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Spatial Accuracy in Orthophoto produced using UAV Photographic Images
Lägesnoggrannhet i ortofoton framställda med UAV-foton
Lily Ng Stensson
Faculty: Faculty of Social and Life Sciences, Geo-Science
Subject: Degree Project, Programme in Surveying and Cartography
Points: Bachelor's degree 7.5 ECTS credits
Supervisor: Jan-Olov Andersson
Examiner: Jan-Olov Andersson
Date: 14092016
Serial number: 2016:9
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Abstract
The popularity of using UAV in image-taking for the production of 3D models and
orthophotos has increased over time. Karlskoga Municipality has recently acquired an
UAV to produce their own 3D models and orthophotos. This project paper aims to
study the geospatial accuracy of the orthophotos and DEM files produced using the
images taken with their UAV. The flight takes only a few minutes but a considerable
time is spent in the production processes. Difficulty is experienced in determining the
right center point for most GCPs. Produced orthophotos in the software Photoscan
have a resolution from 1.7 to 2.4 centimeters while DEM files have a resolution from
3.4 to 4.8 centimeters. Four orthophotos and four DEM files are produced where
GCPs are used and not used and at two different flight heights, 76 and 105 meters.
The spatial data of the ten GCPs are identified on the orthophotos and DEM files in
ArcMap and compared with GNSS NRTK measurements and Lantmäteriet's data. A
visual control in terms of completeness of data, alignment, residual tilt and scale is also
done. Standard deviations in plane for orthophotos there GCPs are not used are
greater than 2 meters, while there GCPs are used are around 0.7 meters. Standard
deviations for DEM files are observed at 0.8 meters.
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Table of Contents
List of abbreviations ...................................................................................................................................... 5
1. Introduction .............................................................................................................................................. 6
1.1 Background ............................................................................................................................................. 6
1.2 Client ....................................................................................................................................................... 6
1.3 Objective ................................................................................................................................................. 6
1.4 Project boundary .................................................................................................................................... 6
1.5 Project Limitation .................................................................................................................................... 7
2. Review of literature .................................................................................................................................. 8
2.1 Ground Control Points ............................................................................................................................ 8
2.2 Overlap between images ...................................................................................................................... 10
2.3 Atmospheric condition - Sun position, shadowing and period of the year .......................................... 11
2.4 Definition of an orthophoto .................................................................................................................. 11
3 Methodology ............................................................................................................................................ 13
3.1 General Workflow in Agisoft Photoscan ............................................................................................... 13
3.2 Flight coverage area .............................................................................................................................. 13
3.3 Signal form ............................................................................................................................................ 14
3.4 Images from UAV .................................................................................................................................. 14
3.5 Placement of the ground markers ........................................................................................................ 15
3.6 Determination of spatial accuracy ........................................................................................................ 16
3.6.1 Position Accuracy with GCP ............................................................................................................... 16
3.6.2 Visual Control ..................................................................................................................................... 17
4 Results ...................................................................................................................................................... 17
4.1 Orthophoto and DEM ........................................................................................................................... 17
4.2 Spatial accuracy test (Absolute accuracy) ............................................................................................. 18
4.3 Spatial accuracy test (Relative accuracy) .............................................................................................. 19
4.4 Parameters for orthophotos ................................................................................................................. 19
4.5 GNSS measured GCP and Lantmäteriet Höjddata 2+ ........................................................................... 19
4.6 Visual Control ........................................................................................................................................ 20
4.6.1 Test for completeness of data ........................................................................................................... 20
4.6.2 Test of alignment ............................................................................................................................... 20
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4.6.3 Residual tilt ........................................................................................................................................ 22
4.6.4 Scaling ................................................................................................................................................ 22
5. Discussion ................................................................................................................................................ 23
6. Conclusion ............................................................................................................................................... 26
References .................................................................................................................................................. 27
Appendix ..................................................................................................................................................... 30
1. Camera and Photoscan processing parameters ................................................................................ 30
2. Coordinates of the ground markers ................................................................................................... 31
3. System requirements for Photoscan ................................................................................................. 32
4. Processing steps in Photoscan ........................................................................................................... 33
5. Computation tables ........................................................................................................................... 42
6. Orthophoto produced from images taken at 105 m flight height and with assignment of 10 GCPs.45
7. GCPs' position comparison ................................................................................................................ 46
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List of abbreviations
DEM Digital Elevation Model EPSG:5848 European Petroleum Survey Group Geodetic Parameter Dataset
5848 GCP Ground Control Point GNSS Global Navigation Satellite System GSD Ground Sample Distance HMK Handbook of Surveying and Mapping Issues (Handbok i mät-
och kartfrågor) NRTK Network Real Time Kinematic (serviced by Lantmäteriet's
SWEPOS satellite positioning) RH2000 Swedish National Height System 2000 SWEREF 99 15 00 Swedish Reference Frame 1999 Zon 15o 00"
UAV Unmanned Aerial Vehicle
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1. Introduction
1.1 Background
The City Planning Administration within the Karlskoga Municipality has plans in using aerial
photography from UAV to create high resolution orthophotos and 3D models over an increasing
number of areas in the municipality. These will serve as tools in mapping, city planning, marketing
real estates and attract investments to the municipality.
