Advances in Geostatistical Information Analysis and Mapping

Dear Colleagues,

In recent decades, there has been a very rapid increase in the application of geostatistical analyses in various fields of knowledge, often quite distant from earth sciences, geography, or cartography, such as history, medicine, microbiology, or forensic science. The popularity of these research techniques is primarily related to access to large spatial and environmental databases that can be correlated with a range of variables that have a spatial distribution. The data used can take a variety of forms, which can also be in the form of image data such as old maps, aerial photographs, and satellite images. In addition to being able to detect spatial relationships, processes can also be studied, taking into account the fourth dimension, which is time.

Geostatistical methods offer the possibility to study phenomena that occur continuously and discretely. These techniques have the ability to take into account the characteristics of spatially distributed variables, regardless of whether their values were obtained in a regular or irregular pattern. Spatial dependence and correlations can be analysed using semivariograms. The latter quantify spatial dependence by determining the variability between samples and are used to quantitatively characterise spatial patterns of development or population distribution over space and time.

However, the field measurement and spatial resolution of the data obtained by mapping the analysed phenomenon is still an important challenge. An additional challenge is how to visualise the obtained research results. In this respect, issues such as presentation methods, degree of generalisation, and form of presentation can be distinguished. It is also important to discuss the interpolation of the analysed variables, as well as to characterise the error and variability of the predicted area. Therefore, in the proposed volume, special attention is given to the problems of mapping and the representativeness of spatial data.

The scope of discussion in this Special Issue will include, but is not limited to, the following:

• Geographical survey and mapping;
• Spatial distribution;
• Spatial analysis;
• Geostatistical methods;
• Autocorrelation;
• Regression models;
• Statistical maps;
• Isopleth maps;
• Hot spot analysis.

Dr. Grzegorz Janicki
Prof. Dr. Yosoon Choi
Guest Editors

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