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ArcGIS Geostatistical Analyst

This course provides the foundation for understanding the operation of the Geostatistical Analyst extension, which provides a wide variety of important resources for modeling surfaces using deterministic and geostatistical methods. It is presented a summary of the main statistical concepts behind the tools of the extension, and the steps comprising the Geostatistical workflow are described. You will learn the different interpolation methods and learn how to decide which is the best suited to the objectives to be achieved. Finally, you will take a comprehensive set of exercises where the concepts learned will be applied.

Topics

  • Fundamentals of descriptive and spatial statistics
  • Geostatistics and Geostatistical Model
  • Representation of Spatial Data
  • Graphs of Exploratory Analysis of Spatial Data
  • Interpolated surfaces creation, classification methods tree
  • Surface creation using deterministic methods
  • Surface creation using geostatistical methods, types of kriging
  • Performing validation and cross-validation
  • Model comparisons
  • Calculation of uncertainty and generation of probability surfaces

Prerequisites

This course focuses on users with a Basic and Intermediate level in the use of Geographic Information Systems, specifically with software ArcGIS Desktop 8.x, 9.x or 10.x, and must have completed the course ArcGIS Desktop I or similar. You must also manage, at least generally, the basic concepts of statistics, spatial analysis and geospatial approach projects.

Furthermore, Windows environment skills for basic file management and browsing is required.

Those who complete the course will be able to:

  • Knowing what geostatistics is and its relationship with descriptive and spatial statistics
  • Remember basic statistical concepts, such as frequency tables, measures of central tendency, measures of dispersion and measures of form and how to apply these concepts in exploratory data analysis
  • Understand the interface and the main features of the Geostatistical Analyst extension for ArcGIS for Desktop
  • Differentiate between statistical and deterministic interpolation methods and identify which one is the most appropriate according to the characteristics of the data
  • Explore the data to understand the behavior of these and decide on the most appropriate model to apply and if required to transform the data before creating interpolated surfaces
  • Evaluate the results of prediction surfaces and find out the associated uncertainty
  • Compare models to decide which is the most accurate and appropriate to the objectives of the investigation

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