D1.1 Technologies and Challenges Report - MOMIT Project · 2018-03-05 · D1.1 – Technologies and...
Transcript of D1.1 Technologies and Challenges Report - MOMIT Project · 2018-03-05 · D1.1 – Technologies and...
Grant Agreement No: 777630
Project Acronym: MOMIT
Project Title:
Multi-scale Observation and Monitoring of railway Infrastructure
Threats
A project co-funded by the European Union’s Horizon 2020 – Shift2Rail Programme
for research, technological development and demonstration
D1.1
Technologies and Challenges Report
This Document is composed by 48 pages, including attachments
Last revision date: 2018-01-30
MOMIT - Multi-scale Observation and Monitoring of railway Infrastructure Threats GA No: 777630
Project co-funded by the European Union’s under the H2020 – S2R Programme
D1.1 – Technologies and Challenges Report – v1.0 Page 2 of 48
Deliverable information
Document Configuration
Programme Name: Shift2Rail
Call: H2020-S2RJU-2017
Topic: S2R-OC-IP3-03-2017
Proposal Number: 777630
Grant Agreement Number: 777630
Project Acronym: MOMIT
Project Title: Multi-scale Observation and Monitoring of railway Infrastructure Threats
Deliverable Number: D1.1
Title of the Deliverable: Technologies and Challenges Report
Work-Package: WP1
Issue date: 2018-01-30
Revision of the document: 1.0
Responsible Beneficiary: Terabee
Prepared by: Mateusz Sadowski (Terabee)
Reviewed by: Massimiliano Ruffo (Terabee)
Contributors: Elena Francioni (e-GEOS), Laura De Vendictis (e-GEOS)
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Revision History
Revision Date Author Organisation Description
V0.1 2017-11-30 Mateusz Sadowski TERABEE First draft issue
V0.2 2018-01-04 Elena Francioni e-GEOS New structures, minor changes
and introduction to chapter in
satellite technologies
V0.3 2018-01-09 Mateusz Sadowski TERABEE Revision of RPAS section and
introduction to Overview and
RPAS chapters
V0.4 2018-01-30 Elena Francioni, Laura
Devendictis
e-GEOS Contribution to satellite
technologies assessment
V1.0 2018-01-30 Mateusz Sadowski TERABEE Final review
V1.1 2018-01-31 Roberto Tomás UA Feedback on final review
Statement of originality
This document contains original unpublished work except where clearly indicated otherwise. Acknowledgement of
previously published material and of the work of others has been made through appropriate citation, quotation or both.
Disclaimer
The information contained in this document and any other information linked therein is confidential, privileged and it
remains the property of its respective owner(s). As such, and under the conditions settled in the MOMIT Grant Agreement
and the MOMIT Consortium Agreement, it is disclosed for the information of the intended recipients within the MOMIT
Consortium and the European Commission / Shift2Rail JU according to its “Dissemination Level”* and may not be used,
published or redistributed without the prior written consent of its owner(s).
* PU = Public, CO = Confidential, EU-R/R-UE = Classified, information as referred to in Commission Decision
2001/844/EC.
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Project co-funded by the European Union’s under the H2020 – S2R Programme
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Table of Contents 1 Executive Summary 9
2 Overview of unmanned technologies 10
3 RPAS for assets monitoring 10
3.1 Remotely Piloted Aircraft Systems 10
3.1.1 VTOL aircraft 11
3.1.2 Fixed wing aircraft 12
3.2 RPAS equipments 13
3.2.1 Visible light cameras 13
3.2.2 UV cameras for corona effect inspection 14
3.2.3 Thermal cameras 16
3.2.4 Multispectral cameras 17
3.2.5 SAR (Synthetic Aperture Radar) 18
3.2.6 LIDAR systems 19
3.3 RPAS control systems and safety 22
3.3.1 Autopilots 22
3.3.2 Object avoidance systems 23
4 Satellite technologies for asset monitoring 25
4.1 SAR Satellite systems 27
4.1.1 COSMO-SkyMed data 29
4.1.2 TerraSAR-X 31
4.1.3 Sentinel-1 32
4.1.4 RADARSAT 2 34
4.1.5 ALOS-2 35
4.2 Optical Satellite system 36
4.2.1 DigitalGlobe Constellation 40
4.2.2 Pleiàdes Constellation 43
4.2.3 Spot 6/7 Constellation 43
4.2.4 Deimos-2 44
4.2.5 RapidEye Constellation 44
4.2.6 Sentinel-2 Constellation 45
5 Conclusions and Recommendations 46
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List of Tables Table 3-1– GSD for multiple camera-lens combinations. Fov is the angular Field of View, Ny is the
number of pixels in the y direction and Py is the length in meters for each pixel in the y
direction..............................................................................................................................................13
Table 3-2– Parameter comparison of CoroCAM 8 and DayCor Swift cameras……………………15
Table 3-3 - Comparison of key parameters of Workswell WIRIS 640 and Flir Vue Pro R 640…...17
Table 3-4 - Comparison of key parameters of Parrot SEQUOIA and Micasense RedEdge………..17
Table 3-5 - Wavelengths and their application in multispectral surveying…………………………18
Table 3-6 - LidarPod parameters……………………………………………………………………20
Table 3-7 - Key parameters of Veronte Autopilot…………………………………………………..22
Table 3-8 - Key parameters of Pixhawk 2 Autopilot……………………………………………….23
Table 4-1 - Main available operational SAR sensors and their key characteristics………………...29
Table 4-2 - COSMO-SkyMed Technical Specification…………………………………………….31
Table 4-3 - TerraSAR-X Technical Specification…………………………………………….…….32
Table 4-4 - Sentinel-1 Technical Specification……………………………………………….…….33
Table 4-5 - Radarsat-2 Technical Specification……………………………………………….……35
Table 4-6 - ALOS-2 Technical Specification…………………………………………………….…36
Table 4-7 - Main operational optical sensors (resolution <= 10 m) and their key characteristics….40
Table 4-8 - GeoEye-1 Sheet…………………………………………..…………………………….41
Table 4-9 - WorldView-1 Sheet…………………………………………………………………….41
Table 4-10 - WorldView-2 Sheet…………………………………………………………………...42
Table 4-11 - WorldView-3 Sheet…………………………………………………………………...42
Table 4-12 - WorldView-4 Sheet…………………………………………………………………...43
Table 4-13 - Pleiades Sheet…………………………………………………………………………43
Table 4-14 - Spot 6/7 Sheet…………………………………………………………………………44
Table 4-15 - Deimos-2 Sheet………………………………………………………………………..44
Table 4-16 - RapidEye Sheet………………………………………………………………………..45
Table 4-17 - Sentinel-2 Sheet……………………………………………………………………….45
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Project co-funded by the European Union’s under the H2020 – S2R Programme
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List of Figures Figure 3-1 Harrier Industrial; heavy duty coaxial octocopter by VulcanUAV .................................. 11
Figure 3-2 - Vapor 55 RPAS helicopter............................................................................................. 12
Figure 3-3 - QuestUAV fixed wing aircraft ....................................................................................... 12
Figure 3-4 - Ofil DayCor Swift .......................................................................................................... 16
Figure 3-5 - Visualization of laser energy vs tree height ................................................................... 19
Figure 3-6 - Visualization of TeraRanger Tower coverage at distances up to 2m ............................ 24
Figure 4-1 - Overview of available Satellite for Earth Observation .................................................. 26
Figure 4-2 - Side looking geometry of a SAR satellite ...................................................................... 27
Figure 4-3 - Etna (Italy) COSMO-SkyMed Spotlight image (1m resolution). © ASI ...................... 27
Figure 4-4 - 3 typical effects of the SAR images.. ............................................................................. 28
Figure 4-5 - X band sensors main characteristics .............................................................................. 29
Figure 4-6 - COSMO-SkyMed data collection opportunities ............................................................ 30
Figure 4-7 - COSMO-SkyMed imaging Modes ................................................................................ 30
Figure 4-8 - TerraSAR-X imaging modes ......................................................................................... 32
Figure 4-9 - Sentinel-1 imaging modes.............................................................................................. 33
Figure 4-10 - Radarsat-2 imaging modes ........................................................................................... 34
Figure 4-11 - Alos-2 imaging modes ................................................................................................. 35
Figure 4-12 - Collection scenarios ..................................................................................................... 38
Figure 4-13 - DigitalGlobe constellation ........................................................................................... 40
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Acronyms and Abbreviations
ASI Agenzia Spaziale Italiana (Italian Space Agency)
BI Business Insider
DG DigitalGlobe
DoA Description of Action
EC European Commission
ESA European Space Agency
GNSS Global Navigation Satellite System
INS Inertial Navigation System
IMU Inertial Measurement Unit
LIDAR Light Detection and Ranging
MP/MPx Megapixel
PTP Picture Transfer Protocol
RPAS Remotely Piloted Aircraft System
RTK Real-Time Kinematics
SAR Synthetic Aperture Radar
TRL Technology Readiness Level
TT&C Telemetry, Tracking, and Command
UAV Unmanned Aerial Vehicle
UV Ultra Violet
VTOL Vertical Takeoff and Landing remotely piloted vehicle
WV WorldView
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Project co-funded by the European Union’s under the H2020 – S2R Programme
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Technologies and Challenges Report
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Project co-funded by the European Union’s under the H2020 – S2R Programme
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1 Executive Summary
The goal of this technology survey is to assess available unmanned and/or remotely piloted
technologies suitable to respond to the needs of the field of railways infrastructure monitoring.
