two dimensional network adjustment and...

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TWO DIMENSIONAL NETWORK ADJUSTMENT AND

DEFORMATION ANALYSIS VIA MATLAB

Roya Olyazadeh

A thesis submitted in fulfillment of the requirements for the award of the

degree of Master of (Geomatic Engineering)

Faculty of Geoinformation Science and Engineering

Universiti Teknologi Malaysia

JULY 2010

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To my beloved mother and father

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AKNOWLEDGMENT

First and foremost, I would like deeply to thank to my supervisor of this

project, Professor Dr. Halim Setan for the valuable guidance and advice. He inspired

me greatly to work in this project. His willingness to motivate me contributed

tremendously to my project. I also would like to thank him for showing me some

examples that related to the topic of my project.

Besides, I would like to thank the authority of University Technology

Malaysia (UTM) for providing me with a good environment and facilities to

complete this project. Thanks and appreciation to the helpful people at Mathworks

community to handle programming difficulties via MATLAB specially Mr.Walter

Roberson.

Finally, an honorable mention goes to my families and friends for their

understandings and supports on me in completing this project specially my parents

and my friends. For all the people who helped me a lot, thank you very much and

may god bless you all. Without helps of the particular that mentioned above, I would

face many difficulties while doing this project. And it would not be successful

without God who guides me in my everyday life and activities; I thank him for the

good health he has given to me, and for the success of my study.

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ABSTRACT

Network adjustment and deformation monitoring are one of the main

activities of engineering surveying. Geodetic networks are estimated by the method

of least-squares estimation (LSE) adjustment and the ‘goodness’ of the network is

measured by a precision analysis based upon the covariance matrix of the estimated

parameters. When such a network is designed, global test and local test are assessed

to test compatibility of variance factor via two-tailed chi-square distribution and

residual of measurements to detect gross error by using a technique pioneered by the

geodesist Baarda. The second step is Deformation detection. Generally, the

deformation computations can be divided into geotechnical and geodetic methods.

There are two types of geodetic networks, namely the absolute and relative networks.

In the absolute network, some of the points are assumed to be located out of the

deformable body. However, in a relative network, all points are assumed to be

located on the deformable body. This study focuses on two dimension (2-D) absolute

geodetic deformation detection via MATLAB7. Deformation analysis can be handled

by several techniques such as Robust (IWST and LAS), Congruency, Bayesian

method and etc. This study presents a deformation analysis procedure via geodetic

methods that consists of LSE of individual epochs, trend analysis of the displacement

field and the deformation detection by IWST between epochs. This research focuses

on the development of two programs in MATLAB7 for network adjustment

(distance, angle and azimuth observation respectively) and deformation detection

between two epochs. In this project, first LSE adjustment is done for each epoch

and creates the appropriate input files for deformation program. Next, deformation

program reads them and creates an output file and displays a graphic consists of error

ellipse for each stations and displacement vector for moved stations. There are three

data sets to run these two programs. For adjustment part the results are compared

with STARNET results and for deformation part the results are compared with

previous works by Caspary (1987), Ranjit(1999) and Khairulnizam(2004).The results

show that these two programs work and there are not significant difference between

these results and results from other works.

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ABSTRAK

Pelarasan jaringan dan pengawasan deformasi merupakan salah satu kegiatan

utama dalam ukur kejuruteraan. Jaringan geodetik dianggarkan dengan kaedah

pelarasan kuasa dua terkecil (LSE) dan kualiti jaringan diterbitkan berdasarkan

analisis daripada matriks kovarians bagi setiap parameter terlaras. Apabila jaringan

tersebut direka, ujian global dan ujian lokal dijalankan untuk menguji keserasian

faktor varians melalui taburan dua hujung khi kuasa dua dan sisa pengukuran untuk

mengesan selisih kasar dengan menggunakan teknik yang dipelopori oleh penyelidik

Baarda. Langkah kedua adalah pengesanan deformasi. Secara umum, perhitungan

deformasi boleh dibahagikan kepada kaedah geoteknik dan geodetik. Terdapat dua

jenis jaringan geodetik iaitu jaringan absolut dan relatif. Dalam jaringan absolut,

