Effect of the number of ground control points in the process of rectifying high-resolution satellite
imagery
Imam Satria Yudha1,Muhammad Taufik1 ,Akbar Kurniawan1
Department of Geomatics Engineering,
Faculty of Civil, Environmental, and Geo Engineering,
Institut Teknologi Sepuluh Nopember
Surabaya, Indonesia
Email: [email protected], [email protected],[email protected]
Abstract
At present, Remote Sensing Technology has been highly developed to produce high-resolution
satellite images, that can be used as an alternative method of mapping and monitoring development in an
area. The main requirement in the use of satellite imagery is to do geometric correction (rectification).
Accurate rectification process is very dependent on the selection of ground control points used. Through
analysis and experiments show that the number of ground control points will affect the accuracy of the
results of image rectification. Good image rectification results are shown by the small Root Mean Square
Error (RMSE) value. This RMSE value is obtained from the test of coordinate accuracy measured by GNSS.
Through accuracy tests using coordinates in the field with corrected image coordinates, when using 4 (four)
ground control points can meet a scale of 1: 1000, 8 (eight) ground control points can meet a scale of 1:
5000, and 12 (twelve) ground control points can fulfilling a 1: 5000 scale.
Keywords : Ground control points, High Resolution Satellite Imagery, Map Scale, Rectification, Remote
Sensing
1. Introduction
The main requirement in the use of satellite
imagery is to do geometric correction
(rectification). Accurate rectification process is
very dependent on the selection of ground control
points used. There are several methods to obtain
control point data, such as selecting ground
control points from the base map, using objects
on aerial photographs or satellite images of the
same or higher resolution that have been
corrected and, obtaining control point data using
field surveys using terestrial method or GNSS. In
practice, many factors limit the use of this
method. For example, it is difficult to obtain maps,
aerial photographs or suitable images, or the data
was made in the past 10-30 years, remote areas
that cannot be accessed for field surveys and so
on. Therefore we need an effective and accurate
method to process high resolution satellite
imagery.
The process of rectifying SPOT-4 Nadir images
level 2A resolution of 20 meters using ground
control points obtained from Landsat
Orthorectification images of USGS products with
spatial resolution 15 meters, can produces RMS
38.33 meters using 5 GCP, if used 16 GCP then
produces RMS 35.61 meters and RMS 26.36
meters for 80 GCP (Arief, Kustiyo, & Surian, 2008).
This is certainly difficult when applied to 0.5 meter
resolution satellite imagery. Therefore a study of
the effective use of the number of soil ground
control points is divided into 3 schemes, namely
scheme 4 GCP, 8 GCP and, 12 GCP. All GCP
measurements are carried out directly in the field
using GNSS.
2. Study Area Description
The city of Kediri has a unique topographic form
of the city because most of the area of the City of
Kediri (80.17%) is a lowland with an altitude of 63100 meters above sea level located along the side
Metodology of the Brantas River. While the rest
(18.83%) is a plateau and hills with an altitude of
100-500 meters above sea level spread in the
western and eastern parts of the City of Kediri
(Bappeda, East Java Province, 2013). The location
of this study was conducted in the City of Kediri,
East Java. Where the coordinates of this city are
located at 7⁰46'11" N - 7⁰52'29" S and 111⁰57'11
"E - 112⁰04’52"E . Administratively, the City of
Kediri has an area of 63,404 km² consisting of 3
sub-districts.
3. Metodology
3.1. Data and Ground control points
Desain
The data used in this study are World resolution-II
Level 1 high resolution satellite image data in
2014. The image still uses a geographical
coordinate system and has not been projected
UTM, so the image rectification process is carried
out. To do the rectification process, the design of
the number and distribution of GCP is made to be
spread in the image for the image rectification
process. There are 3 models of number and
distribution of land ground control points, namely
with scheme 1 using the number 4 GCP. scheme 2
uses the number 8 GCP. scheme 5 using 12 GCP.
3.2.
Imagery Rectification
Imagery rectification aims to reduce the
geometric distortion of the earth's surface objects
in the image caused by the curvature of the
earth's surface and several other factors such as
variations in satellite height, satellite rigidity and
speed.
The use of the number of ground control points
that must be made depends on how complex the
planned Polynomial transformation form is used
to convert raster data into map coordinates. The
parameters of the accuracy of the rectification
process are the values presented by the difference
between the coordinates of the ground control
points resulting from the transformation with the
coordinates of the ground control points in the
field, known as the RMS (Root Mean Square)
Error. The tolerance limit for the RMS error error
value is 1 pixel, so if the value of the RMS error is
more than 1, a recalculation must be done.
(Purwadhi, 2001).
3.3.