Through this initiative, residents, organizations and politicians will have access to this data. They will
get a better perspective and understanding over the different development plans in the municipality
through the visualization of the effects of the proposed new landscapes. Likewise, the creation of
orthophotos and 3D models will aid the landscape and city architects and other division officials in
the development of new plans, its presentation and create a better platform in decision making for
all levels. This action is also in line with the continuous development of the infrastructure for
geodata in the country.
The Karlskoga Municipality provides the student with UAV photo images and GNSS NRTK
measured GCPs for processing. After processing and analysis, the student will provide Karlskoga
Municipality the resulting orthophoto together with a 3D model and a results analysis.
1.2 Client
The client for the project was Magnus Jordan, surveying engineer, together with Johan Mood, city
planning architect of land-use and planning division (mark- och planeringsavdelningen), both
working at the City Planning Administration within the Karlskoga Municipality (Samhälls-
byggnadsförvaltningen, Karlskoga kommun).
1.3 Objective
The objective of the project was to produce orthophotos together with their corresponding DEMs
and a 3D model over an area and evaluate both the orthophotos' and DEMs' geospatial accuracy.
1.4 Project boundary
The area of interest in this project is Äspenäs (or Espenäs), Karlskoga (60,000 m2 or 6 hectare). The
projected reference system concerned is in SWEREF 99 15 00, RH 2000 (EPSG:5848). Figure 1
shows the location of the study area.
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Table 1. Spatial Bounding Coordinates in meters (SWEREF 99 15 00).
Easting (E) Northing (N)
121000 6575300
121050 6575080
120900 6575020
120780 6575150
Figure 1. Location of the study area marked in color yellow (Lantmäteriet, 2016, https://atlas.slu.se/get/).
1.5 Project Limitation
Aerial photography captured using UAV is not included in the standards and prerequisites set in the
HMK-bilddata (2015) or in the HMK-ortofoto (2015). Nonetheless this project tries to follow the
procedures as close to the set standards as which are applicable. The guidelines and standards set in
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HMK Laserdata (2015) and HMK Fordonsburen laserdatainsamling (2015) will also be taken into
consideration.
Selection, design and outline of the ground control points (GCPs) are done under the management
of the client. Likewise, the client does all the planning and implementation of the photographing by
UAV. Suggestions are presented while the client chooses the final alternative for the project. Data in
form of text file and image files in jpeg format are then provided by the client for processing.
Technical documentation for GNSS NRTK measurements of GCPs is not available. A presumption
in this project is that GNSS NRTK measured GCPs behold absolute accuracy according to HMK
standard.
This project of creating the orthophotos, DEMs and 3D model is done with Agisoft Photoscan Pro
version 1.2.4. Processing of 100-200 images requires high capacity 32-64 GB RAM, high-end graphic
card and a high speed multi core CPU. It takes a considerable time to process 100-200 images and
can cause program to stop functioning and thereby disrupting workflow and production efficiency.
