Product Overview

Statistical Tools and Models for Data Exploration, Modeling, and Probabilistic Mapping

ArcGIS Geostatistical Analyst is a statistical extension to ArcGIS Desktop (ArcInfo, ArcEditor, and ArcView) that provides a dynamic environment with a wide variety of tools for spatial data exploration, identification of data anomalies, optimum prediction, evaluation of prediction uncertainty, and surface creation.

ArcGIS Geostatistical Analyst consists of exploratory spatial data analysis and statistical interpolation. Exploratory spatial data analysis is composed of a series of interactive graphs describing such data features as distribution, variability, and large- and small-scale variations. Statistical interpolation consists of a set of models and tools that use information from data exploration. It is used to study data correlation, predict the most likely values at the unsampled locations, and quantify prediction uncertainty for efficient decision making.

A distinctive feature of this statistical package is that it is fully integrated into the ArcGIS environment, so there is no need to use other software for preprocessing, statistical analysis, contouring, postprocessing, and printing.

Since many users of Geostatistical Analyst are beginners in statistical data analysis, friendly interactive graphical tools with reliable default model parameters are provided.

Why Use ArcGIS Geostatistical Analyst?

• The eye can infer patterns that do not exist, and it can miss important patterns. Geostatistical Analyst provides objective, data driven methods for quantifying trends and detecting patterns in spatial data.
• If data is not precise or the model is not exact, uncertainty will affect the output maps and the conclusions made from them. Geostatistical Analyst provides a probabilistic framework for quantifying uncertainties in surface creation.
• Multivariate statistical methods use correlations in attribute values to infer associations between different variables. They are useful for combining data to produce more precise predictions.
• Geostatistical analysis provides a powerful way of predicting unknown parts of some spatial phenomenon. Hence, it is extremely useful for sampling plan design and optimization.

Who Uses ArcGIS Geostatistical Analyst?

The applications of geostatistics are limitless. Any collection of geographical data (e.g., coordinates and values) can be explored using Geostatistical Analyst. Several typical areas where geostatistics is successfully used are presented below.

Meteorologists and statisticians use geostatistics for atmospheric data analysis. This demo includes an example of temperature map creation. View demo: Windows Media [03:22]

Geostatistics is widely used by the mining industry at all stages from initial feasibility studies to production control.

The petroleum industry successfully uses geostatistics to analyze spatial data including integration of seismic data with wells data and studying correlations between physical properties and seismic attributes.

The application of geostatistics to environmental problems provides efficient and consistent models of the variability of air, soil, and groundwater pollutants. Demos, case studies, and educational and research papers provide examples of the geostatistical analysis of the environment. Geostatistics has become a standard approach for estimating fish abundance.

Geostatistics is widely used in mapping soil properties for precision agriculture. An increasing number of farmers (or their consultants) are using geostatistics to increase yield, improve profit, and soften the impact on the environment. Working on Nonstationarity Problems in Geostatistics Using Detrending and Transformation Techniques: An Agricultural Case Study.

Geostatistical Analyst is installed at universities worldwide, helping researchers from other disciplines learn about geostatistical practice from well-established areas such as those mentioned above.