GNU Gama 2.29

1. Introduction

GNU Gama package is dedicated to adjustment of geodetic networks. It is intended for use with traditional geodetic surveyings which are still used and needed in special measurements (e.g., underground or high precision engineering measurements) where the Global Positioning System (GPS) cannot be used.

In general, surveying is the technique and science of accurately determining the terrestrial or three-dimensional spatial position of points and the distances and angles between them.(1)

Adjustment is a technical term traditionally used by geodesists and surveyors which simply means “application of the least squares method to process the over-determined system of measurements” (statistical methods other than least squares are used sometimes but are not common). In other words, we have more observations than needed and we are trying to get the best estimate for adjusted observations and/or coordinates.

Adjustment of geodetic networks means that we have a set of fixed points with given coordinates, a set of points with unknown coordinates (possibly with approximate values available) and a set of observations among them. What is typical of adjustment of special geodetic measurements is that the resulting linearized system might be singular (we can have a network with no fixed points) and we are not only interested in the values of ‘adjusted parameters and observations’ but also in the estimates of their covariances. This is what Gama does.

Gama was originally inspired by Fortran system Geodet/PC (1990) designed by Frantisek Charamza. The GNU Gama project started at the department of mapping and cartography, faculty of Civil Engineering, Czech Technical University in Prague (CTU) about 1998 and its name is an acronym for geodesy and mapping. It was presented to a wider public for the first time at FIG Working Week 2000 in Prague and then at FIG Workshop and Seminar at HUT Helsinki in 2001.

The GNU Gama home page is

http://www.gnu.org/software/gama/

and the project is hosted on

http://savannah.gnu.org/git/?group=gama

GNU Gama is released under the GNU General Public License and is based on a C++ library of geodetic classes and functions and a small C++ template matrix library matvec. For parsing XML documents GNU Gama calls the expat parser version 1.1, written by James Clark. The expat parser is not part of the GNU Gama project, but it is used by the project.

Adjustment in local Cartesian coordinate systems is fully supported by a command-line program gama-local that adjusts geodetic (free) networks of observed distances, directions, angles, height differences, 3D vectors and observed coordinates (coordinates with given variance-covariance matrix). Adjustment in global coordinate systems is supported only partly as a gama-g3 program.

1.1 Download

GNU Gama can be found in the subdirectory /gnu/gama/ on your favourite FTP GNU mirror or cloned from the GIT. See our project page at savannah for more information.

To get anonymous read-only access to the GIT repository for the latest GNU Gama source, issue the following command

git clone git://git.sv.gnu.org/gama.git

1.2 Install

GNU Gama is developed and tested under GNU/Linux. A static library libgama.lib and executables are build in folders lib and src. You can compile Gama easily yourself if you download the sources from a FTP server. The preferred way is to have expat XML parser installed on your system, if not, GNU Gama will be build with internally stored expat older source codes version 1.1.

Change to the directory of Gama project and issue the following commands at the shell prompt (with some optional parameters)

$ ./configure [--enable-extra-tests --bindir=DIR --infodir=DIR]
$ make

For GNU Gama test suite run

$ make check

If the script configure is not available (which is the case when you download source codes from the git server), you have to generate it using auxiliary script autogen.sh. To compile and build all binaries. Run

$ ./autogen.sh
$ ./configure

and

$ make install [--prefix=/your/prefered/install/directory]

if you also want to install executables and info documentation.

Typically, if you want to download (see section Download) and compile sources, you will run following commands:

$ git clone git://git.sv.gnu.org/gama.git gama
$ cd gama
$ ./autogen.sh
$ ./configure
$ make

You should have expat XML parser and SQLite library already installed on your system. For example to be able to compile Gama on Ubuntu 10.04 you have to install following packages:

make doxygen git automake autoconf libexpat1-dev libsqlite3-dev

To compile user documentation in various formats (PDF, HTML, …) run the following commands

$ cd doc/
$ make download-gendocs.sh
$ make run-gendocs.sh

The documentation should be in doc/manual directory. To compile API documentation run

$ doxygen

in your gama directory. Doxygen output will be in the doxygen directory.

1.2.1 CMake

Alternatively you can use CMake to generate makefiles for Unix, Windows, Mac OS X, OS/2, MSVC, Cygwin, MinGW or Xcode. Configuration file CMakeLists.txt is available from the root distribution directory. For example to build gama-local binary for Linux run

$ mkdir build_dir
$ cd build_dir
$ cmake .. [ -G generator-name ]
$ make --build .

where build_dir is an arbitrary directory name for out-of-place build and optional generator-name specifies a build system generator, for example Ninja.

1.2.2 pkgsrc

pkgsrc is a framework for managing third-party software on UNIX-like systems, currently containing over 26,000 packages. It is the default package manager of NetBSD and SmartOS, and can be used to enable freely available software to be built easily on a large number of other UNIX-like platforms. The binary packages that are produced by pkgsrc can be used without having to compile anything from source. It can be easily used to complement the software on an existing system.

Gama is available via pkgsrc as geography/gama, see https://www.pkgsrc.org/ for more information.

1.2.3 Precompiled executables for Windows

qgama is a Qt application for adjustment of geodetic networks with database support, where the database can be a simple SQLite3 flat file, used for storing geodetic network data, or any full-featured relational DBMS with Qt driver available like PostgreSQL or MySQL. It is build on the GNU gama adjustment library.

Windows executable qgama.exe with all DLL libraries is available from the GNU FTP server

https://ftp.gnu.org/gnu/gama/windows/

together with command-line interface executables gama-local.exe and gama-g3 in the subdirectory bin.

1.3 Program gama-local

Program gama-local is a simple command line tool for adjustment of geodetic free networks. It is available for GNU Linux (the main platform on which project GNU Gama is being developed), BSD or Windows.

Program gama-local reads input data in XML format (XML input data format for gama-local) and prints adjustment results into ASCII text file. If output file name is not given, adjustment results in XML format are sent to the standard output device. If development files for Sqlite3 (package libsqlite3-dev) are installed, gama-local also supports reading adjustment input data from sqlite3 database. When run without arguments gama-local [--help] prints a review of runtime options

Adjustment of local geodetic network        version: 2.29
************************************
https://www.gnu.org/software/gama/

Usage: gama-local  [--input-xml] input.xml  [options]
       gama-local  [--input-xml] input.xml  --sqlitedb sqlite.db  --configuration name  [options]
       gama-local  --sqlitedb sqlite.db  --configuration name  [options]
       gama-local  --sqlitedb sqlite.db  --readonly-configuration name  [options]

Options:

--algorithm  gso | svd | cholesky | envelope
--language   en | ca | cz | du | es | fi | fr | hu | ru | ua | zh
--encoding   utf-8 | iso-8859-2 | iso-8859-2-flat | cp-1250 | cp-1251
--angular    400 | 360
--latitude   <latitude>
--ellipsoid  <ellipsoid name>
--text       adjustment_results.txt
--html       adjustment_results.html
--xml        adjustment_results.xml
--octave     adjustment_results.m
--svg        network_configuration.svg
--cov-band   covariance matrix of adjusted parameters in XML output
             n  = -1  for full covariance matrix (implicit value)
             n >=  0  covariances are computed only for bandwidth n
--iterations maximum number of iterations allowed in the linearized
             least squares algorithm (implicit value is 5)
--export     updated input data based on adjustment results
--verbose    [yes | no]
--version
--help

Report bugs to: <[email protected]>
GNU gama home page: <https://www.gnu.org/software/gama/>
General help using GNU software: <https://www.gnu.org/gethelp/>

Program version is followed by information on compiler used to build the program (apart from GNU g++ compiler other possibilities are Clang, Intel C++ compiler and Visual C++, when build under Microsoft Windows).

Program gama-local can read XML input from the standard input if you put "-" (hyphen) after the option --input-xml. This option is special because it is optional (you can specify XML input file name or "-" without it). Elective --input-xml enables backward compatibility with the usage of older versions.

Adjustment results (--text, --xml) and others can be similarly redirected to standard output if instead of a file name is used "-" string. If no output is given, XML adjustment format is implicitly send to standard output.

Option --algorithm enables to select numerical method for solution of the adjustment. Implicit algorithm is sparse matrix envelope. Another possibilities are Cholesky decomposition of semidefinite matrix of normal equations (cholesky), block matrix algorithm GSO by Frantisek Charamza based on Gram-Schmidt orthogonalization (gso) and Singular Value Decomposition (svd). In the last two cases (gso and svd) project equations are solved directly without forming normal equations.

Option --language selects language used in output protocol. For example, if run with option --language cz, gama-local prints output results in Czech languague using UTF-8 encoding. Implicit value is en for output in English.

Option --encoding enables to change inplicit UTF-8 output encoding to iso-8859-2 (latin-2), iso-8859-2-flat (latin-2 without diacritics), cp-1250 (MS-EE encoding) cp-12251 (Russian encoding).

Option --angular selects angular units to be used in output.

Options --latitude and/or --ellipsoid are used when observed vertical and/or zenith angles need to be transformed into the projection plane. If none of these two options is explicitly used, no corrections are added to horizontal and/or zenith angles. If only one of these options is used, then implicit value for --latitude is 45 degrees (50 gons) and implicit ellipsoid is WGS84. Mathematical formulas for the corrections is given in the following section.

Option --octave is used to output simplified adjustment results for GNU Octave, i.e. in an .m file. The following information is give in the output file

• general adjustment paramameters (number of unknowns, observetions etc.)
• list of fixed points’ ids (may be empty)
• adjustment points; ids
• adjustment indexes of unknouwns
• indexes of constrained coordinates (subset of adjustment indexes)
• approximate and adjusted coordinates (zero if not available)
• full covariance matrix of adjusted coordinates
• sparse design matrix, rhs and weights (Ax = b, P = inv(C_ll))
• and adjustment results in matrix format

In the case of free networks system of normal equations is augmented with matrix of constrains. Adjustmment can be then computed independetly in Octave and compared with results from Gama for unknown coordinates. We suggest that for comaprision of Gama and Octave results number of itereations is set to zero (--iterations 0).

This Octave output is currently available only for algorithm envelope (Gama version 2.10), also adjustment in Octave is not supported for the special case of one fixed point and one constrained (where normal equation cannot be directly augmented with constraints because of different number of unknowns).

Option --cov-band is used to reduce the number of computed covariances (cofactors) in XML adjustment output. Implicitly full matrix is written to XML output, which could degrade time efficiency for the envelope algorithm for sparse matrix solution. Explicit option for full covariance matrix is --cov-band -1, option --cov-band 0 means that only a diagonal of covariance matrix is written to XML output, --cov-band 1 results in computing the main diagonal and first codiagonal etc. If higher rank is specified then available, it is reduced do maximum possible value dim-1.

Option --iterations enables to set maximum number of iterations allowed in the linearized least squares algorithm. After the adjustment gama-local computes differences between adjusted observations computed from residuals and from adjusted coordinates. If the positional difference is higher than 0.5mm, approximate coordinates of adjusted points are updated and the whole adjustment is repeated in a new iteration. Implicit number of iterations is 5.