The limitation of hardware capacity can affect and set limits to the resulting orthophotos and 3D
model production.
2. Review of literature There are several contributing factors which affect the spatial accuracy in the production of an
orthophoto as taken from UAV produced images. Some factors are described in this chapter.
2.1 Ground Control Points
The ground control points or GCPs are points of known geographic location in the surveying area
(Pix4d support site, 2016c). It must be easy to identify and measure. The size depends on the
resolution of the image, as too small GCP can cause difficulty in identification after photo taking
while too big can cause the center point being not able to be concretely indicated. According to
HMK-standard 2, GCP is a square signal with 2xGSD by 2xGSD (Lantmäteriet, 2015a).
Some suggestions for the form and shape of the GCP are given in the HMK Bilddata (Lantmäteriet,
2015a) as shown in Figure 2.
Figure 2. Image samples of GCP (Lantmäteriet, 2015a).
While another company like Pix4D suggests the format shown in Figure 3.
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Figure 3. GCP photogrammetric target (Pix4d support site, 2016c).
To get the ground sample distance (GSD), this excel computation table (Figure 4) is downloaded
from Pix4D website.
Figure 4. Computation of GSD (Pix4D support site, 2016e).
where
GSD= (Sw * H * 100) / (Fr * imW)
Dw= ImW*GSD/100
DH= imH*GSD/100
(Pix4d support site, 2016a, 2016c).
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Figure 5. Sample GCP where P is pixel size (Graham and Koh, 2002).
Another source Graham & Koh (2002) has the above suggestion (Figure 5) in determining the size
of a GCP.
Without GCPs, one can still produce orthophoto and 3D model but the result will have no scale,
lack orientation, and no absolute position information. Furthermore, the surveyed area in 3D model
may have a result of bad relative reconstruction, or simply said, it may not be able to preserve the
original shape of the surveyed area. Availability of GCPs in image processing will increase the
absolute accuracy of the image in its geographical location with as little variation in scaling as
possible. The difference of with or without GCP is from meters to centimeters (Pix4d support site,
2016d).
With absence of constructed GCPs, natural GCP or artificial points can also be chosen like the
corners of a woodlot, road intersections, or rock outcrops (Verbyla, 1995). HMK Laserdata
(Lantmäteriet, 2015c) identifies corner points of objects like roads can also be used as markers just
as the ridge on the roof.
In Gunnarsson & Persson's (2013) thesis paper, they were able to test the accuracy of object
geographic position given different numbers and positioning of GCP. The result of their study
indicates that the greater number of GCPs, the accuracy gets better. However the results between 9
GCPs and 17 GCPs differ with only 5 mm.
Agisoft (2016a) recommends at least 10 GCPs spread across the area of reconstruction.
2.2 Overlap between images
Guideline according to the HMK standard 1 and 2 indicates image overlapping at 60 % frontal and
30 % side overlapping (Lantmäteriet, 2015a). Image processing company like Pix4D (2016b)
recommends 75 % frontal and 60 % side overlap in general cases while Agisoft (2016a) recommends
80 % forward overlap and 60 % side overlap.
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2.3 Atmospheric condition - Sun position, shadowing and period of the year
The sun elevation and shadows of the objects on the images contribute to the quality of the
orthophoto. Recommendation in the HMK Bilddata (Lantmäteriet, 2015a) states that sun elevation
(angle/height of the sun over horizon) should be at least 30 degrees with an approximate shadow
length of 1:1.7 ratio. On SMHI's homepage (2015), a sun elevation diagram is created using the
analemma. Figure 6 shows the diagram for Stockholm and is applicable likewise to Karlskoga.
Photographing is recommended before birth tree leafing and after snow melting which is around
May for Stockholm area. Period for photographing however varies depending on the usage of the
resulting orthophoto and 3D model (Lantmäteriet, 2015a).
Figure 6. Sun elevation diagram for Stockholm area (SMHI, 2015).
2.4 Definition of an orthophoto
An orthophoto is a photographic image constructed from vertical or near vertical aerial photographs
from which the distortions due to terrain relief displacement and camera tilt on the aircraft are
removed (Falkner and Morgan, 2002). "An orthophoto has the same scale throughout and can be
used as a map" (Orthophoto, 2016). Simply said, an orthophoto is a photographic map (USGS,
2013).
