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SURVEYING SCIENCE AND GEOMATICS

FACULTY OF ARCHITECRURE, PLANNING AND SURVEYING,
UITM MALAYSIA SHAH ALAM SELANGOR DARUL EHSAN

BACHELOR OF SURVEYING SCIENCE AND GEOMATICS (HONOURS) – AP220

SUG 558/ GLS558 : ADVANCE ENGINEERING SURVEYING

LAB NO/Title : ………………………………………………………………………………………….....

Assigned: ...........................................

Due: .............................................

PREPARED BY:

No. NAME/UiTM No. MARKS/COMMENTS

PREPARED FOR:

ASSOC. PROF. MAT AKHIR BIN MD WAZIR

PRACTICAL 1

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DEFORMATION SURVEY
Objectives:
I. to understand the workflow in deformation survey
II. to understand the surveying process in the deformation survey
III. to carry out a simple deformation survey
IV. to process the deformation data
V. to evaluate the data and the result

Outcomes: At the end of the class, students should be able:

I. to select and create a control network around the selected object using traversing method
II. to select control and target points
III. to design procedure and table for observations
IV. to produce a report on deformation survey

DURATION : 6 weeks

Week Date Description

1 Brief introduction on deformation survey (the practical and reconnaissance )
2 Establishment of control and target points
3 Observations to targets
4 Processing survey data using Starnet (Introduction)
5 Preparation Report (Non F2F)
6 Submission (Non F2F)

LOCATION

Targets are located on SAAS. There are 8

on the wall, however you are required to observe to four (4) of them.

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EQUIPMENT
1. 1 Total station and Tripod for deformation observation.
2. 1 Traversing Set for X and Y control
3. 1 Leveling Set for Z control
4. A field book – to be used during in all practical.

Note: Students are required to plan and select appropriate equipment for observations. Avoid carrying unnecessary
equipment to the field.

METHODS

1. Identify 4 points a, b, c and d. (Target Points – TP) on the face of the retaining wall – Note: There are 6 target
points on the wall which are coloured in blue and green.
2. Walk around the field and identify 3 positions 1, 2 and 3 (Control Points – CP) which are intervisible to all TP.
Each group must ensure the CP has a strong geometry. Properly establish these CP using pegs. No point should
lies inside the field or near the field.
3. Create X, Y and Z control points around the retaining wall.
4. Set up instrument at CP1 and observe CP2 as Reference Object (RO) - with bearing 0 ○ on Face Left (FL).
5. Point the telescope to TPa and record the bearing. Design your own table.
6. Rotate the telescope to TPb and record the bearing.
7. Continue step (5) and finish the reading at CP2. All readings are considered as SET1 at FL
8. Transit the telescope to Face Right (FR) and target to CP2 as in step (5). Set the bearing to 180 ○. Repeat the
above steps as SET 1 at FR.
9. Move the total station to CP2 and RO to CP1. Repeat steps (4) to (8).
10. The instrument is still at CP2 but RO to CP3. Repeat steps (4) to (8).
11. Move the total station to CP3 and RO to CP2. Repeat steps (4) to (8).
12. Determine the coordinates of CP1, CP2 and CP3 using traversing. Assumed one of the CP has a coordinate of
1000, 1000, 50m.
13. Measure the Instrument Height at every CP.

14. Data Preparations and Reductions

i. Reduce all bearings to get angles
ii. Compute coordinates X, Y and Z for CP1, CP2 and CP3.
iii. Use STAR*Net for computations.
iv. Reduce the coordinates of TPa, TPb, TPc, TPd, TPe,
v. Assume SET1 as the datum.
vi. Compare the coordinates from SET1 and SET2 and comments.

SAFETY

1. Students are required to take safety precautions during the survey.

2. Use proper pegs.
3. All pegs must not be placed inside the hockey field. You should carefully design your traverse to avoid the pegs fall in
the field.
4. All vehicles are not allowed to be parked inside the field.
5. Please use the accompany sheet to record your activities.

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PRACTICAL 1

DEFORMATION SURVEY

CONFIGURATION OF A SIMPLE DEFORMATION SCHEME and ERRORS Ellipse

(CP – Control Point and 1 – Target Point)

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PRACTICAL 1

DEFORMATION SURVEY

DATA ENTRY in STARNET FORMAT using NOTEPAD

(CP – Control Point and 1 – Target Point)

#Control point of 103,104 and 105

C CP103 596562.2955 268601.2906 101.497 !!!

