STAR*NET V6 - Circe

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Chapter 8 Analysis of Adjustment Output The answer to a non-convergence problem may be as easy as simply increasing the number of iterations. Because of the geometry of the network, or possibly because of some poor initial estimates of approximate coordinates, some networks just take a larger number of iterations to converge. If the adjustment still fails to converge, even after increasing the iterations to a much larger number, say 20, there is likely some problem in your data which needs to be found and fixed. 8.10 Coordinate Changes from Entered Provisionals (Optional) STAR*NET optionally lists differences between hand-entered provisional coordinates and the final adjusted coordinates. This option is particularly useful in deformation studies where the purpose is to determine how much specific stations moved since the previous survey. To do this, simply enter the specific adjusted coordinates from your previous survey as provisional (approximate) coordinates for a new survey, and request this optional listing section. Only changes from these hand-entered provisional coordinates will be shown in this output listing section, not the remaining approximate coordinates computed by the program. Coordinate Changes from Entered Provisionals (US Feet) Station dN dE dZ 319 0.0000 0.0000 0.0000 46 -0.5022 -0.2278 -1.6420 552 -1.0064 0.9188 0.9973 559 -1.0477 0.7678 0.9115 560 0.2513 0.4325 0.2234 Coordinate Changes from Entered Provisionals (3D Example) When entering provisional coordinates to be used as the basis for computing the changes as described above, it is important to place these coordinate values at the beginning of your data so that they will be read “first” during the processing. Why is this? When STAR*NET reads data and finds more than one set of approximate coordinates for a particular station, only the “first” coordinate values are remembered. The remaining are ignored. Therefore, placing your provisional coordinates first in the data assures you that some other approximate coordinates may be already existing later in the data will not corrupt your desired results. You might consider creating your “provisional” coordinates in a separate file, and placing this file as the first entry in your data file list. Then at some future time when you want to update the provisional coordinates for a subsequent run, simply replace that file’s contents with the newer provisional coordinates. 126
Chapter 8 Analysis of Adjustment Output 8.11 Adjusted Observations and Residuals (Optional) STAR*NET next lists all adjusted observations and their residuals. A residual is the difference between the observed value and the corresponding value computed from the adjusted coordinates. The sizes of the residuals are an indication of how well your observations have fit into the adjusted network. The observation standard errors you specified are also listed to show you how much weight each observation had in the adjustment. Although this section of the listing is optional, it is an important one that you normally will want included. Adjusted Observations and Residuals =================================== Adjusted Angle Observations (DMS) At From To Adj Angle Residual StdErr StdRes 1 701 2 123-40-27.22 -0-00-00.12 4.55 0.0 2 1 3 217-11-36.03 -0-00-00.94 4.99 0.2 3 2 4 113-53-19.28 0-00-21.27 5.18 4.1* Adjusted Distance Observations (FeetUS) From To Adj Dist Residual StdErr StdRes 1 2 537.5551 0.0351 0.0211 1.7 2 3 719.5360 0.0260 0.0273 1.2 3 4 397.6922 0.0322 0.0202 1.5 Adjusted Observations and Residuals You should examine the residuals carefully to see whether they appear reasonable. STAR*NET computes an additional value called the Standardized Residual (StdRes), which is equal to the residual divided by its standard error. This ratio takes into account the different types of observations (i.e. angles and distances) and the different units of standard error (i.e. seconds and feet) assigned to them, and and lets you easily make comparisons of the changes to all observations as “Standardized” residuals. You can also think of this value as the ratio between your observation’s actual fit in the adjustment (its residual), and your estimate of the strength (your input standard error). If the ratio is less than 1.0, it actually fit better than you had estimated. If it is larger than one, it didn’t fit as well. However, Standardized Residuals usually have a value greater than 3.0 before we can really say that there is a problem. Values greater than 3.0 are flagged with “*” to help you locate them quickly. The cause of any flagged values should be investigated. However, no observation should be deleted until a good reason is found for the problem. A large residual in a particular observation may be the result of a blunder in some other observation. 127
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STAR*NET V6 Least Squares Survey Ad
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TABLE OF CONTENTS Chapter 1 OVERVIE
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10.9 Entering a Geoid Height and Ve
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Chapter 1 Overview 4. Survey planni
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Chapter 2 Installation 2.3 Starting
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2.7 The Registry Chapter 2 Installa
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3.3 The Menu System Chapter 3 Using
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3.8 Checking the Error File Chapter
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Chapter 3 Using STAR*NET 3.12 Displ
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Chapter 4 Options 4.2 Changing Proj
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Option Group: Units Chapter 4 Optio
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General Options Chapter 4 Options T
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Chapter 4 Options Option Group: Dis
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Chapter 4 Options What standard err
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Chapter 4 Options The default metho
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Option Group: Adjusted Contents Cha
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Other Files Options Chapter 4 Optio
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Chapter 4 Options Creating a Ground
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Special Options Chapter 4 Options T
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4.5 Company Options Chapter 4 Optio
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Chapter 4 Options Note that any dat
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Chapter 4 Options When the Instrume
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Using the Input Data Files Dialog C
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Chapter 5 Preparing Input Data 5.5
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Station Names Chapter 5 Preparing I
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Chapter 5 Preparing Input Data Zeni
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Point Descriptors Chapter 5 Prepari
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Example 1: (2D Data) Chapter 5 Prep
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Chapter 5 Preparing Input Data The
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Chapter 5 Preparing Input Data SING
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The “V” Code: Vertical Observat
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Chapter 5 Preparing Input Data Samp
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Example 2: (2D Data) Chapter 5 Prep
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Chapter 5 Preparing Input Data The
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Chapter 5 Preparing Input Data TRAV
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Chapter 5 Preparing Input Data Exam
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The “TE” Code: Ending a Travers
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Chapter 5 Preparing Input Data LEVE
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Page 106 and 107: How do I weight observations? Chapt
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Page 110 and 111: Chapter 6 Running Adjustments The S
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Page 146 and 147: Chapter 9 Tools As discussed above,
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Appendix A STAR*NET Tutorial Exampl
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Appendix A STAR*NET Tutorial Before
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Example 5: Resection Appendix A STA
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Example 7: Preanalysis Appendix A S
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Appendix B References 6. Mikhail, E
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Appendix C Additional Technical Inf
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Appendix C Additional Technical Inf
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Appendix D Error and Warning Messag
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Data Lines, General Content Data Ty
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Index Installation Installing, 3 Se
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STARPLUS SOFTWARE, INC.
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STAR*NET V6 - Circe

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