter; Kriging; Markov Chain Monte Carlo; Space-Time model.