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Positional accuracy throughout an image can attain a predictable constant quality if properly
generated (Falkner and Morgan, 2002). Figure 7 shows how the effect of relief is corrected for
orthophotos.
Figure 7. The effects of relief and how it is corrected for orthophotos (Falkner and Morgan, 2002).
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3 Methodology
3.1 General Workflow in Agisoft Photoscan
Agisoft Photoscan is a computer vision software package developed by Russian manufacturer
Agisoft LLC. This program uses a series of overlapping photographs to reconstruct a sparse point
cloud of scenes in three dimensional shape with help of mathematical techniques such as structure
from motion (SFM) algorithms together with stereo-matching algorithms (Verhoeven, 2011). The
detailed processing steps used for this project can be found in Appendix 4 following the general
workflow in Figure 8.
Figure 8. General workflow in Agisoft Photoscan.
3.2 Flight coverage area
The two flight sessions covered the study area as well as a bit of the surrounding area by more than
15 %.
Add photo
Align photo Build dense
cloud
Build mesh Build texture
Build DEM Build
Orthomosaic
Export DEM/ orthomosaic/
points/ 3D model
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Figure 9. Study area in yellow dots and flight coverage area in blue line, Äspenäs, Karlskoga.
3.3 Signal form
Signal form used in this project has an A3 format box with a height of 7.8 cm as shown in Figure 10.
These markers serve as both horizontal and vertical control markers.
Figure 10. Signal form used in this project.
3.4 Images from UAV
Two flight events with different flying altitude are tested. Below are the specifications applied during
each flight.
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Table 2. Specifications used in two different flight heights, 76 meters and 105 meters.
UAV DJI Inspire 1 Professional X5 DJI Inspire 1 Professional X5
Camera Zenmuse X5 Zenmuse X5
Lens DJI MFT 15 mm DJI MFT 15 mm
Surveying application Drone Deploy Drone Deploy
Aspect ratio 4:3 4:3
Date and time June 1, 2016, noon June 1, 2016, noon
Flyght height 76 meters 105 meters
Total number of images 197 112
Duration 16 minutes 6 minutes
Speed 12 m/s 12 m/s
Area 12 hectares 12 hectares
Resolution (GSD) 1.9 cm/pix 2.6 cm/pix
Overlaps 60 % sidelap, 70 % frontlap 60 % sidelap, 70 % frontlap
Reference System WGS84 (EPSG:4326) WGS84 (EPSG:4326)
No. of transects/ parallel
lines
7 5
No. of GCP 8 signal form, 2 natural GCP 8 signal form, 2 natural GCP
Image file format Jpg Jpg
3.5 Placement of the ground markers
Ten GCPs are spread out over the study area at intervals as regular as possible at site as shown on
Figure 11. The coordinates of the GCPs are found in Appendix 2.
Figure 11. Placement of GCPs in Äspenäs, Karlskoga. Within the yellow contour is the target area.
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3.6 Determination of spatial accuracy
In this project, the accuracy of the position of GCPs as identified on the orthophotos which are
produced with Photoscan will be compared to the existing municipal data and maps. GCPs'
coordinates on ground are measured with GNSS NRTK and supplied in reference system
SWEREF99 15 00 and RH2000. GCPs' plane coordinates on the produced orthophotos are
identified using GIS application ArcMap. Altitude coordinates are identified in ArcMap from the
produced DEM files in Photoscan and from the raster folder GSD-Höjddata, grid 2+ provided by
Lantmäteriet which are also identified in ArcMap. These coordinates are tested for their absolute
and relative accuracy.
3.6.1 Position Accuracy with GCP
The computation of position accuracy follows the formulas listed below:
N = northing
E = easting
H = height/altitude
Average deviation
Radial offset in local plane
Radial offset (per GCP)
RMS error
(Lantmäteriet, 2015b, 2015c)
Standard deviation is based on the formula:
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3.6.2 Visual Control
The resulting orthophotos are subjected to control for completeness of content (holes), test of
alignment, residual tilt of high objects and objects' boundaries.