1.3.1 Reductions of horizontal and zenith angles

For evaluating of reductions of horizontal and zenith angles, gama-local computes a helper point P_1 in the center of the network. Horizontal and zenith angles observed at point P_2 are transformed to the projection plane perpendicular to the normal z_1 of the helper point P_1. Coordinates (x_2, y_2) of point P_2 are conserved, but its normal z_2 is rotated by the central angle 2\gamma_12 to be parallel with z_1.

Formulas for reductions of horizontal and zenith angles are given only in the printed version.

1.4 Reporting bugs

Undoubtedly there are numerous bugs remaining, both in the C++ source code and in the documentation. If you find a bug in either, please send a bug report to

[email protected]

We will try to be as quick as possible in fixing the bugs and redistributing the fixes. If you prefere, you can always write directly to Aleš Čepek.

1.5 Contributors

The following persons (in chronological order) have made contributions to GNU Gama project: Aleš Čepek, Jiří Veselý, Petr Doubrava, Jan Pytel, Chuck Ghilani, Dan Haggman, Mauri Väisänen, John Dedrum, Jim Sutherland, Zoltan Faludi, Diego Berge, Boris Pihtin, Stéphane Kaloustian, Siki Zoltan, Anton Horpynich, Claudio Fontana, Bronislav Koska, Martin Beckett, Jiří Novák, Václav Petráš, Jokin Zurutuza, 项维 (Vim Xiang), Tomáš Kubín, Greg Troxel, Kristian Evers, Oleg Goussev, Petra Millarová, Jan Holešovský and Friedhelm Krumm.

Jiří Veselý is the author of calculation of approximate coordinates by intersections and transformations (class Acord). Václav Petráš is the author of SQL schema, SQLite and gama-local. Petra Millarová is the main author of class Acord2 and other helper classes for combinatorial solution of medians of approximate coordinates.

Friedhelm Krumm, Geodätisches Institut Universität Stuttgart, contributed numerical examples for the adjustment of geodetic networks (1D, 2D and 3D) published in his Geodetic Network Adjustment Examples, Rev. 3.5, January 20, 2020. https://www.gis.uni-stuttgart.de/ In version 2.18 the format of input data used in his Examples was implemented in GNU Gama and is used in command line conversion program gama-local-krumm2xml and also directly in qgama GUI.

2. XML input data format for gama-local

The input data format for a local geodetic network adjustment (program gama-local) is defined in accordance with the definition of Extended Markup Language (XML) for description of structured data. The XML definition can be found at

http://www.w3.org/TR/REC-xml

Input data (points, observations and other related information) are described using XML start-end pair tags <xxx> and </xxx> and empty-element tags <xxx/>.

The syntax of XML gama-local input format is described in XML schema (XSD), the file gama-local.xsd is a part of the GNU gama distribution and can formally be validated independently on the program gama-local, namely in unit testing we use xmllint validating parser, if it is installed.

For parsing the XML input data, gama-local uses the XML parser Expat copyrighted by James Clark which is described at

http://www.jclark.com/xml/expat.html

Expat is subject to the Mozilla Public License (MPL), or may alternatively be used under the GNU General Public License (GPL) instead.

In the gama-local XML input, distances are given in meters, angular values in centigrades and their standard deviations (rms errors) in millimeters or centigrade seconds, respectively. Alternatively angular values in gama-local XML input can be given in degrees and seconds (see section Angular units). At the end of this chapter an example of the gama-local XML input data object is given.

2.1 Angular units

Horizontal angles, directions and zenith angles in gama-local XML adjustment input are implicitly given in gons and their standard deviations and/or variances in centicentigons. Gon, also called centesimal grade and Neugrad (German for new grad), is 1/400-th of the circumference. For example

 <direction  from="202" to="416" val="63.9347"  stdev="10.0" />

The same angular value (direction) can be expressed in degrees (sexagesimal graduation) as

 <direction  from="202" to="416" val="57-32-28.428"  stdev="3.24" />

In XML adjustment input degrees are coded as a single string, where degrees (57), minutes (32) and seconds (28.428) are separated by dashes (-) with optional leading sign. Spaces are not allowed inside the string. Gons and degrees may be mixed in a single XML document but one should be careful to supply the information on standard deviations and/or covariances in the proper corresponding units.

Sexagesimal seconds (ss) are commonly called arcseconds, they are related to the metric system centicentigons (cc) as

ss = cc/400/100/100 * 360*60*60 = cc*0.324.

Internally gama-local works with gons but output can be transformed to degrees using the option --angular 360.

Another angular unit commonly used in surveying is the milligon (mgon), 1 mgon = 1 gon/1000 (similarly as 1 mm = 1 m/1000) and 10 cc = 1 mgon.

2.2 Prologue

XML documents begin with an XML declaration that specifies the version of XML being used (prolog). In the case of gama-local follows the root tag <gama-local> with XML Schema namespace defined in attribute xmlns:

<?xml version="1.0" ?>
<gama-local xmlns="http://www.gnu.org/software/gama/gama-local">

GNU Gama uses non-validating parser and the XML Schema Definition namespace is not used in gama-local but it is essential for usage in third party software that might need XML validation.

2.3 Tags <gama-local> and <network>

A pair tag <gama-local> contains a single pair tag <network> that contains the network definition. The definition of the network is composed of three sections:

• <description> of the network (annotation or comments),
• network <parameters /> and
• <points-observations> section.

The sections <description> and <parameters /> are optional, the section <points-observations> is mandatory. These three sections may be presented in any order and may be repeated several times (in such a case, the corresponding sections are linked together by the software).

The pair tag <network> has two optional attributes axes-xy and angles. These attributes are used to describe orientation of the xy orthogonal coordinate system axes and the orientation of the observed angles and/or directions.

• axes-xy="ne" orientation of axes x and y; value ne implies that axis x is oriented north and axis y is oriented east. Acceptable values are ne, sw, es, wn for left-handed coordinate systems and en, nw, se, ws for right-handed coordinate systems (default value is ne).
• angles="right-handed" defines counterclockwise observed angles and/or directions, value left-handed defines clockwise observed angles and/or directions (default value is left-handed).

Many geodetic systems are right handed with x axis oriented east, y axis oriented north and counterclockwise angular observations. Example of left-handed orthogonal system with different axes orientation is coordinate system Krovak used in the Czech Republic where the axes x and y are oriented south and west respectively.

GNU Gama can adjust any combination of coordinate and angular systems.

Example

<gama-local>
<network>
   <description> ... </description>
   <parameters ... />
   <points-observations> ... </points-observations>
</network>
</gama-local>

It is planned in future versions of the program to allow more <network> tags (analysis of deformations etc.) and definitions of new tags.

2.4 Network description

The description of a geodetic network is enclosed in the start-end pair tags <description>. Text of the description is copied into the adjustment output and serves for easier identification of results. The text is not interpreted by the program, but it may be helpful for users.

Example

<description>
A short description of a geodetic network ...
</description>

2.5 Network parameters

The network parameters may be listed with the following optional attributes of an empty-element tag <parameters />

• sigma-apr = "10" value of a priori reference standard deviation—square root of reference variance (default value 10)
• conf-pr = "0.95" confidence probability used in statistical tests (dafault value 0.95)
• tol-abs = "1000" tolerance for identification of gross absolute terms in project equations (default value 1000 mm)
• sigma-act = "aposteriori" actual type of reference standard deviation use in statistical tests (aposteriori | apriori); default value is aposteriori
• algorithm = "gso" numerical algortihm used in the adjistment (gso, svd, cholesky, envelope).
• languade = "en" the language to be used in adjustment output.
• encoding = "utf-8" adjustment output encoding.
• angular = "400" output results angular units (400/360).
• latitude = "50"
• ellipsoid
• cov-band = "-1" the bandwith of covariance matrix of the adjusted parameters in the output XML file (-1 means all covariances).

Values of the attributes must be given either in the double-quotes ("…") or in the single quotes ('…'). There can be white spaces (spaces, tabs and new-line characters) between attribute names, values, and the equal sign.

Example

<parameters sigma-apr = "15"
            conf-pr   = '0.90'
            sigma-act = "apriori" />

2.6 Points and observations

The points and observations section is bounded by the pair tag <points-observations> and contains information about points, observed horizontal directions, angles, and horizontal distances, height differences, slope distances, zenith angles, observed vectors and control coordinates.

Optional attributes of the start tag <points-observations> allow for the definition of default values of standard deviations corresponding to observed directions, angles, and distances.

• direction-stdev = "…" defines the implicit value of standard deviation of observed directions (default value is not defined)
• angle-stdev = "…" defines the implicit value of standard deviation of observed angles (default value is not defined)
• zenith-angle-stdev = "…" defines the implicit value of standard deviation of observed zenith angles (default value is not defined)
• azimuth-stdev = "…" defines the implicit value of standard deviation of observed azimuth angles (default value is not defined)
• distance-stdev = "…" defines the implicit value of standard deviation of observed distances, horizontal or slope (default value is not defined)

Implicit values of standard deviations for the observed distances are calculated from the model with three constants a, b, and c according to the formula

a + bD^c,

where a is a constant part of the model and D is the observed distance in kilometres. If the constants b and/or c are not given, default values b=0 and c=1 will be used.

Example

<points-observations direction-stdev = "10"
                     distance-stdev  = "5 3 1" >
   <!-- ... points and observation data ... -->
</points-observations>

2.7 Points

Points are described by the empty-element tags <point/> with the following attributes:

• id = "…" is the point identification attribute (mandatory); point identification is not limited to numbers; all printable characters can be used in identification.
• x = "…" specifies coordinate x
• y = "…" specifies coordinate y
• z = "…" specifies coordinate z, point height
• fix = "…" specifies coordinates that are fixed in adjustment; acceptable values are xy, XY, z, Z, xyz, XYZ, xyZ and XYz.
• adj = "…" specifies coordinates to be adjusted (unknown parameters in adjustment); acceptable values are xy, XY, z, Z, xyz, XYZ, xyZ and XYz.

With exception of the first attribute (point id), all other attributes are optional. Decimal numbers can be used as needed.

Control coordinates marked using the fix parameter are not changed in the adjustment. Uppercase and lowercase notation of coordinates with the fix parameter are interpreted the same. Corrections are applied to the unknown parameters identified by coordinates written in lowercase characters given in the adj parameter. When the coordinates are written using uppercase, they are interpreted as constrained coordinates. If coordinates are marked with both the fix and adj, the fix parameter will take precedence.

Constrained coordinates are used for the regularization of free networks. If the network is not free (fixed network), the constrained coordinates are interpreted as other unknown parameters. In classical free networks, the constrained points define the regularization constraint

\sum dx^2_i+dy^2_i = \min.

where dx and dy are adjusted coordinate corrections and the summation index i goes over all constrained points. In other words, the set of the constrained points defines the adjustment of the free network (its shape and size) with a simultaneous transformation to the approximate coordinates of selected points. Program gama-local allows the definition of constrained coordinates with 1D leveling networks, 2D and 3D local networks.

