Aim of this writing is making of Bathymetric Surface Modelling from spot depth data and how to improve the quality management from the spot depth data. Output of bathymetric surface model as Digital Surface Model (DSM). Making process of DSM needs the good quality of spot depth data. So, the quality control is needed before to make DSM. The quality of spot depth include quality in horizontal and vertical position. In vertical position, TVU is used and in horizontal position THU is used. Both of them are compared with standar deviation, that value of standar deviation smaller than THU or TVU is good quality. The interpolation contour is needed to make DSM after quality of spot depth data. There are many methods of interpolation, kriging and natural neighbour example. The output in this writing is the good of bathymetric surface model by using natural neighbour interpolation.

1. Undergraduate Program in Geodesy and Geomatics Engineering
GD4202 Quality Management System
Quality Management of Bathymetric Surface Modelling
Ririn Indahyani*
Faculty of Earth Sciences and Technology, Institute of Technology, Bandung
*ririn.indahyani@students.itb.ac.id
Abstract. Aim of this writing is making of Bathymetric Surface Modelling from
spot depth data and how to improve the quality management from the spot depth
data. Output of bathymetric surface model as Digital Surface Model (DSM).
Making process of DSM needs the good quality of spot depth data. So, the
quality control is needed before to make DSM. The quality of spot depth include
quality in horizontal and vertical position. In vertical position, TVU is used and
in horizontal position THU is used. Both of them are compared with standar
deviation, that value of standar deviation smaller than THU or TVU is good
quality. The interpolation contour is needed to make DSM after quality of spot
depth data. There are many methods of interpolation, kriging and natural
neighbour example. The output in this writing is the good of bathymetric surface
model by using natural neighbour interpolation.
Keywords: Digital Surface Model, TVU, THU, interpolation methods.
1 Introduction
Spot depth is depth from surface water to topography of seabed. The spot depth
get from sounding activity. The spot depth lies on line of sounding that called
sounding line. The sounding line is divided into main line and cross line [1].
The cross line cross the main line, the function is to check quality of spot depth
in main line as horizontal and vertical position, also depth itself. Shortly, the
cross line as function as Quality Assesment (QA).
From spot depth data can be make DSM. DSM represents top faces of all
objects on the terrain (both vegetation and man-made features) or terrain itself
in open areas [2]. In this work, DSM represents contour of surface topography
of seabed from spot depth. Making DSM is needed contour’s interpolation.
Some interpolation usually is used known as Kriging, Spline, Triangular
Irregular Network (TIN), Inverse Distance Weight (IDW), Natural
Neigborhood, etc.
Received ________, Revised _________, Accepted for evaluation __________
( Diterima tanggal _______, Perbaikan diterima tanggal ________, Diterima untuk dinilai tanggal _______ )

2. 2 Ririn Indahyani
2 Material and Method
2.1 Spot depth Data
The data used for bathymetric surface model is spot depth. Spot depth content
of horizontal (x) dan vertical (y) position and h (depth). The depth is distance
from surface water to seabed. The depth is result of sounding that include factor
of distance transducer, tide, etc.
The x and y positions represent in projected coordinate system cartesian UTM
WGS 1984, zone 48 S. The spot depth that used is spot depth 1 and select the
one thousands data of spot depth minimally. The data can be seen in figure 1.
Figure 1 Selection of spot depth 1
The red outline is the spot depth data that select to be processed. Its content of
1038 data. The all depth data lie in below one hunderd meter of depth. The orde
1b is used based on IHO S-44 [3].
2.2 Quality Control and Quality Assesment of spotdepth
To check of Quality spot depth selection, there are many steps:
1. Check data (x and y) that redundant. It means in x and y have same in
position have same of depth. Also check data (x and y) in same position
have different depth then average. To check redundant data is outlier or
not, used equations:
TVU > stdev*1.96 (1)
TVU = √a2
+(b*d)2
(2)
Equation (1) and (2) get from IHO S-44 [3].

3. Making of Digital Surface Model of Spotdepth Data 3
Where, a=0.5; b=0.013; d=average depth. Stdev is standar deviation
and 1.96 is scale factor in confidence level 95 %.
2. Check the cross and fix point. To check use equations:
THU>stdev*2.45 (3)
THU=5+5% of depth metre (4)
Where THU is total horizontal uncertainty, 2.45 is scale factor in
confidence level 95 %. Equation (3) and (4) based on IHO-S44 [3].
From the check quality, the data become 823 data.
2.3 Select the interpolation method
There are two interpolation methods to make contour, kriging and natural
neighbour. Kriging use linear combine from weight to estimate value in
data sample. Kriging gives error and confidence. This method use
semivariogram to represent spatial differences and value of data sample.
Semivariogram represent weight in interpolation [4].
The natural neighbour interpolation is a geometric estimation technique
that uses natural neighbourhood regions generated around each point in
the data set. Like IDW, this interpolation method is a weighted-average
interpolation method. However, instead of finding an interpolated point's
value using all of the input points weighted by their distance, natural
neighbors interpolation creates a Delauney Triangulation of the input
points and selects the closest nodes that form a convex hull around the
interpolation point, then weights their values by proportionate area [5].
2.4 Created Contour
After interpolation methods, created contour from select interpolation
methods. To make contour use arcscene or surfer software.
3 Result and Discussion
Table 2 shows the quality assessment of sample of fix and cross point. There are
two samples. The Table 2a shows the point has bad quality because standar
deviation is bigger than THU. Analytically, the difference x and y position in
Table 2a is bigger about 5.9 m in x and 5.1 m in y. although, in Table 2b is good
quality because standar deviation is smaller than THU. The differences x and y
in Table 2b is smaller than Table 2a.