4 Results
4.1 Orthophoto and DEM
Four orthophotos in TIFF format and four DEMs in geotiff format are produced in Photoscan and
studied in ArcGIS ArcMap for their spatial accuracy. A 3D model in 3DS format is exported in
Photoscan. LAS data is also produced in Photoscan and then reprocessed in ArcMap to produce a
surface contour file in CAD format. One orthophoto is reproduced in FME workbench 2016 to
ecw format.
The resolution for orthophotos should not be less than the specification during photographing
(Lantmäteriet, 2015b) and therefore will be reduced to 0.019 m for orthophotos produced at 76
meters height and to 0.026 m for orthophotos produced at 105 meters height respectively.
Table 3. Exported file specifications for orthophotos, DEM and 3D model in reference system SWEREF 99 15 00 RH2000 EPSG:5848.
Production
no.
Orthophoto
File Format
Metadata
Size
Resolution
Pixel size
Total size in
pixels
1 ExportOrthomosaic76GCP.tif
ExportOrthomosaic76GCP.tfw
1712839 kb
1 kb 0.017 m 28154x25434
2 ExportOrthomosaic76NoGCP.tif
ExportOrthomosaic76NoGCP.tfw
2009661 kb
9kb 0.017 m 29385x26246
3 ExportOrthomosaic105GCP.tif
ExportOrthomosaic105GCP.tfw
804438kb
1kb 0.024 m 19564x18873
4 ExportOrthomosaic105NoGCPGeneric.tif
ExportOrthomosaic105NoGCPGeneric.tfw
1266541 kb
1kb 0.024 m 24350x21630
5 ExportDEM76GCPGeotiff.tif
ExportDEM76GCPGeotiff.tfw
432715 kb
1 kb 0.034 m 14670x14214
6 ExportDEM76NoGCP.tif
ExportDEM76NoGCP.tfw
591093 kb
1 kb 0.034 m 21625x20605
7 ExportDEM105GCP.tif
ExportDEM105GCP.tfw
2102234 kb
1 kb 0.047 m 9783x9441
8 ExportDEM105NoGCPGeneric.tif
ExportDEM105NoGCPGeneric.tfw
378500 kb
1 kb 0.048 m 16736x15581
9 Ecw76GCP.ecw 207166 kb
10
3DOrthoMeshTextureAdaptiveOrtho76GCP.3ds
3DOrthoMeshTextureAdaptiveOrtho76GCP.mtl
3DOrthoMeshTextureAdaptiveOrtho76GCP.jpg
1568885 kb
1 kb
3937 kb
11 LASSurfacecontour76GCP.dwg 1672 kb
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4.2 Spatial accuracy test (Absolute accuracy)
GNSS NRTK measured GCPs are compared with the approximate GCPs identified on the
orthophotos and DEMs and have the results as shown in tables 4 and 5. The complete and detailed
tables are found in appendix 5.
Table 4. Resulting accuracy test of orthophotos produced without the use of GCPs.
Table 5. Resulting accuracy test of orthophotos produced with use of 10 GCPs.
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4.3 Spatial accuracy test (Relative accuracy)
Relative accuracy is a test in scaling by comparing the distances between two points as measured
with GNSS NRTK against the corresponding points in the produced orthophotos.
Table 6. Summary of difference in distance between two GCPs in the four orthophotos in comparison against GNSS measured GCPs (in meters).
4.4 Parameters for orthophotos
Below is the table of parameters in accordance with HMK-standard 2 which is intended as guide in
surveying and mapping of urban cities in the municipalities' detailed development plans and
documentation (Lantmäteriet, 2015d).
Table 7. Parameters set for HMK-standard 2 as compared with resulting orthophotos produced with GCP.
