The geologists collect various spatially distributed point data sets for mineral exploration and environmental characterization of sites. The classical statistical data analysis provides valuable basic information which is used in various decision-making processes. Spatial data analysis may include generating two-dimensional contours of the values such as Pb% or, As ppm or, Fe % etc. which provides a general spatial variability. Most of the time contouring involves ‘interpolation’. The accuracy of interpolation in two and three dimensions is important in predicting the value at an un-sampled location. This is where geostatistical techniques are important. Currently ordinary kriging, a geostatistical interpolation technique is inbuilt in many software tools for interpolation purposes.
In this short course, discussions will start with basic statistical analyses of a given set of data used as an example. The spatial data analysis topic will include simple non-geostatistical techniques such as inverse distance power and linear geostatistical interpolation technique, ordinary kriging.
Using a freely available software tool and a common data-set, participants will gain knowledge of spatial data analyses using hands-on exercises. Participants are required to use their own laptop computers or, share computers with other participants.
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