beberapa titik kawalan diandaikan terletak diluar jasad tercanggakan. Namun, dalam

jaringan relatif, semua titik kawalan diandaikan terletak dalam jasad

tercanggakan. Kajian ini menumpu pada pengesanan deformasi dua dimensi (2D)

geodetik absolut melalui MATLAB7. Analisa deformasi dapat diterbitkan oleh

beberapa teknik seperti kaedah Robust (IWST dan LAS), Congruency, Bayesian dan

lain-lain. Kajian ini menbentangkan prosidur analisis deformasi melalui kaedah

geodetik yang terdiri daripada LSE bagi setiap epok, analisis trens tentang magnitud

anjakan dan pengesanan deformasi oleh IWST antara epok. Kajian ini berfokus pada

pembangunan dua program dalam MATLAB7 untuk pelarasan jaringan (cerapan

jarak, sudut dan azimut masing-masing) dan pengesanan deformasi antara dua

epok. Dalam projek ini, pelarasan LSE dilakukan terlebih dahulu untuk setiap epok

dan menerbitkan fail input yang sesuai untuk program deformasi. Selanjutnya,

program deformasi membaca fail input yang diterbitkan dan menghasilkan output

fail serta memaparkan grafik yang terdiri daripada selisih elips bagi setiap stesen dan

vektor anjakan bagi stesen yang telah berganjak. Terdapat tiga dataset dihitung

dengan kedua-dua program tersebut. Untuk bahagian pelarasan, hasil dibandingkan

dengan keputusan STARNET dan untuk bahagian deformasi pula hasil dibandingkan

dengan kerja sebelumnya oleh Caspary (1987), Ranjit (1999) dan Khairulnizam

(2004). Kesimpulannya, kajian ini menunjukkan bahawa kedua-dua program

berfungsi dan hasil yang didapati tidak banyak perbezaan berbanding dengan kerja

sebelumnya.

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CHAPTER ONE

INTRODUCTION

1.1 Background

Deformation measurements are one of the most important activities of

engineering surveying. Deformation analysis is one of the main research fields in

geodesy and geomatic. Deformation analysis process comprises of measurement and

analysis phases. Measurements can be collected using several techniques such as

Total station, GPS, Laser scanner, Photogrammetry or combined techniques. The

output of the evaluation of the measurements is mainly point positions. In the

deformation analysis phase, the coordinate changes in the point positions are

investigated.

Generally, the deformation measurement techniques can be divided into

geotechnical, structural and geodetic methods. In the geodetic method there are two

basic types of geodetic monitoring networks; namely the reference (absolute) and

relative networks (Chrzanowski et al., 1986). In a reference network, some of the

points or stations are assumed to be located outside of the deformable body or object,

thus serving as reference points for the determination of the absolute displacements

of the object points. However, in a relative network, all surveyed points are assumed

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to be located on the deformable body (Setan and Singh, 2001). In this study 2D

absolute geodetic deformation is considered.

1.2 Problem Statement

The results of deformation measurements are related to direct safety of

engineering structures and human life. To avoid a wrong interpretation of

displacements, an appropriate deformation monitoring network must be established

and the data obtained from deformation monitoring network must be carefully

evaluated. Deformation measurements and analysis require the use of very accurate

surveying equipment and analysis methods (Setan and Singh, 1999). Therefore,

deformation detection and network analysis is very important to represent movement

of subjects.

There are several known adjustment and deformation system software

packages, from different university research group like ADJUST4.6 (Ghilani, 2006),

also commercial software like STARNET (Starplus Software, 2000), GEOLAB

(Micro Search, 1985) and PANDA (GeoTec GmbH, 2004). Specialized computer

programming is required because most commercial software like STARNET does

not provide the required data for deformation detection. And some of them are not

easy to use. This research focuses on the development of a program via MATLAB7.

MATLAB is a mathematical computer programming that covers all mathematical

functions are required in surveying and this special subject, deformation. So in this

work MATLAB programming is developed for network adjustment and (distance,

angle and azimuth observation respectively) deformation detection where

Adjustment program can create required data for deformation detection. These

programs are not as powerful as other software and especially commercial software.