Parameters HMK- standard 2 (in meters) Result from the project with GCPs
Geometric resolution
(planimetric/ altitude)
0.08-0.12 / 0.10 0.019-0.026
Standard deviation
(planimetric/ altitude)
0.08-0.12/0.12-0.18 0.694-0.720/0.777-0.783
Flight overlaps between transects (%) 60/30 60 % sidelap, 70 % frontlap
Color model PAN, RGB, CIR RGB
Pixel depth 8-16 bits 8 bits
Period in photographing Free from snow and leaf Free from snow
Angle of the sun (grader) <=30 Around 40 (12 noon)
4.5 GNSS measured GCP and Lantmäteriet Höjddata 2+
7.8 cm is deleted from GNSS GCP due to the box-typed signal GCP which has a height of 7.8 cm.
GCP 9 and 10 are to be ignored in this comparison for reason that Lantmäteriet Höjddata grid 2+ is
based on ground level while the GNSS measured GCP 9 and 10 are not based at ground level. It
must be noted that the resolution from Lantmäteriet is 2 meters per pixel. The comparison shows
the deviation in GNSS NRTK measured method from Lantmäteriet's database and indicates
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possible discrepancies as a result of the effect of resolution difference in the analysis of accuracy in
DEM data.
Table 8. Comparison between GNSS NRTK measured height and Lantmäteriet Höjddata 2+ (in meters).
4.6 Visual Control
Visual control is done on the orthophotos produced with flight heights of 76 meters with GCPs and
105 meters with GCPs.
4.6.1 Test for completeness of data
The resulting orthophoto shows a number of holes throughout the image (Figure 12).
Figure 12. Example of a hole.
4.6.2 Test of alignment
The results are observed for the alignment of hanging electric power lines. The power lines are
shifted from 0.5 to 1.5 meters. One type of alignment shift and distortion observed is due to
vegetation (Figure 13).
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Figure 13. Alignment error due to vegetation.
Another alignment shift is observed displacement as power lines have an offset of 1.2 meter
sideways (Figure 14) on one area of the orthophoto.
Figure 14. Broken power line with offset sideways.
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4.6.3 Residual tilt
Angular error (tilt) of electric poles is noticed (Figure 15). The height data for electric poles is not
available for computation of residual tilt in this project.
Figure 15. Angular error of electric pole.
On the positive side, noticeable tilts of the houses are not observed.
4.6.4 Scaling
The resulting orthophoto does not reflect the real house boundaries from the municipality's base
map (Figure 16).
Figure 16. Comparison of house perimeter from municipality's base map against produced orthophoto.
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5. Discussion
The results in the spatial accuracy tests of the orthophotos give an error with more than the average
RMS and standard deviation from past studies done by Samani (2013), Gunnarsson and Persson
(2013), Axelsson and Skoog (2013) and Jansson (2013). The results neither reflect the accuracy test
done by Agisoft Photoscan (Barry and Coakley, 2013) nor by Pix4D (Draeyer and Strecha, 2014).
During the assignment of ground markers in Photoscan, difficulty is experienced in finding the
center point for the GCP (see Figure 17 and Figure 18). It is impossible to identify the correct center
point of the GCPs as most appear to be blurry. This difficulty is observed in Gunnarsson and
Persson's project (2013) and in Mortensson and Reshetyuk's project (2015) as well.
Figure 17. Natural GCP 10. Center of a cement
block.
Figure 18. Center point for GCP 3.
Figure 19. Reflectance from white background.
Figure 20. Diffusion of a marker.
Reflectance from the white background dominates and wipes out the black triangles. The camera
lens is thus "blinded" by the whiteness of the ground marker (Figure 19). Diffusions of the triangles
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on the markers are also observed (Figure 20). Since the alignment horizontally and vertically and
scaling are highly depended on GCPs, this greatly affects the production of dense cloud.
The size and shape of the GCP affects its correct spatial identification. Maybe the triangle form can
be avoided. The formations shown in Figure 21 and Figure 22 can be more of an advantage
especially when the sun is high and cloud free.
Figure 21. Suggested design of GCP
(modified from Lantmäteriet's proposal).
Figure 22. Suggested GCP form
(Barry and Coakley, 2013).
Another factor to consider is the color and contrast of the ground marker as against the background.
It might be preferable to use another color that does not reflect as much as white. This
consideration is mentioned likewise in Gunnarsson and Persson's project (2013). The slope of the
terrain can also give disadvantage in determining the central point of the marker as the marker will
appear skewed (Figure 23).