Example

<point id="1" y="644498.590" x="1054980.484" fix="xy"  />
<point id="2" y="643654.101" x="1054933.801" adj="XY" />
<point id="403" adj="xy" />

2.8 Set of observations

The pair tag <obs> groups together a set of observations which are somehow related. A typical example is a set of directions and distances observed from one stand-point. An observation section contains a set of

• horizontal directions <direction … />
• horizontal distances <distance … />
• horizontal angles <angle … />
• slope distances <s-distance … />
• zenith angles <z-angle … />
• azimuths <azimuth … />

The band variance-covariance matrix of directions, distances, angles or other observations listed in one <obs> section may be supplied using a <cov-mat> pair tag with attributes dim (dimension) and band (bandwidth). The band-width of the diagonal matrix is equal to 0 and a fully-populated variance-covariance matrix has a bandwidth of dim-1.

Observation variances and covariances (i.e. an upper-symmetric part of the band-matrix) are written row by row between <cov-mat> and </cov-mat> tags. If present, the dimension of the variance-covariance matrix must agree with the number of observations.

The following example of variance-covariance matrix with dimension 6 and bandwidth 2 (two nonzero codiagonals and three zero codiagonals)

[ 1.1  0.1  0.2   0    0    0
  0.1  1.2  0.3  0.4   0    0
  0.2  0.3  1.3  0.5  0.6   0
   0   0.4  0.5  1.4  0.7  0.8
   0    0   0.6  0.7  1.5  0.9
   0    0    0   0.8  0.9  1.6 ]

is coded in XML as

<cov-mat dim="6" band="2">
   1.1  0.1  0.2
        1.2  0.3  0.4
             1.3  0.5  0.6
                  1.4  0.7  0.8
                       1.5  0.9
                            1.6
</cov-mat>

If two or more sets of directions with different orientations are observed from a stand-point, they must be placed in different <obs> sections. The value of an orientation angle can be explicitly stated with an attribute orientation="…". Normally, it is more convenient to let the program calculate approximate values of orientations needed for the adjustment. If directions are present, then the attribute station must be defined.

Optional attribute from_dh="…" enables to enter implicit height of instrument for all observations within the <obs> pair tag.

Observed distances are expressed in meters, their standard deviations in millimeters. Observed directions and angles are expressed in centigrades (400) and their standard deviations in centigrade seconds.

Example

<obs from="418">
   <direction  to=  "2" val="0.0000"   stdev="10.0" />
   <direction  to="416" val="63.9347"  stdev="10.0" />
   <direction  to="420" val="336.3190" stdev="10.0" />
   <distance   to="420" val="246.594"  stdev="5.0"  />
</obs>

<obs from="418">
   <direction  to=  "2" val="0.0000"   />
   <direction  to="416" val="63.9347"  />
   <direction  to="420" val="336.3190" />
   <distance   to="420" val="246.594"  />

   <cov-mat dim="4" band="0">
      100.00 100.00 100.00 25.00
   </cov-mat>
</obs>

2.9 Directions

Directions are expressed with the following attributes in an empty-element tag <direction />

• to = "…" target point identification
• val = "…" observed direction; see section Angular units
• stdev = "…" standard deviation (optional)
• from_dh = "…" instrument height (optional)
• to_dh = "…" reflector/target height (optional)

The standard deviation is an optional attribute. However since all observations in the adjustment must have their weights defined, the standard deviation must be given either explicitly with the attribute stdev="…" or implicitly with <points-observation direction-stdev="…" > or with a variance-covariance matrix for the given observation set. A similar approach applies to all the observations (distances, angles, etc.)

All directions in the given <obs> tag (see section Set of observations) share a common orientation shift, which is an implicit adjustment unknown parameter defining relation between the stand point directions and bearings

direction_AB + orientation shift_A = bearing_AB.

Because one <obs> tag defines one orientation shift for all its directions, stand point id must be given in the <obs from="id"> tag, using attribute from, which in turn must not be used in <direction /> tags, to avoid unintentional discrepancies.

Example

<direction  to=  "2" val="0.0000"  stdev="10.0" />
<direction  to="416" val="63.9347" />

2.10 Horizontal distances

Distances are written using an empty-element tag <distance /> with attributes

• from = "…" standpoint identification
• to = "…" target identification
• val = "…" observed horizontal distance
• stdev = "…" standard deviation of observed horizontal distance (optional)
• from_dh = "…" instrument height (optional)
• to_dh = "…" reflector/target height (optional)

Contrary to directions, distances in an observation set (<obs>) do not need to share a common stand-point. An example is set of distances observed from several stand-points with a common variance-covariance matrix.

Example

<distance from = "2"  to = "1" val = "659.184" />
<distance to ="422" val="228.207"  stdev="5.0"  />
<distance to ="408" val="568.341" />

2.11 Angles

Observed angles are expressed with the following attributes of an empty-element tag <angle />

• from = "…" standpoint identification (optional)
• bs = "…" backsight target identification
• fs = "…" foresight target identification
• val = "…" observed angle; see section Angular units
• stdev = "…" standard deviation (optional)
• from_dh = "…" instrument height (optional)
• bs_dh = "…" backsight reflector/target height (optional)
• fs_dh = "…" foresight reflector/target height (optional)

Similar to distance observations, one observation set may group angles observed from several standpoints.

Example

<angle from="433" bs="422" fs="402" val="128.6548" stdev="14.1"/>
<angle from="433" bs="422" fs="402" val="128.6548" />
<angle bs="422" fs="402" val="128.6548" stdev="14.1"/>
<angle bs="422" fs="402" val="128.6548"/>

2.12 Slope distances

Slope distances (space distances) are written using an empty-element tag <s-distance /> with attributes

• from = "…" standpoint identification (optional)
• to = "…" target identification
• val = "…" observed slope distance
• stdev = "…" standard deviation of observed slope distance (optional)
• from_dh = "…" instrument height (optional)
• to_dh = "…" reflector/target height (optional)

Similar to horizontal distances, one observation set may group slope distances observed from several standpoints.

Example

<s-distance from = "2"  to = "1" val = "658.824" />
<s-distance to ="422" val="648.618"  stdev="5.0"  />
<s-distance to ="408" val="482.578" />

2.13 Zenith angles

Zenith angles are written using an empty-element tag <z-angle /> with the following attributes

• from = "…" standpoint identification (optional)
• to = "…" target identification
• val = "…" observed zenith angle; see section Angular units
• stdev = "…" standard deviation of observed zenith angle (optional)
• from_dh = "…" instrument height (optional)
• to_dh = "…" reflector/target height (optional)

Similar to horizontal distances, one observation set may group zenith angles observed from several standpoints.

Example

<z-angle from = "2"  to = "1" val = "79.6548" />
<z-angle to ="422" val="85.4890"  stdev="5.0"  />
<z-angle to ="408" val="95.7319" />

2.14 Azimuths

The azimuth is defined in GNU Gama as an observed horizontal angle measured from the North to the given target. The true north orientation is measured by gyrotheodolites, mainly in mine surveying. In Gama azimuths’ angle can be measured clockwise or counterclocwise according to the angle orientation defined in <parameters /> tag.

Azimuths are expressed with the following attributes in an empty-element tag <azimuth />

• from = "…" standpoint identification
• to = "…" target point identification
• val = "…" observed azimuth; see section Angular units
• stdev = "…" standard deviation (optional)
• from_dh = "…" instrument height (optional)
• to_dh = "…" reflector/target height (optional)

The standard deviation is an optional attribute. However since all observations in the adjustment must have their weights defined, the standard deviation must be given either explicitly with the attribute stdev="…" or implicitly with <points-observation azimuth-stdev="…" > or with a variance-covariance matrix for the given observation set.

Example

<points-observations azimuth-stdev="15.0">

<azimuth from="1"  to=  "2" val= "96.484371" />

2.15 Height differences

A set of observed leveling height differences is described using the start-end tag <height-differences> without parameters. The <height-differences> tag can contain a series of height differences (at least one) and can optionally be supplied with a variance-covariance matrix. Single height differences are defined with empty tags <dh /> having the following attributes:

• from = "…" standpoint identification
• to = "…" target identification
• val = "…" observed leveling height difference
• stdev = "…" standard deviation of levellin elevation and
• dist = "…" distance of leveling section (in kilometers)

If the value of standard deviation is not present and length of leveling section (in kilometres) is defined, the value of standard deviation is computed from the formula

m_dh = m_0 sqrt(D_km)

If the value of standard deviation of the height difference is defined, information on leveling section length is ignored. A third possibility is to define a common variance-covariance matrix for all elevations in the set.

Example

<height-differences>
  <dh from="A" to="B" val=" 25.42" dist="18.1" />
  <dh from="B" to="C" val=" 10.34" dist=" 9.4" />
  <dh from="C" to="A" val="-35.20" dist="14.2" />
  <dh from="B" to="D" val="-15.54" dist="17.6" />
  <dh from="D" to="E" val=" 21.32" dist="13.5" />
  <dh from="E" to="C" val="  4.82" dist=" 9.9" />
  <dh from="E" to="A" val="-31.02" dist="13.8" />
  <dh from="C" to="D" val="-26.11" dist="14.0" />
</height-differences>

2.16 Control coordinates

Control (known) coordinates are described by the start-end pair tag <coordinates>. A series of points with known coordinates can be defined using the <point /> tag. The variance-covariance matrix for the entire set of points can be created with a single <cov-mat> tag. In the <point /> tags, a point identification (ID) and its coordinates (x, y and z) must be listed. Although the order of the <point /> tag attributes is irrelevant in the corresponding variance-covariance matrix, the expected order of the coordinates is x, y and z (the horizontal coordinates x, y, or the height z might be missing, but not both). The type of the points may be defined either directly within the <coordinates> tag or outside of it.

Example

<coordinates>
   <point id="1" x="100.00" y="100.00" />
   <point id="2" z="200.00" y="200.00" x="200.00" />
   <point id="3" z="300.00" />
   <cov-mat dim="6" band="5" >
       ...  <!-- covariances for 1x 1y 2x 2y 2z 3z -->
   </cov-mat>
</coordinates>

2.17 Coordinate differences (vectors)

Observed coordinate differences describe relative positions of station pairs (vectors). Contrary to the observed coordinates, the variance-covariance matrix of the coordinate differences always describes all three elements of the 3D vectors.

Optional attributes of empty element tag <vec> for describing instrument and/or target height are

• from_dh = "…" instrument height
• to_dh = "…" target height

Example

<vectors>
   <vec from="id1" to="id2" dx="..." dy="..." dz="..." />
   <vec from="id2" to="id3" dx="..." dy="..." dz="..." />
   ...
   <cov-mat dim="..." band="..." >
       ..
   </cov-mat>
</vectors>

2.18 Attribute extern

The attribute extern is available for all observation types, including <vector extern="..."> and <coordinates extern="...">. Its values have no impact on processing in gama-local, it only transferes the attribute values from XML input into the corresponing XML tags in the adjustment output.

