Kriging Interpolation MATLAB Code with Implementation Guide

Kriging interpolation is a spatial interpolation method that uses known point values to estimate values at unknown locations. This technique finds applications across multiple domains including meteorology, geology, and environmental science. This MATLAB implementation provides a robust learning framework for Kriging interpolation, featuring comprehensive documentation, theoretical explanations, and extensively commented code. The implementation includes core algorithms such as variogram modeling (exponential, spherical, and Gaussian models), covariance matrix computation, and the Kriging system solution using matrix operations. Key functions handle data preprocessing, model parameter optimization, and spatial prediction with uncertainty quantification. Through this well-documented codebase, users can gain deep understanding of Kriging methodology and apply it effectively to research projects involving spatial data analysis, resource estimation, and environmental modeling. The code demonstrates practical implementation details including neighbor selection strategies, drift handling for universal Kriging, and cross-validation for model verification.