Figure 23. Skewed GCP.
The produced DEM files there GCPs are not used give unanticipated results with several meters
deviation in altitude as seen when the DEM files are imported in ArcMap (Figure 24 and
Figure 25). For that reason, no further analyses are made with the DEMs produced when GCPs are
not used.
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Figure 24. DEM file, 76 meters, without GCPs. Figure 25. DEM file, 105 meters, without GCPs.
Due to the enormous difference in resolution, a few centimeters in DEMs as against two meters
with Lantmäteriets Höjddata grid 2+, data are not comparable and an analysis is therefore not
practical. It is therefore more realistic to make the comparison between DEMs and GNSS measured
GCPs.
Unexpectedly, the results from the 105 meters flight height gives better positional accuracy than the
results from 76 meters flight height with or without the use of GCPs. The RMS error at 76 meters
flight height with GCPs is 0.683 meter and 0.659 meter at 105 meters flight height. The RMS error
at 76 meters flight height without GCP is 2.292 meters while at 105 meters RMS error is 2.126
meters. On the other hand, DEM results give better altitude accuracy at flight height 76 meters than
105 meters with a few millimeters, with RMS error of 0.737 meter and 0.743 meter respectively. A
possible explanation is that alignment is probably better accomplished at the 105 meters flight height
as each image contributing to orthophoto production covers a larger area and results in a more
effective point matching but this needs to be proven. In Gunnarsson and Persson's project (2013),
their theory for GCP's influence on DEM is that GCPs are chosen horizontally and not vertically.
Likewise, scaling error is also observed throughout the orthophotos. Scaling is inconsequent in
different areas in each orthophoto as concluded from the relative accuracy test shown in table 6 in
which distances between two points are compared.
Due to the factor that photos having been taken in June where leaves have sprouted and matured
and grasses have grown high, the placement of the GCPs has not been ideally done as planned. It is
also observed that Photoscan fails to align images taken with tight vegetation and on water area.
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6. Conclusion
Assignment of GCPs plays a significant role during orthophoto processing for absolute easting,
northing and height position accuracy in a projected reference system. It is also important upon the
production of a more correctly scaled end-product. The consequence of not using GCPs gives
variety in NE deviation from GNSS NRTK measurements from a few decimeters to a few meters in
orthophotos. In the absence of GCP, the elevation in DEM is greatly displaced.
However, there is no significant difference in the absolute position accuracy test between
orthophotos produced with flight heights 76 and 105 meters, with or without the assignment of
GCPs. Lower flight height does not guaranty better results.
Some areas and objects in the orthophotos might be skewed or lacking in data (holes). Holes are
observed where leaves are concentrated and within water areas. Long vertical objects like electric
poles may not satisfy the objective of a real orthophoto in the sense that residual tilts are observed.
Not all vertical features are projected correctly even if the buildings seem to have right vertical angle.
Shift/side offset of hanging power lines gives doubt to proper alignment of hanging objects. It is to
be concluded that relief displacement is not completely ortho-rectified and the orthophotos are not
totally free from distortions.
For future studies, it might be preferable that GCPs are placed on flat horizontal ground and at
regular intervals with suitable color contrast and avoid overwhelming reflectance. The size of the
marker can be set depending on the resolution applied on the camera and the feature of the camera
lens. Height offset for markers is to be avoided. The flying speed of the UAV during image taking
can be tested for their impact on the spatial accuracy test of the produced orthophotos. Another
suggestion is in cases of difficult terrain where elevation difference is high, increase overlapping of
images is recommended. GCPs placement can be tested at regular intervals both horizontally and
vertically.
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References
Agisoft LLC. (2016a). Agisoft PhotoScan User Manual Professional Edition version 1.2. Agisoft LLC. (2016b). Dense Cloud Classification and DTM Generation with Agisoft PhotoScan Professional. Support
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Appendix
Appendix 1
1. Camera and Photoscan processing parameters General settings used in this project paper:
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Appendix 2
2. Coordinates of the ground markers
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Appendix 3
3. System requirements for Photoscan
For system requirements can be found at the Agisoft homepage
http://www.agisoft.com/downloads/system-requirements/.
