Course title

Course code


Adjustment Computation for Geoinformatics-I


Adjustment computationsIntroduction, 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, pre-analysis, introduction to statistical concepts, probability distributions, hypothesis testing

Geoinformatics methodology: Mathematical model, definition, elements and types of models: stochastic and function, linear, non-linear, over-determined, under-determined, 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 non-linear forms, variance-covariance propagation of adjusted data in observations equations method

Condition equation: Model and solution strategy, adjustment of linear and non-linear forms, variance-covariance propagation of adjusted data in condition equations method

Combined method: Model and solution strategy, variance-covariance propagation of adjusted data in combined equations method observation and condition equations as simplification of combined method

Post-analysis 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.



  1. Ghilani C. D., 2010. Adjustment Computations: Spatial Data Analysis (5th ed.), Wiley: NJ, pp. 647.
  2. Leick, A., 2004. GPS Satellite Survey (2nd ed.), Wiley: NY, pp. 429.
  3. Metheley, B. D. F., 1986. Computation Methods in Surveying        and Photogrammetry, Blakie: London, pp. 347.
  4. Mikhail E. M. and Ackermann F., 1976. Observations and Least Squares, IEP Dun-Donnelley: NY , pp. 497.
  5. Mikhail, E. M. and Gracie, G., 1976. Analysis and Adjustment of Survey Measurement. Van Nostrand Reinhold: NY, pp. 340.
  6. Mikhail, E. M., 2001. Introduction to Modern Photogrammetry,Wiley: NY, pp. 479.
  7. Ogundare, J. O. 2019, Understanding Least Squares Estimation and Geomatics Data Analysis, Wiley: USA, pp. 697.
  8. Webster, R. and Oliver, M. A., 2007. Geostatistics for Environmental Scientists, Second Edition, Wiley: Chichester, pp. 332.