The attribude extern="value" is provided to enable storing observations’ database keys from an external database system in gama-local XML adjutement input and output. If you do not have such an external application, you probably will not need this attribute.

2.19 Example of local geodetic network

The XML input data format should be now reasonably clear from the following sample geodetic network. This example is taken from user’s guide to Geodet/PC by Frantisek Charamza.

<?xml version="1.0" ?>

<gama-local xmlns="http://www.gnu.org/software/gama/gama-local">
<network axes-xy="sw">

<description>
XML input stream of points and observation data for the program GNU gama
</description>

<!-- parameters are expressed with empty-element tag -->

<parameters sigma-act = "aposteriori" />

<points-observations>

<!-- fixed point, constrained point -->

<point id="1" y="644498.590" x="1054980.484" fix="xy" />
<point id="2" y="643654.101" x="1054933.801" adj="XY" />

<!-- computed / adjusted points -->

<point id="403" adj="xy" />
<point id="407" adj="xy" />
<point id="409" adj="xy" />
<point id="411" adj="xy" />
<point id="413" adj="xy" />
<point id="416" adj="xy" />
<point id="418" adj="xy" />
<point id="420" adj="xy" />
<point id="422" adj="xy" />
<point id="424" adj="xy" />

<obs from="1">
     <direction  to=  "2" val=  "0.0000" stdev="10.0" />
     <direction  to="422" val= "28.2057" stdev="10.0" />
     <direction  to="424" val= "60.4906" stdev="10.0" />
     <direction  to="403" val="324.3662" stdev="10.0" />
     <direction  to="407" val="382.8182" stdev="10.0" />
     <distance   to=  "2" val= "845.777" stdev="5.0"  />
     <distance   to="422" val= "493.793" stdev="5.0"  />
     <distance   to="424" val= "288.301" stdev="5.0"  />
     <distance   to="403" val= "388.536" stdev="5.0"  />
     <distance   to="407" val= "498.750" stdev="5.0"  />
</obs>

<obs from="2">
     <direction  to=  "1" val="0.0000"   stdev="10.0" />
     <direction  to="407" val="22.2376"  stdev="10.0" />
     <direction  to="409" val="73.8984"  stdev="10.0" />
     <direction  to="411" val="134.2090" stdev="10.0" />
     <direction  to="416" val="203.0706" stdev="10.0" />
     <direction  to="418" val="287.2951" stdev="10.0" />
     <direction  to="420" val="345.6928" stdev="10.0" />
     <direction  to="422" val="368.9908" stdev="10.0" />
     <distance   to="407" val="388.562"  stdev="5.0"  />
     <distance   to="409" val="257.498"  stdev="5.0"  />
     <distance   to="411" val="360.282"  stdev="5.0"  />
     <distance   to="416" val="338.919"  stdev="5.0"  />
     <distance   to="418" val="292.094"  stdev="5.0"  />
     <distance   to="420" val="261.408"  stdev="5.0"  />
     <distance   to="422" val="452.249"  stdev="5.0"  />
</obs>

<obs from="403">
     <direction  to=  "1" val="0.0000"   stdev="10.0" />
     <direction  to="407" val="313.5542" stdev="10.0" />
     <distance   to="407" val="405.403"  stdev="5.0"  />
</obs>

<obs from="407">
     <direction  to=  "1" val="0.0000"   stdev="10.0" />
     <direction  to="403" val="55.1013"  stdev="10.0" />
     <direction  to="409" val="193.3410" stdev="10.0" />
     <direction  to=  "2" val="239.4204" stdev="10.0" />
     <direction  to="422" val="323.5443" stdev="10.0" />
     <distance   to="409" val="281.997"  stdev="5.0"  />
     <distance   to="422" val="346.415"  stdev="5.0"  />
</obs>

<obs from="409">
     <direction  to=  "2" val="0.0000"   stdev="10.0" />
     <direction  to="407" val="102.2575" stdev="10.0" />
     <direction  to="411" val="310.1751" stdev="10.0" />
     <distance   to="411" val="296.281"  stdev="5.0" />
</obs>

<obs from="411">
     <direction  to=  "2" val="0.0000"   stdev="10.0" />
     <direction  to="409" val="49.8647"  stdev="10.0" />
     <direction  to="413" val="291.4953" stdev="10.0" />
     <direction  to="416" val="337.6667" stdev="10.0" />
     <distance   to="413" val="252.266"  stdev="5.0"  />
     <distance   to="416" val="360.449"  stdev="5.0"  />
</obs>

<obs from="413">
     <direction  to="411" val="0.0000"   stdev="10.0" />
     <direction  to="416" val="295.3582" stdev="10.0" />
     <distance   to="416" val="239.745"  stdev="5.0"  />
</obs>

<obs from="416">
     <direction  to=  "2" val="0.0000"   stdev="10.0" />
     <direction  to="411" val="68.8065"  stdev="10.0" />
     <direction  to="413" val="117.9922" stdev="10.0" />
     <direction  to="418" val="348.1606" stdev="10.0" />
     <distance   to="418" val="389.397"  stdev="5.0"  />
</obs>

<obs from="418">
     <direction  to=  "2" val="0.0000"   stdev="10.0" />
     <direction  to="416" val="63.9347"  stdev="10.0" />
     <direction  to="420" val="336.3190" stdev="10.0" />
     <distance   to="420" val="246.594"  stdev="5.0"  />
</obs>

<obs from="420">
     <direction  to=  "2" val="0.0000"   stdev="10.0" />
     <direction  to="418" val="77.9221"  stdev="10.0" />
     <direction  to="422" val="250.1804" stdev="10.0" />
     <distance   to="422" val="228.207"  stdev="5.0"  />
</obs>

<obs from="422">
     <direction  to=  "2" val="0.0000"   stdev="10.0" />
     <direction  to="420" val="26.8834"  stdev="10.0" />
     <direction  to="424" val="225.7964" stdev="10.0" />
     <direction  to=  "1" val="259.2124" stdev="10.0" />
     <direction  to="407" val="337.3724" stdev="10.0" />
     <distance   to="424" val="279.405"  stdev="5.0"  />
</obs>

<obs from="424">
     <direction  to=  "1" val="0.0000"   stdev="10.0" />
     <direction  to="422" val="134.2955" stdev="10.0" />
</obs>

</points-observations>

</network>
</gama-local>

3. YAML input data format for gama-local

YAML is a human-readable data-serialization language. It is commonly used for configuration files and in applications where data is being stored or transmitted. YAML targets many of the same communications applications as Extensible Markup Language but has a minimal syntax which intentionally differs from SGML. Wikipedia

In version 2.12 YAML support was added for gama-local as an alternative to the existing XML input format. The YAML support is limited only to conversion program gama-local-yaml2gkf but it may be fully integrated in gama-local program later.

In GNU Gama YAML documents are based on four main nodes

   defaults:

   description:

   points:

   observations:

Where defaults and description are optional and points and observations are mandatory and each can be used only once. The order of the nodes is arbitrary.

Lets start with a full example

   defaults:
     sigma-apr : 5
     conf-pr:    0.95

   description: >-
     Example: a simple network

   points:
     - id:  1783
       y:   453500.000
       x:   104500.000
       adj: xy

     - id:  2044
       y:   461000.000
       x:   101000.000
       fix: xy

   observations:
     - from: 1783
       obs:
         - type:  direction
           to:    776
           val:   29.51661
           stdev: 2.0

         - type:  direction
           to:    351
           val:   94.22790
           stdev: 2.0

     - from: 351
       obs:
         - type:  direction
           to:    2044
           val:   170.48370
           stdev: 2.0

         - type:  distance
           to:    1783
           val:   5522.668
           stdev: 10.0

     - from: 462
       obs:
         - type:  direction
           to:    2505
           val:   299.99973
           stdev: 2.0

The description node is clearly the simplest one, it just describes a simple text attached to the data. But still there may be a catch. If the description contains colon (:), it might confuse the YAML parser because it would be interpreted as a syntax construction. To escape colon(s) in the description node we use >- to prevent colons to be interpreted as a syntax construction. Always using >- with description is a safe bet.

The data structure of the YAML document is defined by indentation, this principle was inspired by Python programming language, where indentation is very important; Python uses indentation to indicate a block of code.

Practically all attribute names used in out YAML format are the same as in XML data format.

Lets have a look on some more examples. Within observations: section we can define height differerence (another kind of a measurement).

   observations:

     - height-differences:
         - dh:
             from: A
             to  : B
             val : 25.42
             dist: 18.1     # distance in km
         - dh:
             from: B
             to:   C
             val:  10.34
             dist:  9.4

Two remaining observation types are vectors and coordinates.

   observations:
     - vectors:
       - vec:
           from: A
           to: S
           dx: 60.0070
           dy: 35.0053
           dz: 54.9953
       - vec:
           from: B
           to: S
           dx: -39.9974
           dy: 34.9928
           dz: 54.9976

and

   observations:
     - coordinates:
       - id: 403
         x: 1054612.59853
         y: 644373.60446
       - id: 407
         x: 1054821.17131
         y: 644025.97479

   ....

       - cov-mat:
           dim: 20
           band: 19
           upper-part:
             6.7589719e+01 1.8437742e+01 1.3176856e+01 ...

Typically any observation set can define its covariance matrix.

You may wish to compare YAML and XML data files available from Gama tests suite in tests/gama-local/input directory (files *.gkf and *.yaml).

The gama-local input xml data can be formally validated against the XSD definition. Unfortunatelly there is no formal definition of YAML input. Within the testing suite of GNU Gama project we have a test that validates all available YAML files converted to XML by the formal XSD definition, see the test xmllint-gama-local-yaml2gkf.

3.1 YAML support

GNU Gama YAML input format is dependent on C++ YAML-CPP library written by Jesse Beder https://yaml.org/. With the Gama primary build system (autotools) you need to install the library at your system, for example on Debian like systems it is libyaml-cpp-dev package.

A different solution is used in the alternative Gama cmake based build, where the source codes are expected to be available from the lib directory. Change to "GNU Gama sources"/lib and clone the git repository.

   cd "GNU Gama sources"/lib
   git clone https://github.com/jbeder/yaml-cpp

4. SQL schema, SQLite and gama-local

The input data for a local geodetic network adjustment (program gama-local) can be strored in SQLite 3 database file. The general information about SQLite can be found at

http://www.sqlite.org/

Input data (points, observations and other related information) are stored in SQLite database file. Native SQLite C/C++ API is used for reading SQLite database file. It is described at

http://www.sqlite.org/c3ref/intro.html

Please note if you compile GNU Gama as described in Install and SQLite library is not installed on your system, GNU Gama would be compiled without SQLite support.

SQL schema (CREATE statements) is in gama-local-schema.sql file which is part of GNU Gama distribution and is in the xml directory.

All tables for gama-local are prefixed with gnu_gama_local_. In the documentation table names are referred without this prefix. For example table gnu_gama_local_points is referred as points.

Database scheme used for SQLite database is also valid in other SQL database systems. Almost every column has some constraint to ensure correctness.