The two reference technologies that will be analysed are Remotely Piloted Aircraft Systems (RPAS)
and Satellite systems.
Both systems are able to be equipped with different sensors (optical, from UV to thermal bands, radar)
and therefore to perform different analysis as response to different needs.
Moreover, the specific characteristics of the two systems make it possible to cover one of the main
needs infrastructure management: frequent monitoring with high and very high detail, and over wide
areas along the infrastructure.
The report will focus on state of the art technologies, even if in some cases some earlier version or
something slightly different might be chosen for the scope of this project.
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2 Overview of unmanned technologies
RPAS and satellite system are the two unmanned and remotely controlled instruments covered in this
report. The advantage of using both of those types of instruments is their complementarity for the
infrastructure monitoring.
RPAS allow acquiring data at higher resolution than satellite systems (large scale monitoring) and
the ability to vary payloads depending on mission requirements make them more flexible than satellite
system. The RPAS come with multiple limitations such as a need for a certified pilot and flight
authorization, optimal weather conditions etc.
In comparison, satellites allow to survey wide areas, without a need for a pilot and, contrary to RPAS,
a radar payload can work in any weather conditions. Satellites come with lower flexibility in terms
of acquisition as passages over the area of interest are predefined. Lower resolution of captured data
combined with the wide coverage make satellite systems better suited for small scale (from 1:2500)
monitoring.
3 RPAS for assets monitoring
RPAS is one of the areas of technologies studied for the purpose of this technological analysis. The
first part of this section covers both Vertical Takeoff and Landing (VTOL) as well as Fixed Wing
platforms listing both the advantages and disadvantages of those systems with regard to the scope of
the MOMIT project.
Second part of this chapter discusses state of the art payload options for infrastructure monitoring,
taking into account their Technology Readiness Levels, price and ease of integration on an RPAS
platform.
Finally, different modes of RPAS control are explained and autopilots for RPAS systems are
discussed, taking into account safety options and implications as well as supporting systems for
obstacle avoidance.
3.1 Remotely Piloted Aircraft Systems
Use of RPAS for service tasks has been steadily growing over the past few years. BI Intelligence in
its report from August 20171 predicts the value of drone market for Infrastructure industry to pass
over $45 billion by year 2021.
Several technologies are available for this purpose, with different characteristics enabling different
applications and responding to different users needs in the field of infrastructure management.
1 http://www.businessinsider.fr/us/commercial-uav-market-analysis-2017-8/
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The two main families are Vertical Take-Off and Landing (VTOL) aircrafts and Fixed Wing aircrafts.
In the following, an overview of these RPAS technologies is provided in order to frame their
characteristics and main applications capabilities.
3.1.1 VTOL aircraft
Vertical Take-Off and Landing (VTOL) aircraft are capable of hovering, taking off and landing
vertically. Typical VTOL platforms present on the market are helicopters and multi-rotors.
The hovering capability of VTOL vehicles combined with capability of moving in any direction
makes them ideal for detailed structure monitoring and inspection applications.
The main disadvantage of conventional VTOL aircraft compared to fixed wing aircraft is shorter
flight time, requiring multiple flight campaigns to survey large areas.
Multi-rotors
Multi-rotors are rotary wing aircraft with more than two rotors. Typically the multi-rotors on the
market come in 4 (quadro-), 6 (hexa-), 8 (octo-)(Figure 3-1) rotor configurations, sometimes in a
coaxial configuration (two rotors per single arm). The advantage of Multi-rotors over other VTOL
systems like helicopters is the lack of mechanical complexity, significantly reducing maintenance
costs.
Figure 3-1 Harrier Industrial; heavy duty coaxial octocopter by VulcanUAV2
The advantage of multi-rotors with number of rotors higher than 4 is a theoretical increase in
redundancy; in case of a single motor/propeller failure the aircraft might still be controllable in pitch
and roll axes increasing the pilot’s chances to land safely.
Helicopters
The main advantage of helicopter RPAS platforms (Figure 3-2) in comparison to multirotor aircraft
is the increased flight time. The main disadvantage of helicopters compared to the multirotors is the
mechanical complexity of the mechanical links in rotor head, increasing maintenance time and costs.
2 http://vulcanuav.com/aircraft/
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Another limitation of helicopter RPAS is the difficulty of integrating flexible payloads as quite often
there is not much space in the platform undercarriage or because of the main rotor it is significantly
difficult to integrate payload that is meant to look upwards from the frame (e.g. for missions requiring
to fly under the bridges in order to inspect them).
Figure 3-2 - Vapor 55 RPAS helicopter
3.1.2 Fixed wing aircraft
Fixed wing aircrafts (Figure 3-3) consist of a rigid wing capable of generating lift by having a forward
airspeed. Fixed wings have much simpler structure than VTOL aircraft and their gliding capability
makes them use far less power to fly long distances and survey large areas, making them ideal to
monitor a linear infrastructure and the surrounding.
Figure 3-3 - QuestUAV fixed wing aircraft3
The disadvantage of fixed wing aircrafts is their need of runway that is clear of obstructions like trees,
power lines, buildings etc. In order to generate lift fixed wing aircraft have to be in constant movement
making it difficult to focus on a particular feature of infrastructure element. They also have very
limited capacity to switch payloads between missions if payloads differ in size and weight (this might
result in a shift of centre of gravity, making the flight unstable).
3 https://www.questuav.com/media/case-study/fixed-wing-versus-rotary-wing-for-uav-mapping-applications/
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Compared to multi-rotors a loss of thrust generating motor is not a critical problem with fixed wing
aircraft. If such event occurs, the pilot can glide the aircraft and land it safely.
3.2 RPAS equipments
3.2.1 Visible light cameras
In aerial surveying applications using visible light cameras one of the most important parameters one
should consider is Ground Sample Distance (GSD). GSD is a distance between pixel centres
measured on the ground for the images from air or space.
As a part of this report multiple cameras with lenses were analysed for GSD parameter. The following
formula was used for GSD calculations:
Where:
𝜃 - lens field of view in degrees
𝑟- altitude in meters for a flight
𝑁𝑥, 𝑦 - Number of pixels in the x or y direction
𝑔- effective pixel cover
𝑃- length in meters for each pixel of the camera
Technical specifications of three different high-end cameras were compared for this report:
● Sony a7R (36.4 MP)
● DJI Zenmuse X5S (20.8 MP)
● Hasselblad X1D (50 MP)
Table 3-1 summarizes the GSD values for the selected cameras with exemplary lenses. The fixed
parameters for calculations are altitude (50 m was chosen as a reference value, the actual flight
altitude depends on flight condition and mission requirements) and effective pixel cover (90%). The
GSD values presented are for the lowest resolution axis (Ny), making the calculations shown the
‘worst case’ scenario:
Camera Lens Lens fov[deg] Ny[px] Py[m]
Sony a7R Sony SEL35F28Z 63 4912 0.01243618156
Sony a7R Sony SEL28F20 75 4912 0.01480497805
DJI Zenmuse X5S DJI MFT 15mm f/1.7 ASPH Prime Lens 72 3965 0.01760735689
DJI Zenmuse X5S Olympus M.Zuiko Digital 17mm f/1.8 Lens 65 3965 0.01589553053
Hasselblad X1D Hasselblad XCD 3,5/30mm 71 6200 0.01110379721
Hasselblad X1D Hasselblad XCD 3,5/30mm 56 6200 0.008757924562
Table 3-1– GSD for multiple camera-lens combinations. Fov is the angular Field of View, Ny is the number of pixels in the y
direction and Py is the length in meters for each pixel in the y direction.
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The above numbers show that with high-end commercial cameras it is possible to obtain GSD less
than 15 mm.
It has to be noted that choosing a camera with higher resolution in order to increase GSD comes at a
price of increased size footprint of each image that has an impact on needed storage. As an example
16 GB storage medium can hold on average 140 images taken by Hasselblad X1D (a resolution of
8272x6200 px), possibly increasing image processing time and storage costs. For comparison with
the same SD card at the highest resolution Sony a7R (7360x4912 pixels) could fit 196 images and
the DJI Zenmuse X5S (4608x3456 pixels) could fit 430 images.
Main characteristics of the considered camera are reported hereinafter.
Sony a7R
Sony a7R is a relatively small form factor camera (127x94x48 mm) weighing 471 g (including battery
and excluding lens) and the cheapest one of all cameras considered for this technical report. The 36.4
megapixel resolution ensures high GSD (less than 15 mm, depending on selected lens).
