To analyse spatially allows the statistician to incorporate the spatial correlation present in many datasets, without which model interpretation may be incorrect. There is a wealth of knowledge on spatial statistics within South Africa, the research field of spatial statistics is still relatively young and much expert guidance is required to build the field in terms of research as well as training. Spatial statistics has very important applications in the South African context. Most notably the need has been expressed by StatsSA to have trained spatial statisticians in their analyses and data collection. In the past, spatial statistics has been dealt with on at an introductory level, whereas more recently modelling of spatial data has developed as a component of spatial statistics. Such modelling includes new theory and modelling approaches for the spatial domain and for which expertise is still required. Surprisingly, this goes hand in hand with focused applications, such as remote sensing, spatial sampling and spatial medical modelling. Spatial statistics has started worldwide with the seminal work of Danie Krige, who worked in mining studies at Wits. Its importance to the South African research community is much wider and goes these days into poverty alleviation, meteorology and climate, the environment, ecology and agriculture.