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1.3 Aim and objective of the study

The purpose of this work is to monitor and analyze the displacements of

deformation for 2D network IWST (Iterative Weighted Similarity Transformation)

robust method after network adjustment. Robust method is used when there is no

previous information about the movement of points within the network (Singh &

Setan 1999). IWST, developed by Chen (1983) in the New Brunswick University, is

known as the robust method.

The secondary goal is to program via MATLAB and determine whether this

program can be converted to executable (EXE) file by using MATLAB compiler.

Consequently the specific purposes of this work are:

1. Network Adjustment

2. Deformation Analysis

3. MATLAB Programming

1.4 Significance of the study

The results of deformation measurements are related to direct safety of

engineering structures and Human life. To avoid a wrong interpretation of

displacements, an appropriate deformation monitoring network must be established

and the data obtained from deformation monitoring network must be carefully

evaluated. Deformation measurements and analysis require the use of very accurate

surveying equipment and analysis methods. This project is only limited to 2D

network adjustment and 2D deformation detection for distance, angle and azimuth

observations.

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1.5 Research Scope

The research scope covers the limits of the research. In this project the limits

are as follows;

The research area covers a real network with 6 stations and 4 stable stations.

For network adjustment and deformation detection, MATLAB programming is

carried out, while this program is objected to do all 2D network adjustments and

deformations with distance and angle and azimuth. Another example have been used

to test, is a known data of a dam monitoring network, taken from Caspary (1987)

with 12 stations and 7 stable stations. The third data set is 12 stations with distance

and azimuth observation (Setan, Abidin Md Som and M.Idris, 2003).

1.6 Research Methodology

Several methods or approaches can be employed for deformation analysis like

The robust analysis of deformation (Caspary, 1987) ,The Generalized approach

(Chen UNB, 1986) , The integrated analysis (Teskey, 1988) ,The Grey theory (Chen

HK) ,The robustness analysis (Vanicek).This study will be focused on robust method

( IWST) via MATLAB. Robust method was made using both an Iterative Weighted

Similarity Transformation (IWST) and the Least Absolute Sum (LAS) method.

The commonly adopted methods for monitoring deformation by geodetic

methods are based on the repeated observation of a survey monitoring network at

difference epochs (Caspary, 1987), followed by two-step analysis (i.e. independent

least squares estimation (LSE) or adjustment of single epoch, and deformation

detection between epochs). The detection of deformation uses two-epoch analysis, an

absolute monitoring network and a static model to compare the coordinate between

the epochs (Setan, 1997).

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Deformation analysis using the geodetic method mainly consists of these

steps analysis (Setan and Singh, 2001):

1. pre-analysis

2. data acquisition

3. The network least squares adjustment

4. Trend analysis

5. Deformation analysis

Figure 1.1 Flowchart of the research methodology

1. Literature review stage

The literature review is to explore the 2D network adjustment computation and

deformation analysis methodology referring to Internet, books or journal paper.

LITERATURE REVIEW

Choose one method for Deformation

Robust Method (IWST)

Program via MATLAB for Adjustment (LSE)

Check results with STARNET

Program via MATLAB for

Deformation analysis (IWST)

Two Epoch Analysis Deformation

To check if MATLAB can compile to an Executable file

Does MATLAB can convert .m file

to a web page? Web Server

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2. Planning stage

The planning stage is where preparation is done prior to research

implementation. This stage consists of selection for deformation detection

methodology as well as adjustment computation, MATLAB programming practice

and learning how to use compiler in MATLAB and to launch program in a web

server by learning Java or .Net.

3. Implementation stage

This stage involves what is done in order to obtain the final output for

deformation detection. The process is; Input data, processing via MATLAB and

output file for deformation and adjustment and graphic display.

First input data (approximate coordinates and observation) can be read by

MATLAB, and then programming for this network is performed. Finally results are

saved in text file and graphics display in a plot.

4. Results and analysis stage

After implementation stage, the final results are produced from adjustment

program and deformation program which analysis is made for further decisions and

conclusion as well as future work.

5. Conclusion and recommendation stage

The final outcome of the entire process in this thesis is concluded, from which

necessary recommendations are made based on the outcome.

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1.7 Thesis Outline

The thesis is in six chapters as detailed below:

Chapter one: Introduce the research topic, the background of the study, problem

statement, research objective, scope and methodology.