You can convert existing XML input file to SQL commands with program gama-local-xml2sql, for example

$ gama-local-xml2sql geodet-pc geodet-pc-123.gkf geodet-pc.sql

4.1 Working with SQLite database

First of all you have to create tables for GNU Gama in SQLite database file (here with db extension, but you can choose your own, e.g. sqlite).

$ sqlite3 gama.db < gama-local-schema.sql

You can check created tables by following commands (fist in command line, second in SQLite command line).

$ sqlite3 gama.db
sqlite> .tables

Output should look like this:

gnu_gama_local_clusters        gnu_gama_local_descriptions
gnu_gama_local_configurations  gnu_gama_local_obs
gnu_gama_local_coordinates     gnu_gama_local_points
gnu_gama_local_covmat          gnu_gama_local_vectors

When you have created tables you can import data. One way is to process file with SQL statements.

$ sqlite3 gama.db < geodet-pc.sql

Another way can be filing database file in another program.

For using sqlite3 command you need a command line interface for SQLite 3 installed on your system (e.g. sqlite3 package).

4.2 Units in SQL tables

In the gama-local SQLite database, distances are given in meters and their standard deviations (rms errors) in millimeters. Angular values are given in radians as well as their standard deviations.

Conversions between radians, gons and degrees:

    rad = gon * pi / 200
    rad = deg * pi / 180
    gon = rad * 200 / pi
    deg = rad * 180 / pi

4.3 Network SQL definition

Network definitions are stored in the configurations table. This table contains all parameters for each network such as value of a priori reference standard deviation or orientation of the xy orthogonal coordinate system axes.

It is obvious that in one database file can be stored more networks (configurations).

Configuration descriptions (annotation or comments) are stored separately in table descriptions. The description is split to many records because of compatibility with various databases (not all databases implements type TEXT).

Field (attribute) conf_id identifies a configuration in the database. Field conf_name is used to identify configuration outside the database (e.g. parameter in command-line when reading data from database to gama-local).

Table configurations contains all parameters specified in tag <parameters /> (see section Network parameters) and also gama-local command line parameters (see section Program gama-local). The list of all table attributes (parameters) follows.

• sigma_apr value of a priori reference standard deviation—square root of reference variance (default value 10)
• conf_pr confidence probability used in statistical tests (dafault value 0.95)
• tol_abs tolerance for identification of gross absolute terms in project equations (default value 1000 mm)
• sigma_act actual type of reference standard deviation use in statistical tests (aposteriori | apriori); default value is aposteriori
• update_cc enables user to control if coordinates of constrained points are updated in iterative adjustment. If test on linerarization fails (see section Test on linearization), Gama tries to improve approximate coordinates of adjusted points and repeats the whole adjustment. Coordinates of constrained points are implicitly not changed during iterations. Acceptable values are yes, no, default value is yes.
• axes_xy orientation of axes x and y; value ne implies that axis x is oriented north and axis y is oriented east. Acceptable values are ne, sw, es, wn for left-handed coordinate systems and en, nw, se, ws for right-handed coordinate systems (default value is ne).
• angles right-handed defines counterclockwise observed angles and/or directions, value left-handed defines clockwise observed angles and/or directions (default value is left-handed).
• epoch is measurement epoch. It is floating point number (default value is 0.0).
• algorithm specifies numerical method used for solution of the adjustment. For Singular Value Decomposition set value to svd. Value gso stands for block matrix algorithm GSO by Frantisek Charamza based on Gram-Schmidt orthogonalization, value cholesky for Cholesky decomposition of semidefinite matrix of normal equations and value envelope for a Cholesky decomposition with envelope reduction of the sparse matrix. Default value is svd.
• ang_units Angular units of angles in gama-local output. Value 400 stands for gons and value 360 for degrees (default value is 400). Note that this doesn’t effect units of angles in database. For further information about angular units see Angular units.
• latitude is mean latitude in network area. Default value is 50 (gons).
• ellipsoid is name of ellipsoid (see section Supported ellipsoids).

All fields are mandatory except ellipsoid field. For additional information about handling geodetic systems in gama-local see Tags <gama-local> and <network>.

Example (configuration table contents):

conf_id|conf_name|sigma_apr|conf_pr|tol_abs|sigma_act  |update_cc|...
---------------------------------------------------------------------
1      |geodet-pc|10.0     |0.95   |1000.0 |aposteriori|no       |...

... axes_xy|angles      |epoch|algorithm|ang_units|latitude|ellipsoid
---------------------------------------------------------------------
... ne     |left-handed|0.0  |svd      |400      |50.0    |

The list of description table attributes follows.

• conf_id is id of configuration which description (text) belongs to.
• id identifies text in a database.
• text is part of configuration description. Its SQL type is VARCHAR(1000).

There can be more than one text for one configuration. All texts related to one configuration are concatenated to one description.

Example (description table contents):

conf_id|indx|text
-----------------------------------------------
1      |1   |Frantisek Charamza: GEODET/PC, ...

4.4 Table points

• conf_id is id of configuration which points belongs to.
• id identifies point in a database and also in an output. It is mandatory and it is character string (SQL type is VARCHAR(80)). Point id has to be unique within one configuration. In documentation it is referred as point identification or point id.
• x, y and z coordinates of a point. Coordinate z is considered as height.
• txy and tz specify the type of coordinates x, y and z. Acceptable values are fixed, adjusted and constrained (there is no default value). For details see Points.

Example (table contents):

conf_id|id |x       |y      |z|txy     |tz
------------------------------------------
1      |201|78594.91|9498.26| |fixed   |
1      |205|78907.88|7206.65| |fixed   |
1      |206|76701.57|6633.27| |fixed   |
1      |207|        |       | |adjusted|

4.5 Table clusters

The cluster is a group of observations with the common covariance matrix. The covariance matrix allows to express any combination of correlations among observations in cluster (including uncorrelated observations, where covariance matrix is diagonal). For explanation see Observation data and points.

In the database observations are stored in three tables: obs, coordinates and vectors. Cluster’s covariance matrix is stored in table covmat. Every observation, vector or coordinate in database has to be in some cluster.

• conf_id is id of configuration which cluster belongs to.
• ccluster identifies a cluster within one configuration.
• dim and band specify dimension and bandwidth of covariance matrix. The bandwidth of the diagonal matrix is equal to 0 and a fully-populated covariance matrix has a bandwidth of dim-1 (band maximum possible value is dim-1).
• tag specifies type of observations in cluster which also implies the table where they are stored in. obs and height-differences stand for obs table, coordinates and vectors stand for coordinates table and vectors table respectively.

Observations, vectors and coordinates are identified by configuration id (conf_id), cluster id ccluster and theirs index (indx). Observation index (indx) has to be unique within observations of one cluster (which belongs to one configuration). The same applies for vectors and coordinates.

See also Set of observations.

Example (table contents):

conf_id|ccluster|dim|band|tag
-----------------------------
1      |1       |3  |0   |obs
1      |4       |4  |0   |obs

4.6 Table covmat

Values of cluster covariance matrix are stored in covmat table. Attributes conf_id, ccluster identifies covariance matrix. Value position in matrix is specified by rind and cind fields.

• conf_id is id of configuration which cluster belongs to.
• ccluster is id of cluster which matrix belongs to.
• rind is row number in covariance matrix
• cind is column number covariance matrix
• val is value itself (variance or covariance).

Values rind and cind have to respect dim and band specified in table clusters. If value in covariance matrix is not specified (record is missing), it is considered to be zero.

Example (table contents):

conf_id|ccluster|rind|cind|val
--------------------------------
1      |1       |1   |1   |400.0
1      |1       |2   |2   |400.0
1      |1       |3   |3   |400.0
1      |4       |1   |1   |400.0
1      |4       |2   |2   |400.0
1      |4       |3   |3   |400.0
1      |4       |4   |4   |400.0

4.7 Table obs

Table obs contains simple observations like direction or distance.

• conf_id is id of configuration which cluster belongs to.
• ccluster is id of cluster which observation belongs to.
• indx identifies observation within cluster. It has to be positive integer.
• tag specifies a type of an observation. Allowed tags follows.
  • direction for directions.
  • distance for horizontal distances.
  • angle for angles.
  • s-distance for slope distances (space distances).
  • z-angle for zenith angles.
  • azimuth for azimuth angles.
  • dh for leveling height differences.
• from_id is stand point identification. It is mandatory and it must not differ within one cluster for observations with tag = 'direction' .
• to_id is target identification (mandatory).
• to_id2 is second target identification. It is valid and mandatory only for angles (tag = 'angle').
• val is observation value. It is mandatory for all observation types.
• stdev is value of standard deviation. It is used when variance in covariance matrix is not specified.
• from_dh is value of instrument height (optional).
• to_dh is value of reflector/target height (optional).
• to_dh2 is value of second reflector/target height (optional). It is valid only for angles.
• dist is distance of leveling section. It is valid only for height-differences (tag = 'dh').
• rejected specifies whether observation is rejected (passive) or not. Value 0 stand for not rejected, value 1 for rejected. It is mandatory. Default value is 0.

Example (table contents without empty columns):

conf_id|ccluster|indx|tag      |from_id|to_id|val           |rejected
---------------------------------------------------------------------
1      |1       |1   |direction|201    |202  |0.0           |0
1      |1       |2   |direction|201    |207  |0.817750284544|0
1      |1       |3   |direction|201    |205  |2.020073921388|0

4.8 Table coordinates

Table coordinates contains control (known) coordinates.

• conf_id is id of configuration which cluster belongs to.
• ccluster is id of cluster which coordinates belongs to.
• indx identifies coordinates within cluster. It has to be positive integer.
• id is point identification.
• x, y and z are coordinates.
• rejected specifies whether observation is rejected (passive) or not. Value 0 stand for not rejected, value 1 for rejected. Default value is 0.

See also Control coordinates.

4.9 Table vectors

Table vectors contains coordinate differences (vectors).

• conf_id is id of configuration which cluster belongs to.
• ccluster is id of cluster which vector belongs to.
• indx identifies vector within cluster. It has to be positive integer.
• from_id is point identification. It identifies initial point.
• to_id is point identification. It identifies terminal point.
• dx, dy and dz are coordinate differences.
• from_dh is value of initial point height. It is optional.
• to_dh is value of terminal point height. It is optional.
• rejected integer default 0 not null,

See also Coordinate differences (vectors).

4.10 Example of local geodetic network in SQL

Providing complete example would be reasonable because of its extent. However, you can obtain example by following these instructions:

Create a file with XML representation of network by copy and paste example from Example of local geodetic network to a new file. Note that file should start with <?xml version="1.0" ?> (no whitespace). Alternatively you can use existing XML file from collection of sample networks (see Download). Then you can convert your XML file (here example_network.xml) to SQL statements by program gama-local-xml2sql (the path depends on your Gama installation).

$ gama-local-xml2sql example_net example_network.xml example_network.sql

Now you have example network (configuration example_net) in the form of SQL INSERT statements in the file example_network.sql.