C CP104 596552.5321 268623.7399 101.238 !!!
C CP105 596526.3568 268619.0020 101.199 !!!
#C CP4 867.8818 1046.1071 8.212 !!!
#C CP5 852.4751 1065.0252 8.181 !!!
#C CP6 873.3109 1075.9067 8.228 !!!
#C 1 ???
#C 2 ???
#C 3 ???
#C 4 ???

# CP 103 HORIZONTAL
# At-From-To DD-MM-SS
A CP103-CP104-1 139-44-15
A CP103-CP104-2 124-52-11
A CP103-CP104-3 112-00-32
A CP103-CP104-4 125-40-47
A CP103-CP104-1 139-44-21
A CP103-CP104-2 124-52-14
A CP103-CP104-3 112-00-32
A CP103-CP104-4 125-40-50
A CP103-CP104-1 139-44-21
A CP103-CP104-2 124-52-10
A CP103-CP104-3 112-00-27
A CP103-CP104-4 125-40-45

# CP 103 VERTICAL
# FROM-TO DD-MM-SS HI/HT
V CP103-1 90-15-51 1.423/0
V CP103-2 90-16-49 1.423/0
V CP103-3 90-05-41 1.423/0
V CP103-4 89-47-39 1.423/0
V CP103-1 90-15-57 1.423/0
V CP103-2 90-16-55 1.423/0
V CP103-3 90-05-40 1.423/0
V CP103-4 89-47-51 1.423/0
V CP103-1 90-15-53 1.423/0
V CP103-2 90-16-58 1.423/0
V CP103-3 90-05-39 1.423/0
V CP103-4 89-47-53 1.423/0

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PRACTICAL 1

DEFORMATION SURVEY

RESULT FROM STARNET

(CP – Control Point and 1 – Target Point)

Adjustment Statistical Summary

==============================

Convergence Iterations = 4

Number of Stations = 7

Number of Observations = 96
Number of Unknowns = 12
Number of Redundant Obs = 84

Observation Count Sum Squares Error

of StdRes Factor
Angles 48 10945.275 16.143
Zeniths 48 1002676.488 154.510

Total 96 1013621.763 109.850

Warning: The Chi-Square Test at 5.00% Level Exceeded Upper Bound

Lower/Upper Bounds (0.849/1.151)

Adjusted Coordinates (Meters)

=============================

Station N E Elev Description

CP100 596525.4055 268517.1669 95.5990
CP101 596553.1195 268505.0817 99.6530
CP102 596563.9002 268536.2692 99.4840
1 596528.7923 268565.7059 100.0032
2 596540.7040 268565.7014 100.1541
3 596551.8285 268565.8313 100.3199
4 596542.0527 268564.8178 100.5112

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PRACTICAL 1

DEFORMATION SURVEY

USING THE STARNET

1. INPUT DATA

1) Click Input toolbar menu and select Data Files.

2) Click Add

3) Browse input data and click Add.

Then Click OK

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2. PROCESSING

1) Click Run toolbar menu and click Adjust Network!

2) The result will be appeared as shown as below figure.

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3. SHOWING THE REPORT

1) Click Output menu toolbar and select Listing.

The result will be appeared.

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4. SHOWING THE COORDINATE

1) Click at Output menu toolbar and select Coordinates.

2) The result will be display as shown as below figure.

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5. SHOWING THE DRAWING

1) Click Output menu toolbar and select Plot.

2) The traverse plotting will be shown as below figure.

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PRACTICAL 1

DEFORMATION SURVEY

LOG SHEET – Deformation Survey

No Date Report by Activities

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SAMPLE LAB REPORT

The Optimal Foraging Theory:

Food Selection in Beavers Based on Tree Species, Size, and Distance

Laboratory 1, Ecology 201

Abstract.

The theory of optimal foraging and its relation to central foraging was examined by using the beaver as
a model. Beaver food choice was examined by noting the species of woody vegetation, status (chewed vs. not-
chewed), distance from the water, and circumference of trees near a beaver pond in North Carolina. Beavers
avoided certain species of trees and preferred trees that were close to the water. No preference for tree
circumference was noted. These data suggest that beaver food choice concurs with the optimal foraging theory.