RAM
In most cases the maximum project size that can be processed is limited by the amount of RAM
available. Therefore it is important to select the platform allowing installing required amount of
RAM.
See Memory Requirements on Agisoft website.
(http://www.agisoft.com/pdf/tips_and_tricks/PhotoScan_Memory_Requirements.pdf).
CPU
Complex geometry reconstruction algorithms need a lot of computational resources for processing.
A high speed multi core CPU (3GHz+) is recommended.
GPU
Agisoft PhotoScan supports OpenCL acceleration for dense cloud generation step (most time
consuming one), so high-end OpenCL-compatible graphics card can speed up the processing.
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Appendix 4
4. Processing steps in Photoscan
General settings used in orthophoto and 3D model processing.
Step 1. Photo alignment
Agisoft Photoscan uses common points on the photographs to match images, aligning these images
and calculate respective camera positions for each image. Alignment is done with the SFM, structure
for motion, technique. SFM detects geometrical similarities with specific details that serve as image
feature points. The movement of these points throughout the whole sequence in the workplace is
thereby monitored giving an estimation of feature point positions and subsequently rendered as
three-dimensional point cloud. When these are identified, Photoscan refines camera calibration
parameters to create point cloud data and a set of camera positions together with a list for alignment
errors. (Verhoeven, 2011).
At this step, point variance is calculated and three sigma filtering is applied before SFM algorithms
are applied. Camera adjustment is refined using a bundle-adjustment algorithm (Semyonov, 2011).
105 Flight height, alignment result 76 Flight height, alignment result
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Appendix 4 Step 2. Set markers
At this point GCPs are imported for georeferencing and their positions are identified on images
where applicable. Conversion as required depending on the reference system used in the images are
set inline with the reference system used by the GCPs (GCPs estimated vs. measured data error).
This information can be used to check whether the result fulfills one's project requirements for the
spatial and georeferencing accuracy.
Before conversion After conversion
Step 3. Building the dense cloud
Dense reconstruction algorithms are applied on the aligned image set operating on the pixel values
to build a geometric scene.
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Appendix 4 Step 4. Building mesh
Multiview stereo reconstruction handles fine details present on the scene and represent these details
as a mesh. Height field approach is recommended as default for aerial photography in the
reconstruction of terrain-like features (Verhoeven, 2011). The terrain model is a result of the
triangulation of the points in the mesh .
Apply topology fix when applicable on the resulting mesh.
Step 5. Building texture
The mapping mode orthophoto is used in processing nearly planar geometry. This mapping method
implements an adaptive parameterization approach in Photoscan. Horizontal surfaces are mapped
with orthophoto parameterization mode while vertical regions are mapped using generic mapping
mode when building texture. This option is therefore recommended in processing aerial
photographs.
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Appendix 4
Step 6. Building DEM and orthomosaic
Photoscan uses the TIN surface to correct for terrain displacement and calculated exterior
orientations for georeferencing in the orthorectification process (Agisoft Wiki, 2012). The surface
reconstruction algorithm is based on a modified Poisson surface reconstruction algorithm
(Semyonov, 2011).
1. 105 m flight height with GCP
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Appendix 4
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Appendix 4
2. 105 m flight height without GCP
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Appendix 4 3. 76 m flight height with GCP
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Appendix 4 4. 76 m flight height without GCP
.
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Appendix 4 Chunks summary:
1. 76 m flight height with GCP
2. 105 m flight height with GCP
3. 76 m flight height without GCP
4. 105 m flight height without GCP
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Appendix 5
5. Computation tables
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Appendix 5
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Appendix 5 Relative spatial accuracy test
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Appendix 6
6. Orthophoto produced from images taken at 105 m flight height and with
assignment of 10 GCPs.
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Appendix 7
7. GCPs' position comparison
7.1 GNSS measured vs. 105 m flight height and 76 m flight height, with GCP.
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7.2 GNSS measured vs. 105 m flight height and 76 m flight height, without GCP.