The added weight from the lense would make the total weight of this subsystem in range 591-671 g.
DJI Zenmuse X5S
DJI Zenmuse X5S is the lightest of all the compared cameras with a weight of 461 g (including
gimbal). At 20 MP it has the lowest resolution of all surveyed technologies, yet it still allows to obtain
a 20 mm GSD. The main disadvantage of DJI Zenmuse in an application sense is the fact of it being
highly proprietary and working only with DJI multi-rotors.
Hasselblad X1D
Hasselblad X1D is the most expensive camera selected for comparison in this report that comes with
50 MP sensor (8272x6200 resolution). The camera body weights 725 g (1275 g with Hasselblad XCD
3,5/30 mm lens) making it the heaviest camera subsystem of all surveyed technologies.
The lens proposed for the Hasselblad X1D can obtain GSD of 1.1 cm in y direction (lowest amount
of pixels) at 50 meters altitude. By reducing field of view the GSD can be increased further. Due to
the high resolution of this camera the 16 GB memory card can hold on average 140 images. With a
flight at 50 meters altitude and a 60% overlap between images this would allow to survey
approximately 34,000 square meters of land (equal to approximately 5 football pitches).
3.2.2 UV cameras for corona effect inspection
A corona discharge is an electrical discharge brought by ionization of a fluid surrounding a conductor that is
electrically charged. Spontaneous corona discharges occur naturally in high-voltage systems unless steps are
taken to limit the electric field strength around the conductor4.
4 https://en.wikipedia.org/wiki/Corona_discharge
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The corona effect is an unwanted side effect in high voltage electric power transmission, as they constitute a
significant amount of energy. Additionally the gases produced as a result of corona discharge are corrosive
which can lead to further damage to the high voltage equipment.
The corona activities radiate energy in the form of light in ultraviolet band of electromagnetic spectrum (300-
400 nm) with spectral peaks at 340 and 360 nm. The small portion of corona energy radiates in the solar blind
spectrum (below 280 nm). The solar blind spectrum is preferable for corona effect monitoring as the ozone
layer blocks the light below 280 nm spectrum5.
In this report two systems for corona effect inspection are compared:
● Ofil DayCor Swift
● Uvirco CoroCAM 8
Parameter DayCor Swift CoroCam 8
Weight 1.4 kg 2.5 kg
Dimensions 247x125x73mm 215x200x155mm
UV sensitivity 2.6x10-18 W/cm2 2.05x10-18 W/cm2
UV resolution Not specified 640x480 pixels
IR resolution Not specified 640x512
Visible Light resolution Not specified 768x576 pixels
Spectral range 240-280 nm Not specified
External power consumption 6.5-10 V, 14 W N/A (Built in battery)
Communication interface RS-232 USB 2.0, Ethernet
Table 3-2– Parameter comparison of CoroCAM 8 and DayCor Swift cameras
Ofil DayCor Swift
DayCor Swift was designed to fit on RPASs and small aircraft. The camera is appropriate for standard tripod
and gimbal mounts and comes with stabilizing plate making it easy to interface with an aircraft. With a weight
of 1.4 kg DayCor Swift is one of the lightest UV cameras on the market.
5 http://www.specialcamera.com/MC/MCAM_Dev.pdf
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Figure 3-4 - Ofil DayCor Swift6
Being specifically built for a purpose of equipping on aerial systems, considering the purpose of this report its
Technology Readiness Level (TRL) is the highest of all of the compared cameras.
Uvirco CoroCAM 8
Uvirco CoroCAM 8 is a handheld camera for corona effect inspections. The advantage of this camera is the
combined FLIR thermal IR camera, missing in the DayCor Swift one. Since the camera is a handheld system
its main disadvantage is a need for system modification in order to integrate it with other systems on the
platform.
3.2.3 Thermal cameras
According to the demonstrators to be realized within the project, thermal cameras will be also used
for security monitoring of railway network or hotspot detection. For this technology comparison, two
camera models were selected: Workswell WIRIS 640 and FLIR Vue Pro R 640. Table 3-3
summarizes both of the considered systems.
Parameter Workswell WIRIS 640 FLIR Vue Pro R 640
Resolution 640 x 512 pixels 640 x 512 pixels
Dimensions 135 x 77 x 69 mm 57 x 44 x 44 mm
Weight < 390 g 92 - 110 g
Spectral Range 7.5 – 13.5 μm 7.5 – 13.5 μm
RGB camera 1600 x 1200 pixels N/A
Interfaces PWM, SBUS, External trigger, PWM, USB, Mavlink
Sensitivity 0.05°C (50mK)
0.03°C (30mK) available on request
No information in datasheet
Temperature
ranges
-25°C to +150°C
-40°C to +550°C (optional +1 500°C on
request)
-25°C to +135°C
-40°C to +550°C
6 http://www.ofilsystems.com/products/rompact.html
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Accuracy ± 2% or ± 2°C (In high temperature range
0°C to +550°C)
+/-5°C or 5% of reading in -25°C to +135°C
range
+/-20°C or 20% of reading in -40°C to +550°C
range
Built-in memory 32 GB Depends on SD card
Table 3-3 - Comparison of key parameters of Workswell WIRIS 640 and Flir Vue Pro R 640
Both cameras have comparable parameters with only differentiating parameter being an RGB camera
on-board WORSKWELL WIRIS 640 and smaller footprint and weight in the case of the FLIR
solution. The final sensor selection can be done after all customer requirements are identified (e.g.
the need of RGB video feed together with thermal camera feed).
3.2.4 Multispectral cameras
For the purpose of this report, two widely available multispectral cameras are covered: Parrot
SEQUOIA and Micasense RedEdge. Table 3-4 shows the comparison of two systems with detailed
information on each camera in the following subsections.
Item Parrot SEQUOIA Micasense RedEdge
Bands 4 (Green, Red, Red Edge, Near-infrared) 5 (Blue, Green, Red, Red Edge, Near-infrared)
RGB camera 16 MPx 3.6 MPx
Dimensions 56 x 41 x 28 mm 121 x 66 x 46 mm
Weight 135 g 180 g
GSD at 100m 13 cm/pixel 8.1 cm/pixel
Interfaces WiFi, Serial (PTP) Serial, Ethernet, WiFi, External trigger, GPS
Other - Custom bands (400-900nm)
Table 3-4 - Comparison of key parameters of Parrot SEQUOIA and Micasense RedEdge
The Table 3-5 shows wavelengths captured by all mentioned cameras together with their applications:
Color Wavelength Application
Blue 450-520 nm deep water imaging (up to 50 m)
Green 520-600 nm vegetation and water imaging (up to 30 m in
clear water)
Red 600-690 nm imaging vegetation, man made objects, soil,
vegetation
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Red-edge 680-730 nm vegetation
Near-infrared 750-900 nm vegetation
Table 3-5 - Wavelengths and their application in multispectral surveying7
Parrot SEQUOIA
Parrot SEQUOIA is the most affordable multispectral camera covered in this section. It can provide
readings in 4 bands; Green, Red, Red Edge and Near-infrared. The advantage of this camera over
MicaSense RedEdge is its small size and weight and a good resolution built-in RGB camera.
The main disadvantage of SEQUOIA is the small amount of interfaces with autopilot: only serial
interface using Picture Transfer Protocol is supported, otherwise a WiFi connection has to be used to
set up camera trigger options. This is a clear disadvantage as most of the autopilots allow manual
triggering of a camera in order to capture images.
Micasense RedEdge
The Micasense RedEdge has 5 bands (compared to 4 on SEQUOIA) and, in addition, their
wavelength can be customized. The number of interfaces allows a full control of camera triggering
by any autopilot.
The size and weight of a camera should not be a concern given the foreseen payload capabilities of
the platform.
3.2.5 SAR (Synthetic Aperture Radar)
Synthetic Aperture Radar is a well established remote sensing technique. The radar system transmits
frequency modulated, high energy pulses at a high frequency. The backscattered echoes are received
back by the radar and stored in memory. Small antenna length used in the SAR systems guarantees
illuminating each point on the ground by thousands of pulses. The captured data can be then processed
to obtain high resolution 2D or 3D images of the terrain8.
SAR technologies have high TRL as they are used extensively by Space & Defence sector, even
though as Satellite systems and not as equipment of an RPAS system.
The technology research performed for this working package of MOMIT project returned only a
single result of a SAR radar suitable for RPAS and available commercially whose main characteristics
are reported here below.
Anyway, it is important to point out that, due to budget constraints, high price of the SAR for RPAS
systems and specific requirements on flight mode and flight altitude needed for the analysis derived
by SAR data, in the MOMIT project only satellite SAR systems will be considered.