Chapter two: This chapter covers literature review which is to explore methodology

for adjustment and deformation and software packages that can perform these

analyses.

Chapter three: This chapter provides the methodology of this study. The steps

include; data input, processing stage and output.

Chapter four: This chapter discusses implementations of this research. The steps

include; how text file can be read by MATLAB, processing and iterations, M file to

function and how to make an executable file by compiler and launch it to web server.

Chapter five: This chapter discusses the results and analysis of this study from

which necessary conclusion and recommendation will be made.

Chapter six: In this chapter, conclusions and recommendation for future study are

discussed.

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LIST OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION II

DEDICATION III

ACKNOWLEDGEMENTS IV

ABSTRACT V

ABSTRAK VI

TABLE OF CONTENTS VII

LIST OF TABLES XI

LIST OF FIGURES XIV

LIST OF APPENDICES XVII

1 INTRODUCTION 1

1.1 Background 1

1.2 Problem Statement 2

1.3 Aim and objective of the study 3

1.4 Significance of the study 3

1.5 Research Scope 4

1.6 Research methodology 4

1.7 Thesis outline 7

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2 LITERATURE REVIEW 8

2.1 Deformation definition 8

2.2 Deformation analysis 9

2.2.1 The network adjustment computation 10

2.2.2 Adjustment programming 12

2.2.2.1 STARNET 12

2.2.2.2 GEOLAB 14

2.2.2.3 MOVE3 15

2.2.2.4 ADJUST4.6 17

2.2.3 Deformation methodology 17

2.2.3.1 Robust Method 18

2.2.3.2 Congruency Method 19

2.2.3.3 Deformation Modeling 20

2.3 Deformation Monitoring System software packages 21

2.3.1 DETECT 22

2.3.2 GPSAD2000/DEFORM99 23

2.3.2.1 DEFORM99 23

2.3.2.2 GPSAD2000 24

2.3.3 PANDA 25

2.3.4 LOCATA 27

2.3.5 DIMONS 28

3 RESEARCH METHODOLOGY 29

3.1 Introduction 29

3.2 Network Adjustment 30

3.2.1 LSE 31

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3.2.2 Global test and local test 34