Another representations you can create and fill SQLite database (for details see Working with SQLite database):

$ sqlite3 examples.db < gama-local-schema.sql
$ sqlite3 examples.db < example_network.sql
$ sqlite3 examples.db

Once you have SQLite database, you can work with it from SQLite command line. You can get nice output by executing following commands.

sqlite> .mode column
sqlite> .nullvalue NULL
sqlite> SELECT * FROM gnu_gama_local_configurations;
sqlite> SELECT * FROM gnu_gama_local_points;
sqlite> SELECT * FROM gnu_gama_local_clusters;
sqlite> SELECT * FROM gnu_gama_local_covmat;
sqlite> SELECT * FROM gnu_gama_local_obs;

Or you can get database dump (CREATE and INSERT statements) by

sqlite> .dump

If it is not enough for you, you can try one of GUI tools for SQLite.

5. Network adjustment with gama-local

Adjustment of local geodetic network is a classical case of adjustment of indirect observations. After estimation of approximate values of unknown parameters (coordinates of points) and linearization of functions describing relations between observations and parameters we solve linear system of equations

(1)      Ax = b + v,

where A is coefficient matrix, b is vector of absolute terms (right hand side) and v is vector of residuals. This system is (generally) overdetermined and we seek the solution x satisfying the basic criterion of Least Squares

(2)      v'Pv = min,

where P is weight matrix. This criterion unambiguously defines the shape of adjusted network.

Geodetic adjustment is traditionally computed as the solution of normal equations (2)

(a)      Nx = n,  where  N=A'PA  and  n=A'Pb.

In the case of free network, i.e. network with no fixed coordinates (or network without sufficient number of fixed coordinates), the system (1) is singular, matrix A has linearly dependent columns, and there is infinite number of solutions x.

To define a unique solution x we need to definine a set of constriant equations (inner constraints)

(b)      Cx = c

to minimize

(c)      v'Pv - 2k'(Cx - c) = min

where r is the vector of residuals, r = Ax - b, k is a vector of so called Lagrange multipliers and adjusted vector x is obtained from solution of

(d)      ( A'PA, C') (x) = (A'Pb)
         ( C,    0 ) (k) = (  c )

In gama-local a slightly different approach is used, we define a second regularization criterion as

(3)      \sum x_i^2 = min,      for all selected i

stating that at the same time with (2) we demand that the sum of squares corrections of selected parameters is minimal (corrections of unknown parameters with indexes from the set of all selected unknowns. Geometrically this criterion is equivalent to adjustment of the network according to (2) with simultaneous transformation to the selected set of fiducial points. This transformation does not change the shape of adjusted network.

Often it is advantageous to work with a homogenized system, ie. with the system of project equations in which coefficient of each row and absolute term are multiplied by square root of the weight of corresponding observation.

(4)      ~A x = ~b,

where ~A = P^1/2 A, ~b = P^1/2 A. Symbol P^1/2 denotes diagonal matrix of square roots of observation weights (or Cholesky decomposition of covariance matrix in the case of correlated observations). To criterion (2) corresponds in the case of homogenized system criterion

(5)      ~v'~v = min.

Normal equations are clearly equivalent for both systems.

5.1 Approximate coordinates

For computation of coefficients in system (1) (ie. during linearization) we need, first of all, an estimate of approximate coordinates of points and approximate values of orientations of observed directions sets.

Approximate values of unknown parameters are usually not known and we have to compute them from the available observations. For approximate value of orientation program gama-local uses median of all estimates from the given set of directions to the points with known coordinates. Median is less sensitive to outliers than arithmetic mean which is normally used for approximate estimate of orientations

During the phase of computation of approximate coordinate of points, program gama-local walks through the list of computed points and for each point gathers all determining elements pointing to points with known or previously computed coordinates. Determining elements are

• outer bearing (oriented half-line) starting from the point with known coordinates and pointing to the computed point

  distance between given and computed points

• inner angle with vertex in the computed point and arms intersecting given points

For all combinations of determining elements program gama-local computes intersections and estimates approximate coordinates as the median of all available solutions.

If at least one point was resolved while iterating through the list, the whole cycle is repeated.

If no more coordinates can be solved using intersections and points with unknown coordinates are remaining, program tries to compute coordinates of unresolved points in a local coordinates system and obtain their coordinates using similarity transformation. If a transformation succeeds to resolve coordinates at least one computed point and there are still some points without coordinates left, the whole process is repeated. Classes for computation of approximate coordinates have been written by Jiri Vesely.

If program gama-local fails to compute approximate coordinates of some of the network points, they are eliminated from the adjustment and they are listed in the output listing.

With the outlined strategy, program gama-local is able to estimate approximate coordinates in most of the cases we normally meet in surveying profession. Still there are cases in which the solution fails. One example is an inserted horizontal traverse with sets of observed direction on both ends but without a connecting observed distance. The solution of approximate coordinates can fail when there is a number of gross error for example resulting from confusion of point identifications but in normal situations, leaving computation of approximate coordinates on program gama-local is recommended.

Example

Computation of approximate coordinates of points
************************************************

Number of points with given coordinates:      2
Number of solved points                :      2
Number of observations                 :      4
-----------------------------------------------------
Successfully solved points             :      0
Remaining unsolved points              :      2


List of unresolved points
*************************
422
424

5.2 Gross absolute terms

One of parameters in XML input of program gama-local is tolerance tol-abs for detecting of gross absolute terms in project equations. Observations with outlying absolute terms are always excluded from adjustment.

For measured distances program tests difference between observed value d_i and distance computed from approximate coordinates d_0

         |d_i - d_0| > tol-abs,

for observed directions program gama-local tests transverse deviation corresponding to absolute term b_i from project equations (1)

         | b_i | d_0 > tol-abs

and similarly for angles, program tests the greater of two deviations corresponding to left and right distances (left and right arm of the angle)

         |b_i| max{ d_{0_l}, d_{0_r} }  > tol-abs.

Default value of parameter tol-abs is 1000 mm.

Example

Outlying absolute terms in project equations
********************************************

   i   standpoint       target           observed     absolute
=========================================== value ===== term ==

   2          103          104 dir.    301.087900       -9989.1


Observations with outlying absolute terms removed

5.3 Parameters of statistical analysis

Program gama-local uses two basic statistical parameters

• confidence probability P (default value is 95%, see input XML parameter conf-pr) and
• actual type of reference standard deviation m0_a (parameter sigma-act).

Confidence probability determines significance level on which statistical tests of adjusted quantities are carried. Actual type of reference standard deviation m0_a specifies whether during statistical analysis we use an a priori reference standard deviation m0 or an a posteriori estimate m0’. On the type of actual reference standard deviation depends the choice of density functions of stochastic quantities in statistical analysis of the adjustment.

• A priori reference standard deviation m0 is an estimate of the standard deviation of an observation with the unit weight. Numerically it is a scaling factor used in calculation of the weights. If we change m0, only the sum of weighted residuals squares is changed and all adjustment results remain the same (there is just one least squares solution). m0 can be selected in cases when we know its value in advance and with sufficient reliability. Another situation when m0 is used are networks with low number of degrees of freedom (poorly overdetermined systems) or when veen degrees of freedom is zero. Examples may be analysis of network models etc.
• A posteri estimate of reference standard deviation m0’ is used in cases when a priori value of reference standard deviation m0 is not known and when degrees of freedom is sufficiently high and reliable for empirical estimate of m0’.

The standard deviantion of an adjusted quantity is computed in dependence of the choice of actual type of reference standard deviation m0_a according to formula

m0_a sqrt(q)

where q is the weight coefficient of the corresponding adjusted unknown parameter or observation. Apart from the standard deviation, program gama-local computes for the adjusted quantity its confidence interval in which its real value is located with the probabilityP.

5.4 Test on the reference standard deviation

Null hypothesis H_0: m0 = m0’ is tested versus alternative hypothesis H_1: m0 neq m0’. Test criterion is ratio of a posteriori estimate of reference standard deviation

         m0' = sqrt( v'P v / r).

and a priori reference standard deviation m0 (input data parameter m0-apr). For given significance level alpha lower and upper bounds of interval (L, U) are computed so, that if hypothesis H_0 is true, probabilities P(m0’/m0 le D) and P(m0’/m0 ge H) are equal to alpha/2. Lower and upper bounds of the interval are computed as

         L = sqrt((Chi^2_{1-alpha/2,r})/r),
         U = sqrt((Chi^2_{ alpha/2 ,r})/r).

Probability

         P(L < m0'/m0 < U) = conf-pr

is by default 95%, this corresponds to 5% confidence level test.

Exceeding the upper limit H of the confidence interval can be caused even by a single gross error (one outlying observation). Method of Least Squares is generally very sensitive to presence of outliers. Safely can be detected only one observation whose elimination leads to maximal decrease of a posteriori estimate of reference standard deviation

(6)      m0''  = sqrt{(v'P v - delta)/(r-1)},
         delta = max(v_i^2/q_vi),

where

(7)      q_vi = 1/p_i - q_Li

is weight coefficient of i-th residual. If the set of observations contains only one gross error, the outlying observation is likely to be detected, but this can not be guaranteed.

In addition, program gama-local computes a posteriori estimate of reference standard deviation separately for horizontal distances and directions and/or angles after formula from

         m0'_t = sqrt(sum{~v^2_it}) / sum{~q_vi}),    t=d,s,

where symbol t denotes observed distances, directions and/or angles.

Example

m0  apriori  :    10.00
m0' empirical:     9.64         [pvv] : 3.43560e+03

During statistical analysis we work

- with empirical standard deviation 9.64
- with confidence level             95 %

Ratio m0' empirical / m0 apriori: 0.964
95 % interval (0.773, 1.227) contains value m0'/m0
m0'/m0 (distances): 0.997   m0'/m0 (directions): 0.943

Maximal decrease of m0''/m0 on elimination of one observation: 0.892

Maximal studentized residual 2.48 exceeds critical value 1.95
on significance level 5 % for observation #35
<distance from="407" to="422" val="346.415" stdev="5.0" />

5.5 Information on points

Program gama-local lists separately review of coordinates of fixed and adjusted points; adjusted constrained coordinates are marked with *; see equation (3). Adjusted coordinate standard deviations m_x and m_y, and values for computing confidence intervals are given in the listing of adjusted coordinates (Parameters of statistical analysis). In the review index i is the index of unknown x_i from the system of project equations (1) corresponding to the point coordinates x and y.

Example

Fixed points
************

       point         x              y
========================================

           1  1054980.484     644498.590
           2  1054933.801     643654.101


Adjusted coordinates
********************

  i        point    approximate  correction  adjusted    std.dev conf.i.
====================== value ====== [m] ====== value ========== [mm] ===

             422
  2            x   1055167.22747  -0.00510 1055167.22237     2.7     5.4
  3            y    644041.46119   0.00023  644041.46142     2.5     5.1

             424
  4            X * 1055205.41198  -0.00056 1055205.41142     3.1     6.3
  5            Y *  644318.24425  -0.00125  644318.24300     3.6     7.2

For adjusted points, program summarizes information on standard ellipses, confidence ellipses, mean square positional errors (m_p), mean coordinate errors (m_xy) and coefficients g characterizing position of approximate coordinates with regard to the confidence ellipse.