7 https://en.wikipedia.org/wiki/Multispectral_image, https://en.wikipedia.org/wiki/Red_edge 8 http://ieeexplore.ieee.org/document/4142964/
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SAR Aero radar
SAR Aero develops, engineers, sells and integrates compact airborne Synthetic Aperture Radar
(SAR) systems at a commercial cost. This makes the SAR systems appropriate for manned and
unmanned U.S. government or commercial remote sensing missions9. SAR Aero claims to have
produced a low footprint SAR with dimensions 18.5 x 11.4 x 14.2 cm and weighing only 1.8 kg. The
advertised resolution is 0.3 to 3 meters and a working range of 1-10 km10.
3.2.6 LIDAR systems
There is a vast range of LIDAR systems available on the market that are readily available for drones.
In certain scenarios, the advantage of LIDAR systems over photogrammetry for ground surveying is
the ability of recognizing multiple laser reflections in the signal. This feature of LIDAR scanners is
especially useful in scenarios where trees or bushes cover the ground. In fact, the ability to filter
multiple return values from a LIDAR allows to distinguish ground reflection resulting in a good
quality ground model.
Figure 3-5 - Visualization of laser energy vs tree height11
The presented products below are often based on existing LIDAR scanner technology (e.g. Velodyne
LIDARS) and often include another layer of hardware and software (for communication, precise
positioning or data processing).
9 http://saraero.com/about/ 10 http://saraero.com/store/radar-electronics/ 11 https://earthobservatory.nasa.gov/Features/ForestCarbon/page5.php
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Routescene LidarPod
Routescene LidarPod is based on Velodyne HDL-32e LIDAR. The complete payload weight is 2.8
kg with dimensions of 320 mm length and 100 mm diameter. The power supply voltage is 12-50 vDC
and typical power is 28W.
LidarPod comes with a GNSS fused Inertial Navigation System including RTK (Real-Time
Kinematics) system. The advertised features are presented in Table 3-6.
Parameter Value
Horizontal Position Accuracy (with
RTK)
0.008 m
Vertical Position Accuracy (with RTK) 0.015 m
Roll and Pitch Accuracy 0.15°
Heading Accuracy 0.07° (with 2 m GNSS antenna spacing)
Internal Filter Rate 1000 Hz
Output Data rate up to 100 Hz
Table 3-6 - LidarPod parameters
The LIDAR sensor on-board LidarPod has a range of up to 100 meters (minimum range of Velodyne
HDL-32e is 1 meter). It captures up to 700,000 points per second and provides two return values
(strongest and the last return) in dual return mode. The horizontal field of view of LidarPod is 41
degrees.
Phoenix Ranger-UAV
Phoenix Ranger-UAV is the heaviest LIDAR solution covered in this section with a weight of 5.44
kg and dimensions of 308 x 180 x 129 mm for the sensor and 161 x 118 x 96 mm for the navigation
system. The power consumption is 90W at 12-28V.
Similarly to LidarPod this system comes with a navigation system. The positioning accuracy is 1cm
+ 1ppm RMS horizontal.
The LIDAR sensor included provides up to 920 m range at 60% reflectivity (minimum range for this
system is 3 meters). It is capable of capturing up to 500,000 measurement points per second. Ranger-
UAV provides up to 7 returns per single pulse.
Phoenix Scout
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Phoenix Scout is a 1.65 kg system based on Velodyne Puck LIDAR scanner. With dimensions of 160
x 116 x 116 mm it is the smallest and lightest system covered in this section.
The navigation system has similar characteristics to the one covered in Phoenix Ranger-UAV system
with a position accuracy of 1cm + 1 ppm RMS horizontal.
The Velodyne Puck LIDAR has a range of up to 120 meters. Similarly to Velodyne HDL-32e it can
output up to 2 returns per pulse and produce up to 600,000 points a second (in dual return mode). The
vertical field of view of this system is 30 degrees (+15.0° to -15.0°).
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3.3 RPAS control systems and safety
3.3.1 Autopilots
Autopilots are the crucial elements of any flight system as they manage aircraft state, handle
stabilization and interpret operator’s requests and transform them to an appropriate action (e.g.
change in altitude, velocity, angle etc.).
All commercial autopilots come with multiple flight modes:
● Low level control modes - allows for direct control of thrust and rotation rates (rates or
acrobatic mode) or angles (attitude mode) around all axes
● High level control modes - allows for control of climb rate and groundspeed
● Automatic mode - allows the aircraft to fly predetermined path or waypoints (requires GPS
or another positioning system)
● Autonomous mode - the system computes the flight path during operation based on
information from various sensor sources. This mode has low TRL and is usually not available
on commercial systems
Veronte autopilot
Embenton Veronte Autopilot is a high reliability avionics system for advanced RPAS control, highly
customizable and supporting multiple payloads and peripherals.
The Table 3-7 is a summary of key system features.
Parameter Value
Interfaces 1x I2C, 1x UART, 2x CAN Bus, 1x RS232,
1x RS485
PWM Up to 16
Power supply 2 x (6.5 - 36V) DC, 8 - 18 W
GNSS positioning Dual GNSS, RTK & RTCM, GLONASS
Platform types Multirotors, Planes, VTOL etc.
Dimensions and weight 65 x 38 x 65 mm, 190 g (90 g without
enclosure)
Table 3-7 - Key parameters of Veronte Autopilot
The clear advantage of Veronte Autopilot over Pixhawk 2 (reported below) is the safety (the optional
configurations involve a triple or quadruple redundant systems ) and specific certifications (Veronte
autopilot accomplishes among others DO-178C - Software Considerations in Airborne Systems and
Equipment Certification - standard12).
12 https://products.embention.com/veronte/uav-autopilot
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Pixhawk 2 autopilot
Pixhawk 2 is an open source autopilot with triple redundant Inertial Measurement Unit (IMU). The
advantage of using an open source solution is the ability to modify source code to develop custom
functionality of the system (e.g. indoor navigation).
The Table 3-8 summarizes key features of the Pixhawk 2.
Parameter Value
Processor 32bit STM32F427 Cortex M4, 168 MHz,
256 KB RAM, 2 MB Flash, 32 bit
STM32F103 failsafe co-processor
Interfaces 5x UART, 2x CAN, S.BUS, Spektrum
DSM, PPM, RSSI, I2C, SPI
PWM 8 PWM channels with failsafe and manual
override, 6 auxiliary.
Power supply Triple redundant (power module input at
4.8-5.4V), Servo rail input (4.8V to 5.4V),
USB power input (4.8V to 5.4V)
GNSS positioning Here+ RTK ready GNSS system
Platform type Multi-rotors, Planes, VTOL etc.
Dimensions and weight 95 x 45 x 30 mm, 75 g (including enclosure)
Table 3-8 - Key parameters of Pixhawk 2 Autopilot13
The low price of this solution coupled with thousands of flight hours performed by the community
using the available software for Pixhawk 2 (ArduCopter and Px4) make it an attractive autopilot to
include in the system.
The potential issues with using Pixhawk 2 is the lack of involvement of formal methods testing in
software production and lack of certification.
3.3.2 Object avoidance systems
At the time of writing this report, no standalone object avoidance system was identified on the market.
Terabee produces a TeraRanger Tower solution, which supports basic object avoidance for Pixhawk
2 autopilot (with ArduCopter firmware). With current sensor setup the objects of width of more than
1.44 meters (further referred to as blind spot) can be reliably detected in the sensor’s field of view at
a distance of 2 meters as shown on the Figure 3-6.
13 http://www.proficnc.com, https://pixhawk.org/modules/pixhawk2
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Figure 3-6 - Visualization of TeraRanger Tower coverage at distances up to 2m
The experience of Terabee in sensor development, robotics control and navigation has allowed to
develop a state of the art robust obstacle avoidance system for increased safety of operations and
personnel. The developed system could also be used as an indoor positioning system in GPS denied
environments.
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4 Satellite technologies for asset monitoring
Earth Observation Satellite technology has grown a lot in the recent years in terms of capability,
availability and application. In fact, if it’s true that from a technological point of view, new satellite
platforms, new higher resolution sensors and new satellite constellations with lower revisit time are
available, completely new opportunities of satellite data exploitation have been opened by the
Copernicus Programme which has cut to zero the costs for data in medium resolution.
The Copernicus Programme, has been specifically designed to meet the needs of the Copernicus
services and their users. In particular, Copernicus is served by a set of dedicated satellites (the Sentinel
families) and some contributing missions. Since the launch of Sentinel-1A in 2014, the European
Union set in motion a process to place a constellation of almost 20 more satellites in orbit before
2030. Concerning the possible use of Copernicus Data in infrastructure monitoring, it is important
to note that the medium resolution of Sentinel data is not always the most suitable for infrastructures
monitoring. Indeed, in this field, very high detail is usually needed. Anyway, the possibility to access
freely to satellite data has allowed to develop new application and use case and to refine the already
consolidated ones.
The two main classes of satellite sensors useful for railways monitoring, and in general for
infrastructure monitoring, are the passive sensor and active sensors: technologies completely different
and able to provide different information and therefore enabling several kind of applications.
