Training on Geostatistical Modeling for Spatial Data Analysis

Module 1: Introduction to Geostatistics

• Basic concepts of spatial data
• Spatial autocorrelation and variograms
• Exploratory data analysis for spatial data

Module 2: Variogram Modeling

• Variogram estimation methods
• Variogram model fitting
• Anisotropy in spatial data

Module 3: Ordinary Kriging

• Theory of ordinary kriging
• Kriging variance
• Block kriging

Module 4: Universal Kriging

• Universal kriging model
• Trend estimation
• Residual kriging

Module 5: Indicator Kriging

• Indicator kriging for categorical data
• Probability of exceedance maps

Module 6: Cokriging

• Cokriging for multiple variables
• Cross-variogram modeling

Module 7: Sequential Gaussian Simulation

• Conditional simulation techniques
• Monte Carlo simulation
• Uncertainty assessment

Module 8: Spatial Regression

• Spatial lag models
• Spatial error models
• Mixed models for spatial data

Module 9: Geostatistical Applications in Environmental Science

• Soil contamination mapping
• Groundwater modeling
• Air pollution assessment

Module 10: Geostatistical Applications in Other Fields

• Disease mapping
• Natural resource management
• Remote sensing data analysis