Abstract
Spatial statistics and geostatistics have developed to describe and analyze the variation in both natural and man-made phenomena on, above or below the land surface. Spatial statistics includes any of the formal techniques that study entities that have a spatial index (Cressie 1993). Geostatistics is embraced by this general umbrella term, but originally it was more specifically concerned with processes that vary continuously, i.e. have a continuous spatial index. The term geostatistics applies essentially to a specific set of models and techniques developed largely by Matheron (1963) in the 1960s to evaluate recoverable reserves for the mining industry. These ideas had arisen previously in other fields; they have a long history stretching back to Mercer and Hall (1911), Youden and Mehlich (1937), Kolmogorov (1941), Gandin (1965), Matérn (1960) and Krige (1966). Geostatistics has since been applied in many different fields, such as agriculture, fisheries, hydrology, geology, meteorology, petroleum, remote sensing, soil science and so on. In most of these fields the data are fragmentary and often sparse, therefore there is a need to predict from them as precisely as possible at places where they have not been measured. This chapter covers two of the principle techniques of geostatistics that solve this need for prediction; the variogram and kriging.
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Oliver, M.A. (2010). The Variogram and Kriging. In: Fischer, M., Getis, A. (eds) Handbook of Applied Spatial Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03647-7_17
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