The term Passive Sensor refers to sensor able to capture electro-optical or simply optical
electromagnetic waves of the sunlight and/or the emitted infrared radiation reflected or emitted by
objects on the ground. There are many commercial optical satellite systems available, commercial
and free: some of them are Landsat, Pléiades, DigitalGlobe constellation (GeoEye and WorldView),
but also the Copernicus Sentinel 2 sensors. With respect to active sensors, Optical/thermal data
allows usually an easy interpretation of the image that appears as a standard photograph, and therefore
are particularly indicated when a classification/identification of objects and changes is needed.
The term Active sensors commonly refers to SAR (synthetic aperture radar) data. Being active means
that the sensor generates itself the radiation and collects the signal reflected by the illuminated area
of interest. It means that these sensors could work day and night being independent by the sunlight.
Images collected by active sensors are more difficult to be interpreted being the information contained
both in the amplitude and in the phase components of the signal. Therefore, SAR data needs to be
processed in order to extract an intelligible information that, indeed, could provide very different data
with respect to the optical imagery. By the use of automatic and semiautomatic processing, it is
possible to derive millimetric deformation of ground and structures, anomalies/changes detection,
etc. Moreover, the wavelength of the electromagnetic field allows the signal to pass through the
atmosphere making these sensors operational independently from the weather conditions. Cosmo-
SkyMed, RADARSAT, TerraSAR-X and Sentinel 1 are just an examples of available active sensors.
In the following Figure 4-1, a wide overview of main Satellites sensors (optical and SAR) available
is represented. Then, the two technologies will be shortly described and some of main available
sensors listed and described in their main specifications.
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Figure 4-1 - Overview of available Satellite for Earth Observation
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4.1 SAR Satellite systems
SAR satellite are active sensors in the radar waves of the electromagnetic field. The reference to a
“synthetic aperture radar” and not simply to a radar is due to the need of large antennas for radar
frequencies that is not possible to mount on Satellites. Therefore, radar satellite operates in a
“synthetic aperture radar” systems with a side-looking geometry.
Figure 4-2 - Side looking geometry of a SAR satellite
Figure 4-3 shows an example of a high resolution SAR data.
Figure 4-3 - Etna (Italy) COSMO-SkyMed Spotlight image (1m resolution). © ASI
One of the main feature characterising SAR data is the signal wavelength:
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- X-band (~3.5 cm wavelength) as COSMO-SkyMed and TerraSAR-X
- C- band (~6 cm wavelength) as RADARSAT-2
- L-band (~24 cm wavelength) as ALOS-2
As already mentioned, one of the most important characteristic of this technology is the weather and
daylight independence: the wavelengths pass through clouds, emitting signal by themselves do not
require the sunlight.
On the other side with respect the above advantages, the analysis and interpretation of SAR images
is not as obvious as could be for optical data. In part this is due to the side looking geometry, whose
geometric characteristics cause some effects that distorted the image, so that objects can look different
in SAR images if acquired with a different incidence angle.
Figure 4-4 reports schematically the most important effects.
Layover
Foreshortening
Shadowing
Figure 4-4 - 3 typical effects of the SAR images. The real a, b, c positions are reported in the image as the a’, b’, c’ position, with a
clear distortion of the original positions.
SAR data’s resolution is influenced by several factors: acquisition mode, wavelength, bandwidth and
also incidence angle. For example, in the spotlight mode the same area is illuminated for a longer
time by the radar and this results in a higher resolution with respect to a “pass through” ScanSAR
mode.
A very important characteristic of the SAR systems is the possibility to set same acquisition
parameters (mode, incidence angle, polarization) and therefore to collect images that could be directly
compared. The received signal does not change if there aren’t any changes in the area. On the other
side, if there are changes they impact both the amplitude and the phase components of the received
signal. Being the two images acquired with the same parameters it is possible to highlight differences
due only to real changes in the area.
Based on this principle, it is possible to perform Change Detection analysis (mainly based on
differences in the signal Amplitude) and interferometric analysis (based on differences in the signal
phase, and therefore allowing to detect very small changes being the wavelength of the order of few
cm).
Table 4-1 and the related synthetic tables of the next paragraphs (Tables 4-2 to 4-6), summarize the
technical characteristics of main SAR mission\satellite sensor.
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Space asset Revisit time
(days) Swath (km) Polarization
Spatial
resolution (m)
Data archive
temporal
length
COSMO-
SkyMed 16 10-200 Single, Dual 1-100 2007-now
TerraSAR-X 11 10-100 Single, Dual,
Quad 1-18 2007-now
Sentinel-1 12 80-400 Single, Dual 9-50 2013-now
RADARSAT-2 24 20-500 Single, Dual,
Quad 1-100 2007-now
ALOS-2 14 25-490 Single, Dual,
Quad 1-100 2014-now
Table 4-1 - Main available operational SAR sensors and their key characteristics
4.1.1 COSMO-SkyMed data
The COSMO-SkyMed system is a constellation of four radar satellites (X-band) for Earth
Observation founded by the Italian Space Agency and the Italian MoD. COSMO-SkyMed is at the
forefront of technology and uses high-resolution radar sensors to observe the Earth day and night,
regardless of weather conditions. The constellation is fully operational since the 2008. Its purpose is
to monitor the Earth for the sake of emergency prevention (management of environmental risks),
strategy (defence and security), scientific and commercial purposes, providing data on a global scale
to support a variety of applications among which risk management, environment protection, natural
resources exploration, land management, defence and security.
The satellites are owned by the Italian Space Agency (ASI) and are operated by e-GEOS and
Telespazio under a service agreement with ASI. COSMO-SkyMed satellite constellation, in addition
to day/night and all weather data collection, provides unmatched performance in terms of image
resolution, revisit time, rapid coverage of huge territories, enabling the operation of application
services that are not possible with any other existing SAR satellite system.
Figure 4-5 - X band sensors main characteristics
The X-band allows very high resolution surveys, enabling the detection of detailed features, not
possible by C-band radar satellites (e.g. Sentinel 1) measurements. Moreover, the constellation of 4
satellites is a system able to image the whole world (including North and South Poles, which are
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prevented to the other SAR systems), offering superior data collection opportunities that are of vital
importance for activity of monitoring, surveillance and intelligence thanks, to the frequent acquisition
capability.
Figure 4-6 - COSMO-SkyMed data collection opportunities
All 4 satellites have the same payload. Figure 4-7 shows the different imaging modes of COSMO-
SkyMed.
Figure 4-7 - COSMO-SkyMed imaging Modes
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Mission/Satellite Sensor: COSMO-SkyMed
Operator Italian Space
Agency (ASI)
Spatial
Resolution
Single
polarisation
modes:
-Spotlight: 1 m.
-Stripmap: 3 - 15
m
-ScanSAR: 30 or
100 m
Two polarisation
mode (PING-
PONG): 15 m.
Revisit time 16 day repeat
cycle
Inclination 97,9 degrees Swath 10-200 km Altitude 619 km
Polarization
Single: VV, HH,
HV, VH
Dual: HH/HV +
VV/VH
Frequency
band
Microwave: X-
band, 9.6 GHz,
with choice of 5
polarisation
modes (VV, HH,
HV, VH,
HH/HV +
VV/VH)
Coverage Global
Data
distribution
policy
Commercial
license
Catalogue &
Access
ASI manages and coordinates institutional and scientific
users ordering by mean of the COSMO-SkyMED website
(http://www.cosmo-skymed.it/).
Commercial users can access the system through the
commercial provider e-GEOS (www.egeos.it).
Table 4-2 - COSMO-SkyMed Technical Specification
4.1.2 TerraSAR-X
TerraSAR-X was launched on June 15, 2007 and has been in operational service since January 2008.
In June 21, 2010 TerraSAR-X was joined by his twin TanDEM-X. The two satellites fly at a distance
of a few hundred metres and synchronously acquire data for DEM generation.
The TerraSAR-X satellite is operated from the Mission Control Center in Oberpfaffenhofen. In the
system baseline, two ground stations are in Germany: Weilheim is used as the TT&C station and
Neustrelitz serves as the central receiving station for the 300 Mbps X-Band downlink. Beyond that,
additional Direct Access Stations - commercial partners of Airbus - are available to extend the
baseline receiving station concept.
The incidence angles are ranging from 20 to 45 degrees, on both Right and Left looking sides (right
is the nominal look direction). Swath width is ranging from 5x10 km (SpotLight) to 100 km
(ScanSAR) and the resolution varies from 1 m (SpotLight) to 18.5 m (ScanSAR). TerraSAR-X
products are delivered on scene-basis.