Result Analysis
Analysis of image rectification results, can be
obtaine from :
a. Analysis of the accuracy of coordinates
b. Analysis of area
c. Map Scale
4. Results and Discussion
4.1. Imagery Rectification Results
The rectification process uses first order
polynomial, which is linear. The first order
polynomial equation with three parameters
makes it possible to correct the translation in x, y,
rotation, x, y, and oblique axes (Mohammed,
2013). The first order polynomial equation is used
for relatively flat areas using a minimum of 3 GCP
or more. This is the same for each model because
at least 1 polynomial requires 3 GCPs to do the
rectification process, order 2 polynomials need a
minimum of 6 GCP and order 3 requires a
minimum of 10 GCP. There are several factors in
choosing the polynomial order, namely the
number of ground control points available, the
state of the topography of the area and errors or
distortions in the image to be rectified.
The first order polynomial formula (linear) is as
follows:
𝑥0 = 𝑎0 + 𝑎1 𝑥 + 𝑎2 𝑦
𝑦0 = 𝑏0 + 𝑏1 𝑥 + 𝑏2 𝑦
The above formula is a transformation formula in
the rectification process using first order
polynomial (linear), with x and y are the origin
coordinates (input) while x0 and y0 are the
corrected (output) coordinates (Erdas, 1999).
To find out the accuracy of the image rectification
results can be seen from the error RMS value.
Error RMS values indicate the value of errors that
occur in the rectification process that has been
done.
Table 1. Rectification Results
Number of
Average Mean Eror
GCP
(pixel)
4 GCP
0,637
8 GCP
0,525
12 GCP
0,373
4.2. Result Analysis
4.2.1. Accuracy of Coordinates
Accuracy of coordinate analysis was obtained by
finding residual measurement data in the field
from GPS measurements and coordinate points
from satellite images after the rectification
process. The residual values of X and Y
coordinates are used to find the RMS value of the
image coordinate error.
The number of samples taken is 30 points, located
in the Kediri city area. The results of the residual
data can obtain the value of RMS eror of imagery
coordinates.
Table 2. Coordinates Accuracy Test
Number of GCP
Average Mean Eror (m)
4 GCP
2.031
8 GCP
1.270
12 GCP
1.718
From table, it can be seen that scheme 2 with 8
ground control points has the smallest RMS value
of the coordinate, which is 1,270 meters. In
scheme 3 the value of the RMS error coordinates
of the image is 1.718. Scheme 3 should have the
best accuracy results of coordinates, because it is
a representation of the whole scheme using 12
ground control points.
4.2.2. Accuracy of Area
In addition to obtaining an error RMS value from
the rectified image coordinates can also be
generated area. The field observation area using
GNSS has a significant difference with the results
of the rectified imagery. Accuracy of area in the
image is expressed by presentation of the
difference in field observations and interpretation
of the rectified imagery.
Table 3. Percentage Area Eror
Number of
GCP
Average Percentage Eror
4 GCP
3.81%
8 GCP
2.37%
12 GCP
1.32%
From the table it can be seen that the percentage
of the average area difference is best found in
scheme 3 with presentation of 1.32%, followed by
scheme 2 of 2.37% and in scheme 1 of 3.81%.
tolerance value for area differences is below 10%.
4.2.3. Map Scale
From the Indonesian National Standard (SNI)
number 19-6502.1-2000, about the technical
specifications for the presentation of an
Indonesian topography map with scale 1: 10000,
states that on a 1: 10000 scale of map it has a 0.3
mm error RMS which is a coordinate value that is
scaled against the closest grid line in the field..
From this provision planimetric accuracy of each
map scale is as follows:
• Map scale 1: 1000 has an accuracy of 0.3 m
• Map scale 1: 5000 has accuracy of 1.5 m
• Map scale 1:10,000 has accuracy of 3 m
Table 4. Map Scale
Number of GCP
4 GCP
8 GCP
12 GCP
Map Scale
1 :
10000
1 :
5000
1 :
5000
From the table of results of image rectification, it
can be concluded that the use of GCP has
planimetric accuracy, good time and cost
effectiveness, and for 12 GCPs it also meets good
planimetric accuracy, but the large number and
spread throughout the city takes more time and
cost than 8 GCP. This is due to a reduction in the
number ground control points (GCP). The more
ground control points, better the level of
accuracy. Vice versa.
5. Conclusion
Analysis and experiments showed that the
number of soil control points affected accuracy in
the process of rectifying high-resolution satellite
images. The use of the right number and point
location that are evenly distributed is something
that must be fulfilled in determining the control
points in the field. In the experiment above, it can
be seen that the use of 8 control points and 12
control points fulfills planimetric accuracy in
accordance with the applicable Indonesian
National Standard, which meets a 1: 5000 scale.
References
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Badan Standarisasi Nasional. (2003). “Spesifikasi
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Bappeda Provinsi Jawa Timur. (2013).
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