Introduction

In this lab, we explore the theory of optimal foraging and the theory of central place foraging using
beavers as the model animal. Foraging refers to the mammalian behavior associated with searching for food.
The optimal foraging theory assumes that animals feed in a way that maximizes their net rate of energy intake
per unit time (Pyke et al. 1977). An animal may either maximize its daily energy intake (energy maximizer) or
minimize   the   time   spent   feeding   (time   minimizer)   in   order   to   meet   minimum   requirements.   Herbivores
commonly   behave   as   energy   maximizers   (Belovsky   1986)   and   accomplish   this   maximizing   behavior   by
choosing   food   that   is   of   high   quality   and   has   low­search   and   low­handling   time   (Pyke   et   al.   1977).
          
 The central place theory is used to describe animals that collect food and store it in a fixed location in
their home range, the central place (Jenkins 1980). The factors associated with the optimal foraging theory also
apply to the central place theory. The central place theory predicts that retrieval costs increase linearly with
distance of the resource from the central place (Rockwood and Hubbell 1987). Central place feeders are very
selective when choosing food that is far from the central place since they have to spend time and energy
hauling it back to the storage site (Schoener 1979).

           The main objective of this lab was to determine beaver (Castor canadensis) food selection based on tree
species, size, and distance. Since beavers are energy maximizers (Jenkins 1980, Belovsky 1984) and central
place feeders  (McGinley and Whitam  1985), they make an excellent  test animal  for the optimal  foraging
theory. Beavers eat several kinds of herbaceous plants as well as the leaves, twigs, and bark of most species of
woody plants that grow near water (Jenkins and Busher 1979). By examining the trees that are chewed or not­
chewed in the beavers home range, an accurate assessment of food preferences among tree species may be
gained (Jenkins 1975). The purpose of this lab was to learn about the optimal foraging theory.  We wanted to
know   if   beavers   put   the   optimal   foraging   theory   into   action   when   selecting   food.
          
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  We hypothesized that the beavers in this study will choose trees that are small in circumference and
closest to the water. Since the energy yield of tree species may vary significantly, we also hypothesized that
beavers  will  show  a preference  for some  species  of trees  over others  regardless  of circumference  size or
distance from the central area. The optimal foraging theory and central place theory lead us to predict that
beavers, like most herbivores, will maximize their net rate of energy intake per unit time. In order to maximize
energy, beavers will choose trees that are closest to their central place (the water) and require the least retrieval
cost. Since beavers are trying to maximize energy, we hypothesized that they will tend to select some species
of trees over others on the basis of nutritional value.

Methods

This study was conducted at Yates  Mill Pond, a research area owned by the North Carolina State
University,   on   October   25th,   1996.   Our   research   area   was   located   along   the   edge   of   the   pond   and   was
approximately 100 m in length and 28 m in width. There was no beaver activity observed beyond this width.
The circumference, the species, status (chewed or not­ chewed), and distance from the water were recorded for
each tree in the study area. Due to the large number of trees sampled, the work was evenly divided among four
groups of students working in quadrants. Each group contributed to the overall data collected. 

We conducted a chi­squared test to analyze the data with respect to beaver selection of certain tree
species. We conducted t­tests to determine (1) if avoided trees were significantly farther from the water than
selected trees, and (2) if chewed trees were significantly larger or smaller than not chewed trees. Mean tree
distance from the water and mean tree circumferences were also recorded.

Results

Overall, beavers showed a preference for certain species of trees, and their preference was based on
distance from the central place. Measurements taken at the study site show that beavers avoided oaks and
musclewood (Fig. 1) and show a significant  food preference (x2=447.26, d.f.=9, P<.05). No avoidance  or
particular preference was observed for the other tree species. The mean distance of 8.42 m away from the water
for not­chewed trees was significantly greater than the mean distance of 6.13 m for chewed trees (t=3.49,
d.f.=268, P<.05) (Fig. 2). The tree species that were avoided were not significantly farther from the water
(t=.4277,   d.f.=268,   P>.05)   than   selected   trees.   For   the   selected   tree   species,   no   significant   difference   in
circumference was found between trees that were not chewed (mean=16.03 cm) and chewed (mean=12.80 cm)
(t=1.52, d.f.=268, P>.05) (Fig. 3). 