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Figure 4-8 - TerraSAR-X imaging modes
Mission/Satellite Sensor: TerraSAR-X
Operator German Aerospace
Center (DLR)
Spatial
Resolution
Spotlight: 1.2 x 1 - 4 m
Stripmap: 3 x 3 - 6 m
ScanSAR: 16 x 16 m
Revisit
time
11 day
repeat
cycle
Inclination 97,44 degrees Swath 5-100 km Altitude 514 km
Polarization Single, Dual, Quad/Full Frequency
band
9.65 GHz, 300 MHz
bandwidth, all 4
polarisation modes
Coverage Variable
Data distribution
policy Commercial license
Catalogue
& Access
Catalogue: http://terrasar-x-archive.infoterra.de/
(http://www.geo-airbusds.com/en/2901-terrasar-x-
data-request-form). Table 4-3 - TerraSAR-X Technical Specification
4.1.3 Sentinel-1
The satellite carries a C-band Sentinel-1 is composed of a constellation of two satellites, Sentinel-1A
(launched on 2014) and Sentinel-1B (launched on 2016), sharing the same orbital plane with a 180°
orbital phasing difference with the goal providing C-Band SAR data continuity following the
retirement of ERS-2 and the end of the Envisat mission. The mission provides an independent
operational capability for continuous radar mapping of the Earth with enhanced revisit frequency,
coverage, timeliness and reliability for operational services and applications requiring long time
series.
Each Sentinel-1 satellite is in a near-polar, sun-synchronous orbit, with a 12-day repeat cycle and 175
orbits per cycle. A single Sentinel-1 satellite is potentially able to map the global landmasses in the
Interferometric Wide swath mode once every 12 days, in a single pass (ascending or descending).
The two-satellite constellation offers a 6 days exact repeat cycle at the equator. Since the orbit track
spacing varies with latitude, the revisit rate is significantly greater at higher latitudes than at the
equator.
Sentinel-1 satellites will operate in four modes has shown on the Figure 4-9:
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● Strip Map Mode: 80 km swath, 5x5 m spatial resolution
● Interferometric Wide Swath Mode: 250 km swath, 5x20 m spatial resolution
● Extra-Wide Swath Mode: 400 km swath, 25x100 m spatial resolution
● Wave-Mode: 20 km x 20 km swath, 5x20 m spatial resolution
Figure 4-9 - Sentinel-1 imaging modes
Mission/Satellite Sensor: Sentinel-1A and Sentinel-1 B
Operator European Space
Agency (ESA) Spatial
Resolution
- Strip mode: 9 m,
- Interferometric wide swath
mode: 20 m,
- Extra-wide swath mode: 50
m,
- Wave mode: 50 m
Revisit
time
Each
satellite: 6
days repeat
cycle at the
equator
Inclination 98,19 degrees Swath 80-400 km Altitude 693 km
Polarization
Single: HH, VV
Dual: HH+HV,
VV+VH
Frequency
band
C-band: 5.405 GHz; HH, VV,
HH+HV, V+VH; Incidence
angle: 20-45; MW (1.0 cm -
100 cm); C-Band (8 - 4 GHz)
Coverage Global
Data
distribution
policy
Full and open Catalogue
& Access
Registration is open to all users via simple on-line self-
registration accessible via the Sentinel Data Hub
(https://scihub.esa.int/). Table 4-4 - Sentinel-1 Technical Specification
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4.1.4 RADARSAT 2
RADARSAT-2 was launched on December 14, 2007. It is a follow-up mission to RADARSAT-1 and
has the same orbit, but provides new capabilities that include high resolution imaging, flexibility of
polarization, left and right looking imaging options. Its left looking capability allows the spacecraft
the unique capability to image the Antarctic on a routine basis providing data in support of scientific
research. The multiple mode capabilities of RADARSAT-2 respond to the evolving needs of clients
and encourage the development of specialized applications.
RADARSAT-2 can image using HV, VH, or VV polarization in contrast with RADARSAT-1 which
offered only HH polarization and also offers new UltraFine, WideUltraFine, ExtraFine, Ship
Detection, Ocean Surveillance, Multi-Look Fine, Fine Quad-Pol and Standard Quad-Pol beam
modes.
Nominal swath width ranges from 18x8 km (Spotlight) to 500 km (ScanSAR Wide). The resolution
of the different acquisition modes ranges from 1 m (Spotlight) to 100 m (ScanSAR Wide).
Figure 4-10 - Radarsat-2 imaging modes
Mission/Satellite Sensor: RADARSAT-2
Operator Canadian Space
Agency (CSA) Spatial
Resolution
Depending on
Acquisition
mode: from 1 to
100meters
Revisit time 24 day repeat
cycle
Inclination 98,6 degrees Swath 20-500 km Altitude 798 km
Polarization Single, Dual,
Quad
Frequency
band
Microwave: C
band 5.405 GHz.
HH, VV, HV,
VH polarization
Coverage Global
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- includes Quad,
100MHz
Bandwidth
Data
distribution
policy
Commercial
license
Catalogue &
Access
Catalogues are available to end-users either locally,
through the Acquisition Planning Tool, or by web through
the National Earth Observation Data Framework web
page at Natural Resources Canada.
(https://neodf.nrcan.gc.ca/neodf_cat3/index.php?lang=en
). Table 4-5 - Radarsat-2 Technical Specification
4.1.5 ALOS-2
ALOS-2 is the follow-on JAXA L-SAR satellite mission of ALOS (Daichi) approved by the Japanese
government in late 2008. The overall objective is to provide data continuity to be used for
cartography, regional observation, disaster monitoring, and environmental monitoring. The post-
ALOS program of JAXA has the goal to continue the ALOS (nicknamed Daichi) data utilization -
consisting of ALOS-2 (SAR satellite) and ALOS-3 (optical satellite) in accordance with Japan's new
space program.
The PALSAR-2 aboard ALOS-2 is an L-band Synthetic Aperture Radar (SAR) sensor, a microwave
sensor that emits L-band radio waves and receives their reflection from the ground to acquire
information. The PALSAR-2 has three imaging modes:
● Spotlight mode: The most detailed observation mode with 1 by 3 meters resolution
(observation width of 25 km)
● Strip Map mode: A high-resolution mode with the choice of 3, 6 or 10 meters resolution
(observation width of 50 or 70 km)
● ScanSAR mode: A broad area observation mode with observation width of 350 km or 490
km, and resolution of 100 m or 60 m respectively
Figure 4-11 - Alos-2 imaging modes
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Mission/Satellite Sensor: ALOS-2 (Palsar)
Operator
JAXA (Japan
Aerospace
Exploration
Agency)
Spatial
Resolutio
n
Spotlight mode (1 to 3 m),
Stripmap mode (3 to 10 m).
Ultra-fine mode: 3 m
High-sensitive mode: 6 m
Fine mode: 10 m
ScanSAR mode: 100 m
Revisit
time
14 day repeat
cycle
Inclination 97,9 degrees Swath 25-490 km Altitude 628 km
Polarizatio
n
Single: HH, VV,
HV, VH,
Dual: HH+HV,
VH+VV
Full:
HH+HV+VH+V
V
Frequenc
y band
Microwave:
L-Band 1270 MHz; MW (1.0 cm
- 100 cm)
L-Band (2 - 1 GHz)
Coverag
e Global
Data
distribution
policy
Commercial
licence
Catalogue
& Access Catalogue: https://www.gportal.jaxa.jp/gp/top.html
Table 4-6 - ALOS-2 Technical Specification
4.2 Optical Satellite system
Optical satellite sensors require the sun’s illumination for imaging. Depending on the system, passive
sensors typically record electromagnetic waves in the range of visible (~430–720 nm) and near-
infrared (~750–950 nm) light. Some systems, such as SPOT 5, also are designed to acquire images
in the middle-infrared wavelength (1,580–1,750 nm).
Because sensors feature specific wavelength sensitivity, acquisitions with an optical instrument are
separated into several images, depending on the mode. For multispectral sensors, such as SPOT 6 and
7 and Pléiades, it is common to separate image data into the three main spectral ranges—blue (~430–
550 nm), green (~500–620 nm) and red (~590–710 nm)—as well as an additional sensor for near
infrared (~750–940 nm). With the acquired dataset, the different wavelengths can be analyzed and
used as input for further processing or easier feature classification.
For hyperspectral systems, such as EnMAP, sensors cover smaller spectral ranges, and the spectral
range is extended into the infrared range to >2,000 nm. Acquisitions in panchromatic mode record
the area of interest with one sensor covering the entire spectral range of the visible light and the near
infrared (~470–830 nm). The panchromatic mode’s resolution is higher than the multi/hyperspectral
mode. The whole spectral range is covered, without separation among different wavelengths.
Because optical imaging is only possible with sun illumination, changes in the seasonal cycle have to
be considered when planning acquisitions. Furthermore, cloud coverage can hamper image collection,
as the sunlight is reflected by the clouds and recorded by the sensors. These two parameters limit
Earth observation with passive sensors, particularly in polar areas with seasonal changes in sun
illumination and the equatorial belt with persistent cloud coverage.