3.2.3 Error Ellipses 36

3.3 Deformation Analysis 38

3.3.1 Datum Defect 40

3.3.2 S-transformation 41

3.3.3 Initial checking of data and test on Variance Ratio 42

3.3.4 Trend analysis 43

3.3.5 Robust Method (IWST) 43

3.3.6 Final S-transformation 45

4 IMPLEMENTATION 46

4.1 Introduction 46

4.2 Data Input 46

4.2.1 Adjustment File 47

4.2.2 Deformation File 47

4.3 MATLAB Procedure 48

4.3.1 Reading text in MATLAB 50

4.3.2 SYMS and SUBS in MATLAB 52

4.3.3 Rearranging Matrixes in MATLAB 53

4.3.4 Chi-Square and F distribution in MATLAB 55

4.3.5 Plot Error Ellipse and displacement vector 58

4.4 Script M-file to Function M-file 59

4.5 Creating Graphical User Interfaces (GUIDE) Features 61

4.6 Stand Alone Executable file for M file 64

4.7 MATLAB Web Server 69

5 DISCUSSION AND RESULT 71

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5.1 Introduction 71

5.2 Adjustment Results 71

5.2.1 LSE Results for data set one 72

5.2.1.1 Data set one,Epoch1 73

5.2.1.2 Data set one,Epoch2 75

5.2.2 LSE Results for data set two 78

5.2.2.1 Data set two,Epoch1 79

5.2.2.2 Data set two,Epoch1 82

5.2.3 LSE Results for data set three 85

5.2.3.1 Data set three,Epoch1 86

5.2.3.2 Data set three,Epoch2 89

5.3 Deformation Results 92

5.3.1 Data set one 92

5.3.2 Data set two 95

5.3.3 Data set three 99

6 CONCLUSION AND RECOMMENDATION 103

6.1 Introduction 103

6.2 Conclusion 103

6.3 Recommendation 104

REFERENCES 106

Appendices A – C 111-135

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LIST OF TABLES

TABLE NO. TITLE PAGE

3.1 Confidence region ellipses 37

5.1 Approximate Coordinates for data set one 72

5.2 Observations for data set one epoch 1 73

5.3 Comparison results of LSE between Adjustment Program,

STARNET and program by Singh R. 74

5.4 Coordinates comparison of first epoch between Adjustment

program and STARNET 75

5.5 Error Ellipse comparison of first epoch between Adjustment


5.6 Observations for data set one epoch 76

5.7 Comparison results of LSE between Adjustment program,

STARNET and program by Singh R. 77

5.8 Coordinates comparison of second epoch between

Adjustment program and STARNET 77

5.9 Error Ellipse comparison of second epoch between Adjustment


5.10 Approximate coordinates for data set two 78

5.11 Observations for data set two epoch one 79

5.12 Comparison results of LSE between Adjustment program

and STARNET 80

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5.15 Observations for data set two epoch two 82


and STARNET 83

5.17 Coordinates comparison of second epoch between Adjustment


5.18 Error Ellipse comparison of second epoch between Adjustment


5.19 Approximate coordinates for data set Three 85

5.20 Observations for data set three epoch one 86


and STARNET 87





5.24 Observations for data set three epoch two 89


and STARNET 90

5.26 Coordinates comparison of second epoch between


5.27 Error Ellipse comparison of second epoch between


5.28 Deformation results of data set one for Deformation

program vs. program by Singh R. 93

5.29 Displacement vector and single point test for data set one

for Deformation program and Program by Singh R. 95

5.30 Difference in displacement vector and single point test for

data set one for Deformation program and Program by Singh R. 95

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5.31 Deformation results of data set two for Deformation

program vs. Caspary 96

5.32 Displacement vector and single point test for data set two

for Deformation program and Caspary(mm) 98

5.33 Difference in displacement vector (Delta Disp.) for data set two

between Deformation program and Caspary 98

5.34 Deformation results of data set three for Deformation

program vs. Program by Khairulnizam 99

5.35 Displacement vector and single point test for data set three

for Deformation program 101

5.36 Difference in displacement vector for data set three for

Deformation program (Disp1) and Khairulnizam (Disp2) 102

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LIST OF FIGURES

FIGURE NO TITLE PAGE

1.1 Flowchart of the research methodology 5

2.1 Preview of STARNET 13

2.2 Preview of GEO-LAB 14

2.3 Preview of MOVE3 16

2.4 Preview of ADJUST4.6 17

2.5 Linking STARNET and GPSAD2000/DEFORM99 23

2.6 Program DEFORM99 24

2.7 Program GPSAD2000 25

2.8 PANDA Program 26

2.9 DIMONS 28

3.1 Flowchart of least square estimation with statistical testing 30

3.2 Observation of horizontal angle, azimuth and horizontal distance 31

3.3 Error ellipse 37

3.4 Flowchart of Deformation detection by robust method 39

4.1 Chi-Square graph 56

4.2 F distribution graph 57

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4.3 Error Ellipse 58

4.4 Displacement Vector 59

4.5 GUI Flowchart 61

4.6 GUIDE Quick Start Dialog 62

4.7 Layout Editor 63

4.8 Callback Editor 63

4.9 Embedded MATLAB and MATLAB Compiler 64

4.10 Embedded MATLAB 65

4.11 MATLAB Compiler 66

4.12 MATLAB DEPLOYTOOL 68

4.13 New Deployment Project 69

4.14 MATLAB Web Server 70

5.1 Adjustment Program and STARNET plots, Data set

one epoch one 73


one epoch two 76


two epoch one 80


two epoch two 83


three epoch one 85


three epoch two 90

5.7 Displacement vector and error ellipse graphic by

Deformation program for data set one 93


Singh R. program for data set one 94

5.9 Displacement Vector (Disp.) 94

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Deformation program for data set two 96


Singh R. program for data set two 97



Deformation program for data set three 100

5.14 Displacement vector for data set three for program

by Khairulnizam 100


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LIST OF APPENDICES

APPENDIX TITLE PAGE

A. Results for data set one 111

B. Results for data set two 119

C. Results for data set three 128

two dimensional network adjustment and...

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