Part 4 : Types of Error – Systematic Errors

  1. Systematic errors exist from instrument calibration, observational procedures and the data pre-processing for atmospheric and other effects.
  2. Physical sources of systematic errors are
    1. Temperature,
    2. Humidity,
    3. Pressure changes.
  3. All physical sources will affect :-
    1. angle measurement, distance measurement either by tapes or EDM
    2. will cause the bending of photogrammetry light rays due to atmospheric refraction,
    3. lack of adequate adjustment of equipment
  4. Can be eliminated by :-
    1. Adjusting the instruments
    2. Using certain procedure during measurement, example: levelling survey collimation errors can be minimized by taking measurement at equal distance from the level.

Mikhail, (1974) said " systematic effect take on different forms depending on the value and sign of each of the effects. If the value and sign remain the same all through the measuring process, we would have the so-called constant error. An example of this is making distance measurement with a tape that is either too short (or too long) by a constant value. All length measured by that tape will undergo the same systematic effect due to the tape alone. If the sign of the systematic effect changes, perhaps due to personal bias of an observer, the resulting systematic errors are often called counteracting. For example, on a aerial photograph earth curvature and atmospheric refraction cause opposite displacement of image points. Thus the systematic effect due to the first counteracts that due to the second."

Mikhail, E. M. (1974). Observation and Least Square, A Dun-Donnelley Publisher, New York

Abstract : Least Squares Formula for Zero Error of Electromagnetic Distance Measuring Instruments

AliReze Amiri-Simkooei (2003). Least Squares Formula for Zero Error (Z0) of Electromagnetic Distance Measuring Instruments. Journal of Surveying Engineering. Vol. 129, No 4, November 1, 2003

Abstract: The zero error of electromagnetic distance measuring instruments is a near-constant systematic error, which has the same effect on the measured distances. This paper presents a least-squares formula for this correction based on the division of a baseline into m subbaselines, and measuring all possible distances between the marked points. The validity of the formulation is verified by two examples.

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Part 3 : Types of Errors – Gross Errors

Gross errors – blunders – mistakes

Examples (Cooper, 1974):

  1. A tape reading of 38.23m may be recorded as 38.32m in the field book,
  2. The thermometer may be misread
  3. Measurement may be made between the wrong pegs

Characteristics - its magnitude is significantly very large or different in comparison to the measured values

Sources – Personal errors (careless of the observer)

Effect – Inhomogeneous observables

In practice there are variety of ways that can be employed to reduced gross errors (Mikhail, 1974)

  1. Taking multiple reading and checking for reasonable consistency
  2. Careful checking of both pointing and recording
  3. Using simple and quick technique for verification
  4. Applying logic and common sense
  5. Checking and verifying the performance of equipment, particularly those with automatic readout
  6. Repeating the experiment with perhaps slightly different technique
  7. Increasing redundancy of the observation used in a model

References

  1. Cooper, M.A.R. (1974). Fundamental of Survey Measurement and Analysis. Crosby Lockwood Staples, Great Britain
  2. Mikhail, E.M. (1974). Observations and Least Squares. A Dun-Donnelley Publisher, New York

Part 2 – Sources of Errors

In observations, errors sources can be from:-

  1. Personal    – limitation of the observer, where the ability to repeat the same measurement
  • Careless of the observer
  1. Instrumental    - Due to imperfect construction of incomplete adjustment of the instrument (eg, incorrect graduation)
  2. Natural     - Due to changing environmental condition (eg, temperature)

Part I - About Observations

Geodesy, Geodetic or Geospatial data are composed of points, lines and area relations which rich attributes.

In other word, surveyor are usually faced with the problem of estimating unknown quantities (paramaters). This is done through collecting several measurement known as observations.

Then adopting the appropriate mathematical model relating both observation and unknowns.

Observation generally requires some form instrumentations that is used by an observer in certain environment.

All observations contain errors. An error is different between an observation of a quantity and the true value. True value can never be known.

True error (e) = l – t, where l is observed value and t is true value

Both quantities, e and t can be estimated ..