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Optical systems cannot bypass the cloud constraint. However, recent innovations with some satellite
systems enable mission operators to more frequently update tasking plans to accommodate cloud-
coverage forecasts. Compared with former optical systems, the resulting efficiency of cloud-free data
collection is highly improved. For example, the ratio of images collected with less than 10 percent of
clouds typically improves from less than 30 percent to about 60 percent.
In the past, optical satellite imaging was performed at nadir, meaning the sensor looked straight down
from the platform to Earth—like the first Landsat satellites. SPOT 1’s launch was a revolution in that
respect. Equipped with a mirror technology that enabled collections left or right of the track, SPOT 1
was the first satellite able to acquire imagery of an area of interest at a specific time.
Now many optical satellites are manoeuvrable, with varying speed levels to move from one target to
another. Standard satellites are equipped with momentum wheels, while the most agile satellites are
equipped with control moment gyroscopes (CMGs) that enable a faster slew between two consecutive
targets. This kind of performance increases the number of images that can be collected during the
same pass, as collection opportunities are more numerous, conflicts among contiguous requests are
minimized, and several targets can be acquired on the same pass at the same latitude.
Advanced satellite agility enables different collection scenarios to match user needs as:
• Target collection to image multiple targets
• Strip mapping to create large mosaics in a single pass
• Stereo and tri-stereo acquisition for accurate 3-D applications
• Corridor acquisition for linear features such as coastlines, borders, pipelines, roads, etc.
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Figure 4-12 - Collection scenarios
Applying the same principle as photo cameras, optical satellites feature is a compromise between
coverage and resolution (the biggest is the zoom, the smallest is the field of view). When the satellite
is equipped with multispectral bands (colour), images in panchromatic mode offer four times the
resolution than the multispectral mode. Current systems can deliver panchromatic acquisitions with
submeter resolution and multispectral acquisitions with approximately 2-meter resolution.
High-resolution imaging allows users to identify small objects and infrastructure features from space.
Moreover, the reflection from different spectral bands can be used to classify land cover types and
varieties in vegetation. Even vegetation’s vitality can be recognized using near-infrared and infrared
reflections.
A technique called pan-sharpening combines the visual information of the multispectral data with the
spatial information of the panchromatic data, resulting in a higher-resolution colour product equal to
the panchromatic resolution. This image-fusion process combines multiple images into composite
products to generate more information than the individual input images.
Optical data are easy to use for visual interpretation, as the images represent Earth’s surface the same
way as the human eye views Earth. The number of satellites flying at any time has progressed as a
function of increased launch rates and mission longevity.
Since the 1970s, the average operational life of a mission has almost tripled, increasing from 3.3 years
in the 1970s to 8.6 years (and still lengthening); in addition, the spatial resolution increased from
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around 80 m to less than half a meter and more recent optical satellite missions, such as Digital
Globe’s WorldView mission, that provides 31 cm panchromatic and 1.24 m multispectral imagery
The availability of long time series is an important need. Whilst there is a trend to finer resolution
imaging over time, some spatial resolutions are continuously maintained, especially for global change
research and applications like agriculture, forestry, regional planning and environmental monitoring.
The US' Landsat has the longest record of continuously monitoring the changes in earth's surface at
medium resolution for close to 40 years now. Landsat 8 (initially named Landsat Data Continuity
Mission - LDCM), launched on 2013, in combination with Landsat 7 as the only on-orbit Landsat
program satellite, ensures the continued acquisition and availability of Landsat data and their
consistency with data from the earlier Landsat missions.
Despite ERS-1’s mission ended in 1995 and its successor ERS-2 was shut down in 2011, the task of
extending these datasets was transferred to ESA’s follow-on Envisat environmental satellite (ended
in 2013) after which the Sentinels will be needed in orbit to ensure mission continuity time series.
For some specific domains as, for example, crisis events domain that requires a frequent monitoring
of territory, another key factor is the satellite revisit time. With this respect, one of the most innovative
trends of the new missions is the launch of small satellite constellations as PlanetLabs that combine
the advantage of lower costs associated to high-temporal revisit.
The Table 4-7 and the related synthetic tables of the next paragraphs (Tables 4-8 to 4-17), summarize
the technical characteristics of main optical mission\satellite sensor actually operational, up to 10 m
resolution.
Space
asset
Revisit
time Swath (km)
Spatial
resolution Launch year
GeoEye-1 (DG
Constellation) ~ 3 days 15,2
0.41 m Pan, 1,64 m
MS 2008
WorldView-1 (DG
Constellation)
~ 1,7 days (1 m
GSD) 17,6 0,5 m Pan 2007
WorldView-2 (DG
Constellation)
~ 1,1 days (1 m
GSD) 16,4
0.31 m Pan, 1,84 m
MS 2009
WorldView-3 (DG
Constellation) <1 days (1 m GSD) 13,1
0.31 m Pan, 1,24 m
MS 2014
WorldView-4 (DG
Constellation) <1 days (1 m GSD) 13,1
0.31 m Pan, 1,24 m
MS 2016
Pleiades ~ 4 days 20 0.5 m Pan, 2,00 m
MS 2011/2012
Rapid-Eye ~ 3 days 78 6,5 m MS 2008
Sentinel-2 ~ 5 days 290 10¸ 20 and 60 m MS 2015/2016
Spot-6-7 ~ 4 days 14 1,5 m Pan, 6 m MS 2012/2014
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Deimos-2 ~ 2 days (average) 12 0.75 m Pan, 4 m
MS 2014
Table 4-7 - Main operational optical sensors (resolution <= 10 m) and their key characteristics
4.2.1 DigitalGlobe Constellation
DigitalGlobe owns and operates a large constellation of high-resolution commercial earth imaging
satellites. Without considering Ikonos and QuickBird satellites, not more operational, WorldView-1,
GeoEye-1, WorldView-2, WorldView-3 and WorldView-4 are capable of collecting well over one
billion square kilometers of quality imagery per year and offering intraday revisits around the globe.
Figure 4-13 - DigitalGlobe constellation
GeoEye-1 can collect up to 500,000 square kilometres of pan-sharpened multi spectral imagery per
day. This capability is ideal for large-scale mapping projects. GeoEye-1 can revisit any point on Earth
once every three days or sooner.
WorldView-1 has an average revisit time of 1.7 days and is capable of collecting over one million
square kilometers per day of half-meter imagery.
With its improved agility, WorldView-2 is able to act like a paintbrush, sweeping back and forth to
collect very large areas of multispectral imagery in a single pass. WorldView-2 alone is able to collect
nearly 1 million km2 every day, doubling the collection capacity of our constellation to nearly 2
million km2 per day.
And the combination of WorldView-2’s increased agility and high altitude enables it to typically
revisit any place on earth in 1.1 days. These images supply unprecedented detail and geospatial
accuracy, further expanding the applications for satellite imagery in both commercial and government
markets.
DigitalGlobe is adding a SWIR (Shortwave Infrared) sensing capability (8-band instrument) to its
planned WorldView-3 satellite that will open up a host of new civil and military applications. CAVIS
will monitor the atmosphere and provide correction data to improve WorldView-3's imagery when it
images earth objects through haze, soot, dust or other obscurants.
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Last satellite of DigitalGlobe constellation is WorldView-4, operating at an expected altitude of 617
km, provides 31 cm panchromatic resolution, and 1.23 m multispectral resolution, with an average
revisit time of <1 day and a capability of collecting up to 680,000 sq km per day.
GeoEye-1
Mission/Satellite Sensor: GeoEye-1
Operator Digital Globe Inc.,
USA
Spatial
Resolution
0,41 m
PAN
1,64 m MS
Revisit
time ~ 3 days
Inclination SSO 98° Swath 15,2 km Altitude 681 km
Frequency
band
- Pan: 450-900 nm
- Blue: 450-510 nm
- Green: 520-580
nm
- Red: 655-690 nm
- Near IR: 780-920
nm
Data
distributio
n policy
Commercia
l
Catalogu
e &
Access
https://discover.digitalglobe.com
/
Table 4-8 - GeoEye-1 Sheet
WorldView-1
Mission/Satellite Sensor: WorldView-1
Operator Digital Globe
Inc., USA
Spatial
Resolution 0,5 m Pan
Revisit
time ~ 1,7 days (1 m GSD)
Inclination SSO 98° Swath 17,6 km Altitude 496 km
Frequency
band
Pan: 400-900
nm
Data
distributio
n policy
Commercial
Catalogu
e &
Access
https://discover.digitalglobe.com
/
Table 4-9 - WorldView-1 Sheet
WorldView-2
Mission/Satellite Sensor: WorldView-2
Operator Digital Globe
Inc., USA
Spatial
Resolution
0,31 m Pan
1,84 m MS Revisit time
~ 1,1 days (1 m
GSD)
Inclination SSO 97,8° Swath 16,4 km Altitude 770 km
Frequency
band
- Pan: 450-800
nm
Multispectral:
- 400-450 nm
(coastal blue)
- 450-510 nm
(blue)
Data
distribution
policy
Commercial Catalogue &
Access
https://discover.
