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Course title 
Course code 
Syllabus 
Adjustment Computation for GeoinformaticsI 
CE770a 
Adjustment computations: Introduction, observation/ measurements: True value, most probable value (MPV), true error, residual, discrepancy, types and sources of error, Gaussian law of accidental errors, precision and accuracy, measures of precision from Gaussian law, expectation operator, variance, covariances, correlation, weights and cofactors, various error measures on 1D, 2D, and 3D standards, propagation of errors, variance, covariance and cofactors, preanalysis, introduction to statistical concepts, probability distributions, hypothesis testing Geoinformatics methodology: Mathematical model, definition, elements and types of models: stochastic and function, linear, nonlinear, overdetermined, underdetermined, unique, explicit, implicit, observation, condition, combined, Adjustment: purpose and types, Least squares adjustment: principle and techniques, assumptions, ordinary, weighted, generalized is, geometrical interpretation Observation equations: Model and solution strategy, adjustment of linear and nonlinear forms, variancecovariance propagation of adjusted data in observations equations method Condition equation: Model and solution strategy, adjustment of linear and nonlinear forms, variancecovariance propagation of adjusted data in condition equations method Combined method: Model and solution strategy, variancecovariance propagation of adjusted data in combined equations method observation and condition equations as simplification of combined method Postanalysis of adjusted data: Absolute and relative error ellipse and error ellipsoid, significance and use in designing projects, outlier/blunder detection, redundancy, redundancy number, reliability and sensitivity analysis. Applications of adjustment computations: Traversing, Tacheometry, EDM, photogrammetry, GNSS, network adjustment. Introduction to Geostatistics: Geostatistical tools: Semivariance, variogram, various models Kriging.
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