Discussion

Although beavers are described as generalized herbivores, the finding in this study related to species
selection suggests that beavers are selective in their food choice. This finding agrees with our hypothesis that
beavers are likely to show a preference for certain tree species. Although beaver selection of certain species of
trees may be related to the nutritional value, additional information is needed to determine why beavers select

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some tree species over others. Other studies suggested that beavers avoid trees that have chemical defenses that
make the tree unpalatable to beavers (Muller­Schawarze et al. 1994). These studies also suggested that beavers
prefer trees with soft wood, which could possibly explain the observed avoidance of musclewood and oak in
our study. 

The result that chewed trees were closer to the water accounts for the time and energy spent gathering
and hauling. This is in accordance with the optimal foraging theory and agrees with our hypothesis that beavers
will choose trees that are close to the water. As distance from the water increases, a tree?s net energy yield
decreases because food that is farther away is more likely to increase search and retrieval time. This finding is
similar to Belovsky’s finding of an inverse relationship between distance from the water and percentage of
plants cut. 

The lack of any observed difference in mean circumference between chewed and not chewed trees does
not agree with our hypothesis that beavers will prefer smaller trees to larger ones. Our hypothesis was based on
the idea that branches from smaller trees will require less energy to cut and haul than those from larger trees.
Our finding is in accordance with other studies (Schoener 1979), which have suggested that the value of all
trees should decrease with distance from the water but that beavers would benefit from choosing large branches
from large trees at all distances. This would explain why there was no significant difference in circumference
between chewed and not­chewed trees. 

This lab gave us the opportunity to observe how a specific mammal selects foods that maximize energy
gains in accordance with the optimal foraging theory. Although beavers adhere to the optimal foraging theory,
without additional information on relative nutritional value of tree species and the time and energy costs of
cutting certain tree species, no optimal diet predictions may be made. Other information is also needed about
predatory risk and its role in food selection. Also, due to the large number of students taking samples in the
field, there may have been errors which may have affected the accuracy and precision of our measurements. In
order to corroborate our findings, we suggest that this study be repeated by others. 

Conclusion

The purpose of this lab was to learn about the optimal foraging theory by measuring tree selection in
beavers. We now know that the optimal foraging theory allows us to predict food­seeking behavior in beavers
with respect to distance from their central place and, to a certain extent, to variations in tree species. We also
learned that foraging behaviors and food selection is not always straightforward. For instance, beavers selected
large   branches   at   any   distance   from   the   water   even   though   cutting   large   branches   may   increase   energy
requirements. There seems to be a fine line between energy intake and energy expenditure in beavers that is not
so easily predicted by any given theory.

Literature Cited

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Belovsky, G.E. 1984.  Summer diet optimization by beaver.  The American Midland Naturalist. 111: 
209­222.
Belovsky, G.E.? 1986. Optimal foraging and community structure: implications for a guild of generalist
grassland herbivores. Oecologia. 70: 35­52.
Jenkins, S.H.  1975. Food selection by beavers:  a multidimensional contingency table analysis.  
Oecologia.  21: 157­173.
Jenkins, S.H. 980. A size­distance relation in food selection by beavers Ecology.
61:? 740-746.
Jenkins, S.H., and P.E. Busher. 1979. Castor canadensis.Mammalian Species.
120:? 1-8.
McGinly, M.A., and T.G. Whitham.? 1985. Central place foraging by beavers (Castor Canadensis):? a 
test of foraging predictions and the impact of selective feeding on the growth form of cottonwoods (Populus 
fremontii).? Oecologia.? 66: 558­562.
Muller­Schwarze, B.A. Schulte, L. Sun, A. Muller­Schhwarze, and C. Muller­Schwarze. 1994. Red 
Maple (Acer rubrum) inhibits feeding behavior by beaver (Castor canadensis).  Journal of Chemical Ecology. 
20: 2021­2033.

*Note: This document was modified from the work of NCSU graduate students Selena Bauer, Miriam Ferzli,
and Vanessa Sorensen.

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