Example

Mean errors and parameters of error ellipses
********************************************

  point     mp      mxy      mean error ellipse  conf.err. ellipse   g
========== [mm] == [mm] ==== a [mm] b  alpha[g] ==== a' [mm] b' ========

    422     3.6     2.6     2.7     2.5   187.0     6.8     6.4     0.8
    424     4.7     3.4     3.7     2.9   131.8     9.5     7.4     0.2
    403     5.7     4.0     4.3     3.6    78.9    11.0     9.3     1.1

Mean square positional error m_p and mean coordinate error (m_xy) are computed as

         m_p = sqrt(m_y^2 + m_x^2),    m_xy = m_p / sqrt(2),

where m_y^2 and m_x^2 are squares of standard deviations (variances) of adjusted points coordinates.

Semimajor and semiminor axes of standard ellipse are denoted as a and b in the listing, bearing of semimajor axis is denoted as alpha and they are computed from covariances of adjusted coordinates

         a = sqrt(1/2(cov_yy + cov_xx + c),
         b = sqrt(1/2(cov_yy + cov_xx - c),

         c = sqrt( (cov_xx - cov_yy)^2 + 4(cov_xy)^2 ),

         tan 2alpha = 2(cov_xy) / (cov_xx - cov_yy).

The angle alpha (the bearing of semimajor axis) is measured clockwise from X axis.

Probability that standard ellipse covers real position of a point is relatively low. For this reason program gama-local computes extra confidence ellipse for which the probability of covering real point position is equal to the given confidence probability. Both ellipses are located in the same center, they share the same bearing of semimajor axes and they are similar. For lengths of their semi-axis holds

         a' = k_p a,        b' = k_p b,

where k_p is a coefficient computed for the given probability P as defined in Parameters of statistical analysis.

Position of approximate coordinates of an adjusted point with respect to its confidence ellipse are expressed by a coeeficient g Three cases are possible

• g < 1 approximate coordinates of adjusted point are located inside the confidence ellipse
• g = 1 approximate coordinates of adjusted point are located on the confidence ellipse
• g > 1 approximate coordinates of adjusted point are outside the confidence ellipse

The coefficient g is calculated from formula

         g = sqrt( (a_0 / a')^2 + (b_0/b')^2 )

where

         b_0 = delta_y cos(alpha) - delta_x sin(alpha),
         a_0 = delta_y sin(alpha) - delta_x cos(alpha)

symbol delta is used for correction of approximate coordinates and alpha is bearing of confidence ellipse semimajor axis.

If network contains sets of observed directions, program writes information on corresponding adjusted orientations, standard deviations and confidence intervals. Index i is the same as in the case of adjusted coordinates the index of i-th adjusted unknown in the project equations.

Example

Adjusted bearings
*****************

  i   standpoint   approximate  correction  adjusted   std.dev conf.i.
==================== value [g] ==== [g] === value [g] ======= [cc] ===

  1            1    296.484371  -0.000917  296.483454      5.1    10.3
 10            2     96.484371   0.000708   96.485079      5.1    10.4
 21          403     20.850571  -0.001953   20.848618      8.8    17.7

5.6 Adjusted observations and residuals

In the review of adjusted observations program gama-local prints index of the observation, index of the row in matrix A in the system (1), identifications of standpoint and target point, type of the observation, its approximate and adjusted value, standard deviation and confidence interval.

Example

Adjusted observations
*********************

   i   standpoint   target         observed     adjusted std.dev conf.i.
===================================== value ==== [m|g] ====== [mm|cc] ==

   1            1        2 dis.   845.77700    845.77907     3.0     6.1
   2                   422 dir.   28.205700    28.205613     5.1    10.3
   3                   424 dir.   60.490600    60.491359     6.7    13.6

Review of residuals serves for analysis of observations and containts values of normalized or studentized residuals (depending on type of m0_a used) and three characteristics. Theese are coefficient f identifying weak network elements and estimates of real error of observation e-obs and real error of its adjusted value e-adj, see definition in the following text.

If normalized or studentized residual exceeds critical value for the given confidence probability, it is marked in the review with symbol c (critical) and maximal normalized or studentized residual is marked with symbol m.

Example

Residuals and analysis of observations
**************************************

   i standpoint   target        f[%]        v    |v'|     e-obs.  e-adj.
======================================== [mm|cc] =========== [mm|cc] ===

   1          1        2 dir.   47.4       9.170  1.1      12.7    3.5
   2                 422 dir.   47.0      -0.873  0.1      -1.2   -0.3
   3                 424 dir.   30.3       7.588  1.1      14.8    7.2

5.7 Identification of weak network elements

When planning observations in a geodetic network we always try to guarantee that all observed elements are checked by other measurements. Only with redundant measurements it is possible to adjust observations and possibly remove blunders that might otherwise totaly corrupt the whole set of measurements. Apart from sufficient number of redundant observations the degree of control of single observed elements is given by the network configuration, ie. its geometry.

Less controlled observations represent weak network elements and they can in extreme cases even disable detection of gross observational errors as it is in the case of uncontrolled observations. There are two limit cases of observation control

• fully controlled observation as is for example an observed distance between two fixed points (standard deviation of the adjusted element is zero; standard deviation of the residual equals to the standard deviation if the observation) and
• uncontrolled observations as is a free polar bar for example (standard deviation of adjusted value is equal to standard deviation of observed quantity; residual and standard deviation of the residual are zero).

Weakly controlled or uncontrolled observations can result even from elimination of certain suspisios observations during analysis of adjusment.

Standard deviation of adjusted observations is less than standard deviation of the measurement. Degree of observation control in network is defined as coefficient

(8)      f = 100 (m_l - m_L)/m_l,

where m_l is standard deviation of observed quantity and m_L is standard deviation computed from a posteriori reference standard deviation m0. We consider observed network element to be

• uncontrolled if f < 0.1 (in listing marked with letter u),
• weakly controlled if 0.1 le f < 5 (in listing marked with letter w).

5.8 Estimation of real errors

Acording to previous section we can consider an observation to be controlled if its coefficient f > 0.1. Any controlled observation can be eliminated from the network without corrupting the network consistency—network reduced by one controlled observation can be adjusted and all unknown parameters can be compute without the eliminated observation.

Estimate of real error of i-th observation is defined as

(9)      e_li = L^red_i - l_i,

where e_li is value of i-th observation and is value of i-th network element computed from adjusted coordinates and/or orientations of the reduced network. Similarly is defined the estimate of real error of a residual

(10)     e_vi = L^red_i - L_l.

Adjustment results are the best statistical estimate of unknown parameters that we have. This holds true even for adjustment of reduced network which is not influenced by real error of i-th observation. On favourable occasions differences (9) and (10) can help to detect blunders but to interpret these estimates as real errors is possible only with substantial exaggeration. These estimates fail when there are more than one significant observational error. Generally holds tha the weaker the element is controlled in netowrk the less reliable these estimates are.

Estimate of real error of an observation computes program gama-local as

         e_li = v_i/(p_i q_vi)

and estimate of real error of a residual as

         e_vi = e_li - v_i.

5.9 Test on linearization

Mathematical model of geodetic network adjustment in gama-local is defined as a set of known real-valued differentiable functions

(11)      L^* = f(X^*)

where L^* is a vector of theoretical correct observations and X^* is a vector of correct values of parameters. For the given sample set of observations L and the unknown vector of residuals v we can express the estimate of parameters X as a nonlinear set of equations

(12)      L + v = f(X).

With approximate values X_0 of unknown parameters

(12)      X = X_0 + x

we can linearize the equations (12)

          L + v = f(X_0) + f'(X_0)x.

yielding the linear set of equations (1)

Unknown parameters in gama-local mathematical model are points coordinates and orientation angles (transforming observed directions to bearings). The observables described by functions (12) belong into two classes

• linear observables: horizontal and slope distances, height differences, control coordinates and vectors (coordinate differences),
• angular observables: directions, horizontal and zenith angles.

Internally in gama-local unknown corrections to linear observables are computed in millimeters and corrections to angular observables in centigrade seconds. To reflect the internal units in used all partial derivatives of angular observables by coordinates are scaled by factor 2000/pi.

When computing coefficients of project equations (1) we expect that approximate coordinates of points are known with sufficient accuracy needed for linearization of generally nonlinear relations between observations and unknown paramters. Most often this is true but not always and generally we have to check how close our approximation is to adjusted parameters.

Generally we check linearization in adjustment by double calculation of residuals

         v^I  = Ax - b,
         v^II = ~l(~x) - l,

Program gama-local similarly computes and tests differences in values of adjusted observations once computed from residuals and once from adjusted coordinates. For measured directions and angles gama-local computes in addition transverse deviation corresponding to computed angle difference in the distance of target point (or the farther of two targets for angle). As a criterion of bad linearization is supposed positional deviation greater or equal to 0.0005 millimetres.

Example

Test of linearization error
***************************

Diffs in adj. obs from residuals and from adjusted coordinates
**************************************************************

 i standpoint     target          observed     r        difference
=================================   value  = [mm|cc] = [cc] == [mm]=

 2 3022184030 3022724008 dist.   28.39200    -7.070          -0.003
 3            3022724002 dist.   72.30700   -18.815          -0.001
 7            3000001063 dir.  286.305200    11.272  -0.002  -0.001
 8            3022724008 dir.  357.800600   -23.947   0.037   0.002

From the practical point of view it might seem that the tolerance 0.0005 mm for detecting poor linearization is too strict. Its exceeding in program gama-local results in repeated adjustment with substitute adjusted coordinates for approximate. Given tolerance was chosen so strict to guarantee that listed output results would never be influenced by linearization and could serve for verification and testing of numerical solutions produced by other programs.

Iterated adjustement with successive improvement of approximate unknown coordinates converges usually even for gross errors in initial estimates of unknown coordinates. If the influence of linearization is detected after adjustment, typically only one iteration is sufficient for recovering.

For any automatically controlled iteration we have to set up certain stopping criterion independent on the convergence and results obtained. Program gama-local computes iterated adjustment three times at maximum. If the bad linearization is detected even after three readjustments it signals that given network configuration is somehow suspicious.

5.10 Glossary

Symbols and names used in adjustment statistics.

6. Data structures and algorithms

6.1 Observation data and points

The Gama observation data structures are designed to enable adjustment of any combination of possibly correlated observations. At its very early stage Gama was limited to adjustment of uncorrelated observations. Only directions and distances were available and observable’s weight was stored together with the observed value in a single object. A single array of pointers to observation objects was sufficient for handling all observations. So called orientation shifts corresponding to directions measured form a point were stored together with coordinations in point objects.