4. 4 Ririn Indahyani
Table 2 Sample of Quality Assesment (2a and 2b)
Figure 3 Representation of kriging interpolation Table 3 Value of kriging interpolation
Figure 4 Representation
of natural neighbour
Table 4 Value of natural
neighbour
interpolation
interpolation
Point 2 x (m) y (m) h (m) stdev*2.45
Main 678014.
5
9367389.3 -1.3 2.165515
Cross 678012.
1
9367388.6 -1.56
depth rata2 -1.43
THU 4.928
5
Classification statistics
Count 73453
Minimum -47.08341599
Maximum -1.317789197
Sum -745718.5656
Mean -10.13989864
Standar Deviation 13.92407178
Classification statistics
Count 65580
Minimum -47.03961563
Maximum -1.33706552
Sum -513168.1322
Mean -7.82507065
Standar Deviation 11.70080632
2a 2b

5. Making of Digital Surface Model of Spotdepth Data 5
Figure 5 DSM by using natural neighbour (5a) and kriging interpolation (5b)
From Figure 3 and Table 3, Figure 4 and Table 4 show that natural neighbour
interpolation has smaller standar deviation than kriging. It means natural
neighbour interpolation good from data to make DSM and also the contour is
smoother than kriging method. This methods give different result from other
people, just because its depend on the data. From that data is varied in depth, but
almost content of -11 m until -1m of depth. In Figure 5, natural neigbbour
represents spikes in clearly than kriging interpolation.
4 Conclusion
To make good bathymetric surface model is needed quality management of spot
depth data. So, to improve high quality management must be based on IHO S-
44. IHO-S44 as international standar quality of bathymentric survey. In this data
set, natural neighbour interpolation gives good quality of bathymetric surface
model. The natural neighbour interpolation is recommended to use for futher.
Acknowledgement
This writing is one of task the Quality Management System in 2016.
References
[1] Poerbandono & Djunarsjah, E. (2005). Survei Hidrografi. PT. Refika
Aditama, Bandung.
[2] Kufmann, Mario. (2011). Recommended accuracy and update
requirement for depth data. Journal of IRIS Research.
[3] Interntional Hydrograhic Bureau. (2008). IHO Standards for
Hydrographic Surveys.5th
Edition, Monaco.
[4] Bohling, Geoff. (2005). KRIGING. Kansas Geoling Survey.
[5] Ledoux, Hugo & Gold, Christoper. An efficient Natural Neighbour
Interpolation Algorithm for Geoscientific Modelling. Hongkong.
Department of Land Surveying and Geo-Informatics, Hong Kong
Polytechnic University.
(5a) (5b)

6. Making of Digital Surface Model of Spotdepth Data 5
Figure 5 DSM by using natural neighbour (5a) and kriging interpolation (5b)
From Figure 3 and Table 3, Figure 4 and Table 4 show that natural neighbour
interpolation has smaller standar deviation than kriging. It means natural
neighbour interpolation good from data to make DSM and also the contour is
smoother than kriging method. This methods give different result from other
people, just because its depend on the data. From that data is varied in depth, but
almost content of -11 m until -1m of depth. In Figure 5, natural neigbbour
represents spikes in clearly than kriging interpolation.
4 Conclusion
To make good bathymetric surface model is needed quality management of spot
depth data. So, to improve high quality management must be based on IHO S-
44. IHO-S44 as international standar quality of bathymentric survey. In this data
set, natural neighbour interpolation gives good quality of bathymetric surface
model. The natural neighbour interpolation is recommended to use for futher.
Acknowledgement
This writing is one of task the Quality Management System in 2016.
References
[1] Poerbandono & Djunarsjah, E. (2005). Survei Hidrografi. PT. Refika
Aditama, Bandung.
[2] Kufmann, Mario. (2011). Recommended accuracy and update
requirement for depth data. Journal of IRIS Research.
[3] Interntional Hydrograhic Bureau. (2008). IHO Standards for
Hydrographic Surveys.5th
Edition, Monaco.
[4] Bohling, Geoff. (2005). KRIGING. Kansas Geoling Survey.
[5] Ledoux, Hugo & Gold, Christoper. An efficient Natural Neighbour
Interpolation Algorithm for Geoscientific Modelling. Hongkong.
Department of Land Surveying and Geo-Informatics, Hong Kong
Polytechnic University.
(5a) (5b)