ArcGIS Geostatistical Analyst

Strictly by pre-registration only

What is this course about?

Attendees will learn to create a probabilistic framework for quantifying uncertainties in data which is incomplete or subject to error by creating surfaces from sample data using various interpolation methods and deriving models to improve decision making by enhancing surfaces.

This course is for: ArcGIS users who want to know how to create surfaces that can be used to visualise, analyse and understand spatial phenomena.

Download course outline

Course details


480.00 SGD




1 day




Visualisation, Editing and Analysis Course

CPD points

Safety measures for training courses

While courses in our training facility have resumed, we want to assure you that the wellbeing of our trainees and staff remains Esri Singapore’s highest priority.

As the COVID-19 situation continues to develop, strict safety measures and guidelines as recommended by the Ministry of Health are being adhered to for all training conducted.

All computer equipment and desks are disinfected before class commences and during the lunch break, while seats are placed and marked at least 1-metre apart, in accordance with official Safe Distance Measures.

Masks are mandatory throughout training, and alcohol hand sanitisers and anti-bacterial wet wipes will be available.

Your temperature will be taken before commencement. For your safety, you will be asked to return home and see a doc if your temperature exceeds 37.5deg.

An isolation room has been prepared for trainees to rest in if they are feeling unwell and awaiting transportation.

Are there any prerequisites?

Completion of ArcGIS 3: Performing Analysis and ArcGIS Spatial Analyst is required.

What skills will I learn?

After completing this course, you will be able to:

  • Create surface modeling using deterministic and geostatistical methods.
  • Generate interpolation models and assess their quality before using them in any further analysis.
  • Know how to use models to generate predictions for unsampled locations, as well as measures of uncertainty for those predictions.

What can I expect?

  • Course topics

    Understanding Geostatistics

    • Interpolation and methods
    • The geostatistical workflow

    Examining Data

    • Data mapping
    • Quantitative data exploration
    • Data distribution
    • Looking for global/local outliers and trends
    • Spatial autocorrelation
    • Voronoi map

    Creating Surfaces

    • Deterministic methods
    • Inverse distance weighted
    • Global/Local polynomial interpolation
    • Radial basis functions
    • Interpolation with barriers

    Geostatistical Methods

    • Components of geostatistical models
    • Empirical semivariogram and Binning
    • Anisotropy
    • Fitting a model to the empirical data
    • Model parameters
    • Handling trends
    • Different kriging models

    Evaluating Interpolation Results

    • Cross-validation
    • Result Plots
    • Prediction error statistics
    • Comparing models

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