To enable adjustment of possibly correlated observations (like angles derived from observed directions or already adjusted coordinates from a previous adjustment) Gama has come with the concept of clusters. Cluster is an object with a common variance-covariance matrix and a list of pointers to observation objects (distances, directions, angles, etc.). Weights were removed from observation objects and replaced with a pointer to the cluster to which the observation belong. All clusters are joined in a common object ObservationData; similarly to observations, each cluster contains a pointer to its parent Observation Data object. Orientation shifts were separated from coordinates and are stored in the cluster containing the bunch of directions and thus number of orientations is not limited to one for a point.

This organisation of observational information has proved to be effective. Template classes ObservationData and Cluster are used as base classes both in gama-local and gama-g3

template <typename Observation>
  class ObservationData
  {
  public:    
    ClusterList<Observation>  CL;
    
    ObservationData();
    ObservationData(const ObservationData& cod);
    ~ObservationData();
    
    ObservationData& operator=(const ObservationData& cod);   
    template <typename P> void for_each(const P& p) const;
  };

template <typename Observation>  
  class Cluster 
  {
  public:
    const ObservationData<Observation>*     observation_data;
    ObservationList<Observation>            observation_list;
    typename Observation::CovarianceMatrix  covariance_matrix;  
    
    Cluster(const ObservationData<Observation>* od);
    virtual ~Cluster();
    
    virtual Cluster* clone(const ObservationData<Observation>*) const = 0;
    double stdDev(int i) const;
    int size() const;
    void update();
    int  activeCount() const;
    typename Observation::CovarianceMatrix activeCov() const; 
  };

The following template class PointBase for handling point information is used in gama-g3. The template class PointBase relies internally on std::map container but comes with its own interface (in gama-local std::map was used directly for storing points).

template <typename Point>
  class PointBase
  {
    typedef std::map<typename Point::Name, Point*>  Points;

  public:    
    PointBase();
    PointBase(const PointBase& cod);
    ~PointBase();
    
    PointBase& operator=(const PointBase& cod);
    void put(const Point&);
    void put(Point*);
    Point*       find(const typename Point::Name&);
    const Point* find(const typename Point::Name&) const;
    void erase(const typename Point::Name&);
    void erase();
    
    class const_iterator;
    const_iterator  begin();
    const_iterator  end  ();

    class iterator;
    iterator  begin();
    iterator  end  ();
  };

Template classes ObservationData and PointBase are defined in namespace GNU_gama and are located in the source directory gnu_gama.

6.2 Supported ellipsoids

6.3 Transformation from spatial to geographical coordinates

Spatial coordinates (X, Y, Z) can be easily computed from geographical ellipsoidal coordinates (B, L, H), where B is geographical latitude, L geographical longitude and H is elliposidal height, as

X = (N + H) cos B cos L
Y = (N + H) cos B sin L
Z = (N(1-e^2) + H)sin B

where N = a/sqrt(1 - e^2 sin^2 B) is the radius of curvature in the prime vertical, e^2 = (a^2 - b^2)/a^2 is the first eccentricity for the given rotational ellipsoid (spheroid) with semi-major axis a and semi-minor axis b.

In the case of coordiante transformation from (X, Y, Z) to (B, L, H), the longitude is given by the formula

tan L = Y / X.

Now we can introduce

D = sqrt(X^2 + Y^2),

so that the cartesian system become (D, Z). Coordinates B and H are then usually computed by iteration with some starting value of B_0, for example

tan B_0 = Z/D/(1 - e^2),

tan B = Z/D + N/(N+H) e^2 tan B,   H  = D / cos B = Z / sin B - N(1-e^2)

B. R. Bowring described a closed formula(3) that is more effective and sufficiantly accurate and that is used in GNU Gama.

The centre of curvature C of the spheroid corresponding to P’ is the point

(e^2 a cos^3 u, -e’^2 b sin^3 u)),

where e’^2 = (a^2 - b^2)/b^2 is second eccentricity and u is the parametric latitude of the point P’, (1-e^2)N sin B = b sin u. Therefore

tan B = (Z + e’^2 b sin^3 u) / (D - e^2 a cos^3 u).

This is clearly an iterative solution; but it has been found that this formula is extremely accurate using the single first approximation for u for the tan u = (Z/D)(a/b). Maximum error in earth bound region is 3e-8 of sexagesimal arc seconds (5e-7 millimetres); maximum is 0.0018” (0.1 millimetres) at height H = 2a.

6.4 Class g3::Model

g3::model documentation shall come here ...

namespace GNU_gama {  namespace g3 {

  
  class Model {
  public:
    
    typedef GNU_gama::PointBase<g3::Point>              PointBase;
    typedef GNU_gama::ObservationData<g3::Observation>  ObservationData;
    
    PointBase           *points;
    ObservationData     *obs;
    
    GNU_gama::Ellipsoid  ellipsoid;


    Model();
    ~Model();

    Point* get_point(const Point::Name&);
    void   write_xml(std::ostream& out) const;
    void   pre_linearization();
}}

7. Gama-local companion tools

With gama-local come several companion command line tools, most of them being conversion programs for various data formats.

7.1 gama-local-deformation

Program gama-local-deformation reads XML adjustment results files from two dates (epochs), compute differences for adjusted points common in both epochs, calculate the covariance matrix of the differences and optionally renders the deformation diagram in SVG output file.

Usage: gama-local-deformation epoch1.xml epoch2.xml [--text file] [--svg file]
       gama-local-deformation --version
       gama-local-deformation --help

Options:

epoch1 and epoch2 are adjustment results in XML format of the surveying network.
           The program computes the shift vectors of common adjusted points
           and their corresponding covariance matrix.

--text     deformation analyses in textual format. If missing, standard
           output device is used (i.e. screen).
--svg      if defined, the program writes SVG image of the second epoch
           adjustment with standard deviation ellipses and points' shits.
           The network schema is available only in 2D (xy coordinates only).
--version
--help

Report bugs to: <[email protected]>
GNU gama home page: <https://www.gnu.org/software/gama/>
General help using GNU software: <https://www.gnu.org/gethelp/>

7.2 gama-local-gkf2yaml

Program gama-local-gkf2yaml converts input XML format of gama-local (in Gama project usually denoted with extension gkf) to yaml format.

gama-local-gkf2yaml input.gkf [output.yaml]

7.3 gama-local-yaml2gkf

Program gama-local-yaml2gkf converts YAML input to XML imput format.

gama-local-yaml2gkf input.yaml  [ output.gkf ]

7.4 gama-local-xml2sql

Program gama-local-xml2sql converts gama-local XML input format (aka gkf) to SQL script.

Usage: gama-local-xml2sql configuration (xml_input|-) [sql_output|-]

Convert XML adjustment input of gama-local to SQL

7.5 gama-local-xml2txt

Conversion from adjustment XML output to text format.

Usage: gama-local-xml2txt [options] < std_input > std_output

Convert XML adjustment output of gama-local to text format

Options:

--angles     400 | 360
--language   en | ca | cz | du | fi | fr | hu | ru | ua 
--encoding   utf-8 | iso-8859-2 | iso-8859-2-flat | cp-1250 | cp-1251
--help

7.6 krumm2gama-local

GNU Gama sources come with an extensive set of testing data examples in the directory tests where subdirectory tests/krumm contains examples from the book by Friedhelm Krumm, Geodetic Network Adjustment Examples, Geodätisches Institut Universität Stuttgart, https://www.gis.uni-stuttgart.de, Rev. 3.5 January 20, 2020. All these examples are distributed with GNU Gama with permission from the author.

Conversion program krumm2gama-local converts the examples data format defined in the book to the gama-local XML input format. For more details read the file tests/krumm/input.README.md.

Conversion from data format used in Geodetic Network Adjustment Examples
by Friedhelm Krumm to XML input format of gama-local (GNU Gama)
https://www.gis.uni-stuttgart.de/lehre/campus-docs/adjustment_examples.pdf

     krumm2gama-local  input_file  [ output_file  ]
     krumm2gama-local < std_input  [ > std_output ]

Options:
-h, --help      this text
-v, --version   print program version
-e, --examples  add the following comment to the generated XML file

     This example is based on published material Geodetic Network Adjustment
     Examples by Friedhelm Krumm, Geodätisches Institut Universität Stuttgart,
     Rev. 3.5, January 20, 2020

8. Gama-local test suite

GNU Gama comes with a set of tests that provides gama-local test suite. To run the test suite, go to the top-level Gama directory and type

$ make check

You should see the names of the test suite files as they are processed, any other output indicates some problem. The output might be for example this

Entering directory 'gama/tests/gama-local'
PASS: gama-local-version.sh
PASS: gama-local-adjustment.sh
PASS: gama-local-algorithms.sh
PASS: gama-local-xml-xml.sh
PASS: gama-local-html.sh
PASS: gama-local-equivalents.sh
PASS: gama-local-xml-results.sh
PASS: gama-local-parameters.sh
PASS: gama-local-export.sh
PASS: gama-local-sqlite-reader.sh
PASS: xmllint-gama-local-xsd.sh
PASS: xmllint-gama-local-adjustment-xsd.sh
========================================================================
Testsuite summary for gama 2.29
========================================================================
# TOTAL: 12
# PASS:  12
# SKIP:  0
# XFAIL: 0
# FAIL:  0
# XPASS: 0
# ERROR: 0
========================================================================

Number of tests vary according to the configuration of your system. Tests that are always present are

gama-local-version
gama-local-adjustment
gama-local-algorithms
gama-local-xml-xml
gama-local-html
gama-local-equivalents
gama-local-xml-results
gama-local-parameters
gama-local-export

Optional tests are

gama-local-sqlite-reader
xmllint-gama-local-xsd
xmllint-gama-local-adjustment-xsd

which are included only if sqlite3 database support libraries and/or xmllint program are installed.

You can also request more extra test configuring the project as

./configure --enable-extra-tests

but be prepared that these extra test might take some time to finish.

8.1 Internal organisation

Gama-local tests are implemented as shell scripts that are stored in gama/tests/gama-local directory. The scripts are generated from corresponding .in files which are stored in gama/tests/gama-local/script directory where are also stored helper C++ programs called by the testing suite scripts. Generating scripts and the build of helper programs is controlled from gama/tests/gama-local/Makefile.am, where a list of testing data files is also defined.

In gama/tests/gama-local directory are also stored detail .log files for all tests together with corresponging .trs (as in Test ReSults) files.

All files generated by the test suite are stored in gama/tests/gama-local/script/2.29 (thus generated files from different versions are not overwritten).

To run selected test individually, go to the directory gama/tests/gama-local and start the test manually

$ cd gama/tests/gama-local
$ ./test-name

A. Copying This Manual

A.1 GNU Free Documentation License

Version 1.1, March 2000

Copyright © 2000 Free Software Foundation, Inc.
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Everyone is permitted to copy and distribute verbatim copies
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Concept Index

Footnotes

(1)

Wikipedia, http://en.wikipedia.org/wiki/Surveying

(2)

gama-local can solve the project equations (1) directly using algorithms Gram-Schmidt orthogonalisation or Singular Value Decomposition, which generally yield numerically more stable solution.

(3)

B. R. Bowring: Transformation from spatial to geographical coordinates, Survey Review XXIII, 181, July 1976

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