digitalglobe.com
/
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- 510-580 nm
(green)
- 585-625 nm
(yellow)
- 630-690 nm
(red)
- 705-745 nm
(red edge)
- 770-895 nm
(NIR1)
- 860-1040 nm
(NIR2)
Data
distribution
policy
Commercial Catalogue &
Access https://discover.digitalglobe.com/
Table 4-10 - WorldView-2 Sheet
WorldView-3
Mission/Satellite Sensor: WorldView-3
Operator Digital Globe
Inc., USA
Spatial
Resolution
0,31 m Pan
1,24 m MS
3,7m SWIR
30 m (CAVIS)
Revisit time <1 days (1 m
GSD)
Inclination SSO 98° Swath 13,1 km Altitude 617 km
Frequency
band
- Pan: 450-800
nm
Multispectral:
- 400-450 nm
(coastal blue)
- 450-510 nm
(blue)
- 510-580 nm
(green)
- 585-625 nm
(yellow)
- 630-690 nm
(red)
- 705-745 nm
(red edge)
- 770-895 nm
(NIR1)
- 860-1040 nm
(NIR2)
Data
distribution
policy
Commercial Catalogue &
Access
https://discover.
digitalglobe.com
/
Table 4-11 - WorldView-3 Sheet
WorldView-4
Mission/Satellite Sensor: WorldView-4
Operated by Digital Globe Inc., USA Spatial
Resolution
0,31 m Pan
1,24 m MS
Revisit
time
<1 days (1 m
GSD)
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Inclination SSO 98° Swath 13,1 km Altitude 617 km
Frequency
band
- Pan: 450-800 nm
Multispectral:
- Blue: 450-510 nm
- Green: 510-580 nm
- Red: 655-690 nm
- Near IR: 780-920 nm
Data distribution
policy Commercial
Catalogue
& Access
https://discover.di
gitalglobe.com/
Table 4-12 - WorldView-4 Sheet
4.2.2 Pleiàdes Constellation
Pléiades is the CNES (French national space agency) program designed as the follow-on to its highly
successful Spot series of low Earth orbit (LEO) multi-mission observation satellites, which has
operated an uninterrupted service since 1986. The Pléiades-HR satellites are the high-resolution
optical imaging component of the French-Italian Orfeo system, for which Italy is supplying the
COSMO-Skymed radar component.
The ground resolution of the HiRI (High-Resolution Imager) will be 70 cm across a 20 km swath,
while a very high degree of agility will allow them to acquire several images successively along track
or off track, for mosaicking of ground scenes. The onboard storage capacity has been increased to
600 gigabits and the downlink data rate to 450 megabits per second.
The 1,000 kg satellites will have a design lifetime of five years and onboard power capacity of 1,000
W.
Mission/Satellite Sensor: Pleiades constellation. Satellite number: 2
Operator Airbus Defence and Space Spatial
Resolution
Pan: 0,5 m
(0,7 m
native)
MS: 2,0 m
(2,8 native)
Revisit
time ~ 24 h
Inclination SSO 98.2° Swath 20 km Altitude 695 km
Frequency
band
- Pan: 480-820 nm
Multispectral:
- B0=450-530 (blue)
- B1=510-590 (green)
- B2=620-700 (red)
- B3=775-915 (NIR)
Data
distribution
policy
Commercia
l Catalogue
& Access
http://www.geo-
airbusds.com/
Table 4-13 - Pleiades Sheet
4.2.3 Spot 6/7 Constellation
SPOT 6 and 7 (Satellite Probatoire de l'Observation de la Terre) are two agile Earth observation
satellites to continue the services of the SPOT 4 and 5 satellites. Both satellites offer 2m resolution
data in a 60 km by 60 km swath, and improved agility with twice the design life of previous SPOT
satellites.
The satellites feature two NAOMI (New AstroSat Optical Modular Instrument) instruments, high-
resolution push-broom imagers based on a Korsch-type telescope designed and developed at EADS
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Astrium SAS. The imager provides imagery of 2 m in Pan and four multispectral (MS) bands of 8 m
multispectral. The satellites are co-orbital with the high-resolution Pléiades satellites.
Mission/Satellite Sensor: Spot6/7. Satellite number: 2
Operator Spot Image Spatial
Resolution
1, 5 Pan, 6, 0
m MS
Revisit
time Spot Image
Inclination SSO 98.2° Swath 14 km Altitude 695 km
Frequency band
- PAN: 0.45-0.75 µm
Multispectral
- Blue: 0.45-0.52 µm
- Green: 0.53-060 µm
- Red: 0.62-0.69 µm
- NIR: 0.76-0.89 µm
-
Data
distribution
policy
Commercial
license Catalogue
& Access
http://www.geo-
airbusds.com/
Table 4-14 - Spot 6/7 Sheet
4.2.4 Deimos-2
Deimos-2 is a follow-on imaging mission of Deimos-1 of Deimos Imaging S. L. U., an Elecnor
company, Spain. The Deimos-2 mission is aimed at operating an agile minisatellite for high-
resolution Earth Observation applications. The agile spacecraft can be steered to accurately point the
pushbroom-type optical payload, which can provide 1 m panchromatic and 4 m multispectral images
in a swath of 12 km at nadir, at an orbit altitude of ~600 km. The multispectral capability includes 4
channels in the visible and near-infrared spectral range (red, green, blue and NIR).
Mission/Satellite Sensor: Deimos-2
Operor Urthecast Spatial
Resolution
0.75 m PSH
4 m MS Revisit time
~ 2 days
(average)
Inclination SSO 97.9° Swath 12 km Altitude 620 km
Frequency
band
- Pan: 450-900
nm
- Multispectral:
- MS1: 420-510
(blue)
- MS2: 510-580
(green)
- MS3: 600-720
(red)
MS4: 760-890
(NIR)
Data
distribution
policy
Commercial
license. Catalogue &
Access
http://www.deim
os-
imaging.com/cat
alogue
Table 4-15 - Deimos-2 Sheet
4.2.5 RapidEye Constellation
RapidEye is a full end-to-end commercial Earth Observation system comprising a constellation of
five mini-satellites, a dedicated SCC (Spacecraft Control Center), a data downlink ground station
service, and a full ground segment designed to plan, acquire and process up to 5 million km2 of
imagery every day to generate unique land information products.
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Mission/Satellite Sensor: RapidEye
Operaor Planet Labs Spatial
Resolution
6,5 m MS
(resampled at
5 m) M
Revisit time ~ 3 days
Inclination SSO 98° Swath 78 km Altitude 634 km
Frequency
band
Multispectral
- Blue: 440-
510nm - Green:
520-590nm - Red: 630-
685nm - Red edge:
690-730nm - NIR: 760-
850nm
Data
distribution
policy
Commercial
license
Catalogue &
Access
http://eyefind.rapideye.com/
Table 4-16 - RapidEye Sheet
4.2.6 Sentinel-2 Constellation
SENTINEL-2 is a multispectral operational imaging mission within the Copernicus program, jointly
implemented by the EC (European Commission) and ESA (European Space Agency) for global land
observation (data on vegetation, soil and water cover for land, inland waterways and coastal areas,
and also provide atmospheric absorption and distortion data corrections) at high resolution with high
revisit capability, to provide enhanced continuity of data so far provided by SPOT-5 and Landsat-7.
SENTINEL-2 satellite carries an optical instrument payload that will sample 13 spectral bands: four
bands at 10 m, six bands at 20 m and three bands at 60 m spatial resolution. The orbital swath width
will be 290 km.
Mission/Satellite Sensor: Sentinel-2. Satellite number: 2
Opeor ESA Spatial
Resolution
10 m MS,
30 m MS Revisit
time ~ 5 days
Inclination SSO 98.5° Swath 290 km Altitude 786 km
Frequency
band
13 spectral bands (443nm-
2190nm):
- 4 visible and NIR
- 6 red-edge/SWIR - 3 atmospheric
correction bands
Data
distributio
n policy
Open data
policy
https://copernicusdata.esa.i
nt/
Table 4-17 - Sentinel-2 Sheet
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5 Conclusions and Recommendations
Most of the devices presented in this technical report have high TRL making them a good choice for
prototyping and producing the final system.
Anyway, for a final selection of the devices, payloads configuration and overall solutions, a clear
definition of use cases and respective needs is crucial. This analysis is expected in D1.2- Railway
key asset monitoring: parameters, technology, specifications. Final choices will be reported and
justified in D4.1 - Application cases definition.
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Parent Documents
The parent documents establish the criteria and technical basis for the existence of this document.
[PD1] Shift2Rail Joint Undertaking (S2R JU) – Multi-Annual Action Plan (MAAP) – Rev. 3 –
26/11/2015
[PD2] Shift2Rail Joint Undertaking (S2R JU) – Annual Work Plan 2017 – Version 1.1– 23/12/2016
[PD3] MOMIT – Description of Action (DoA) – GA 777630
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End of the document