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Jeo-İstatistik'te Kullanılan Temel Kriging Yöntemleri

Çevresel, hidrolojik, tarımsal ve benzer çalışmalara ait ölçümler dünya üzerinde yapılmış noktasal gözlemlere dayanır. Yağış ve sıcaklık değerleri meteorolojik istasyonlarda, toprak karakteristiği toprak örneklerinden ve göl kirliliği gölden alınan örneklerden ölçülür. Bunlar noktasal olarak yapılan mekânsal ölçümlere örnektir. Belli noktalardan örnekler alarak veya belirgin yerlerden ölçüm yaparak sınırlı sayıda ölçüm yapabiliriz. Ancak ilgilendiğimiz değişkenin dünyanın her noktasında ya da belli büyüklükteki bir alan üzerinde ölçüm yapmak mantıksal olarak mümkün değildir. Bunun yerine bilim insanları bir değişkenin tüm alanda mekânsal olarak nasıl dağıldığını haritalamak için enterpolasyon yöntemini kullanmayı tercih ederler. Birbirine yakın olan gözlem noktaları benzer değerlere sahiptirler, ancak birbirinden uzak olan noktalar daha farklı değerler taşırlar. Bu bilgi tahmin prosedüründe (enterpolasyon) kullanılır. Burada bahsi geçen kriging yöntemleri de enterpolasyon yöntemlerindendir. Kriging en uygun tahmin değerleri verir: bir değişkene ait herhangi bir yerde en olası değeri üretir. Bu derleme çalışmasında jeo-istatistikte en çok kullanılan kriging metotlarından Sıradan kriging, Regresyon kriging ve Evrensel kriging yöntemlerine ait yöntemler anlatılmıştır.

Anahtar Kelimeler:

Jeoistatistik, Enterpolasyon, Sıradan kriging, Regresyon kriging, Evrensel kriging

Basic Kriging Methods in Geostatistics

Measurements of environmental, hydrological, agricultural and similar studies are based on point observations over the Earth. Precipitation and temperature values are measured from meteorological stations, soil characteristics are measured from soil samples, and pollution of a lake is measured by taking samples from lake. These are some examples from spatial point measurements. These variables can be measured by taking samples from a limited number of locations or from certain locations. However, it is logically impossible to measure a variable at all parts of globe or on a field of certain size. Instead of this it is possible to make some interpolation to map spatial distributions of that variable. Observation locations which are close to each other tend to have similar values, however the ones located farther apart from each other differ more. So this knowledge is used in prediction procedure (interpolation). Kriging which will be described here, is an interpolation method. Kriging makes optimal predictions: it provides the most likely value at any location of a variable. Methodologies of most commonly used kriging methods in geostatistics; Ordinary kriging, Regression kriging and Universal kriging have been described in this review work.

Keywords:

Geostatistics, Interpolation, Ordinary kriging, Regression kriging, Universal kriging,

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