1. The iOneTM Infrastructure Metric-Mapping System
A Paradigm Shift on Co-Mounting and Co-Registering Geoimaging Sensors with LiDAR
Dr. J. Armando Guevara
Visual Intelligence LP - President and CEO
armando.guevara@visualintell.com
ABSTRACT
Integration efforts of geoimaging sensors with LiDAR have demonstrated the need to
systematically improve the co registration of the imagery with the LiDAR data such that errors in the
imagery collected are greatly reduced by the sensors being rigidly mounted, share the geopositional
metadata and are registered to each other in a rigorously calibrated metric configuration.
At Visual Intelligence (“VI”) a committed pursuit with our customers is to increasingly enable
them with our ubiquitous metric geoimaging sensor technology to collect more, do more, for less; this
whilst abating the increasingly speed at which digital devices become obsolete. In this pursuit VI has
developed the iOneTM Sensor Tool Kit Architecture (or iOne STKATM) from which the iOne Infrastructure
Metric-Mapping System has been developed. The iOne IMS is a modular and scalable co mounted and co
registered (“CoCoTM”) geoimaging sensor with LiDAR that can readily, efficiently and economically be
configured to fit a variety of infrastructure surveying applications. This paper describes first the iOne
STKA and the iOne IMS, its core design and the operational efficiencies it provides.
KEYWORDS: iOne, STKA, Iris One, Digital camera, Camera calibration, Co mounting and Co
registration of Sensors, infrastructure mapping and surveying
1. INTRODUCTION
Founded in 1997, Visual Intelligence (VI) has focused on research and development (R&D) to provide
a multipurpose metric digital geoimaging sensor technology with scalable sensor imaging arrays for
automated high-accuracy metric geoimaging for mapping, surveillance, ground and mobile applications.
The sensor architecture is designed to be economical (lowest cost of ownership), light, small, high
collection, high resolution, and fast in deployment. The multi-year R&D has resulted with various granted
patents that have provided the foundation to generate a Virtual Frame (VF) camera systems comprised of
multiple COTS camera modules arranged at certain angles to achieve flexible and rapid configurations as
different and distinct (sometimes conflicting) mission requirements may mandate.
The patents awarded along with the USGS Aerial Digital Sensor Type Certification received in 2009
for the Iris One 50 (now called the Iris One Ortho 19 kps); validate the uniqueness of VI’s intellectual
property, technological foundation, and its forthcoming potential transforming role in the digital
geoimaging industry. The current and evolving portfolio of VI IP has been casted into a sensor tool kit
architecture called the iOne Sensor Tool Kit Architecture or iOne STKA. The scalability of the sensors
built from the iOne STKA are based on the Angular Retinal Camera Array (ARCA); this scalability
property allows for both functional and collection scalability. Functionally the sensors can be configured to
have only or many features such as ortho, stereo, oblique, full 3D as well as CoCo -(the co mounting and co
registering of sensors; e.g. imagery fusion- such as LiDAR, thermal, SWIR, FLIR, multispectral and
hyperspectral among other types of passive (e.g. electro-optical) and active (e.g. LiDAR, radar) sensors.
The modularity of the iOne STKA allows flexibility and scalability to meet various customer needs and
applications within one single base sensor system (hence “iOne”).
Visual Intelligence among its sensor family built from the iOne STKA has brought to market the Iris
One Ortho 19 kps; the Iris One MS; the Iris One Stereo and recently the iOne Infrastructure Mapping
System or iOne IMS –the subject matter of this paper. The iOne family of digital geoimaging sensor
systems in general, and in particular the iOne Stereo, is designed to achieve and exceed the performance of
the film aerial cameras, in collection capacity and metric accuracy. For a detailed description of the Iris
One family of sensors created to-date from the iOne STKA please see Petrie, Gordon 2012.
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2. 2. iOne STKA ARCA BASED DESIGNS
The iOne STKA is an optimal set of software, hardware, methods and procedures geoimaging
components (”Lego®-like) that include advanced imaging processing algorithms for radiometric and
geometric accuracy, pixelgrammetry processing and image analysis (feature extraction, point cloud
generation); it is a flexible and modular set of components, all solid state that are all integrated by software.
The iOne STKA is based on the ARCA (Guevara, 2009), a patented angular cross eyed imaging array
that allows the system to be small, light and scalable in collection capacity, resolution, and functionally
using the same base architecture –i.e. One system for all applications. An advantage of the ARCA is that
camera modules are configured in a linear arrangement with an “hour glass imaging effect”, giving it the
advantage of imaging a larger swath while looking through a small aperture; the optical axis of each
individual CM in the array to intersect, passing through a single perspective center. The patented ARCA
design uses synchronously operating camera module heads to form a single virtual central-perspective
image.
With multiple ARCAs, Iris One system can be easily configured as multi-spectral sensor (double
ARCAs) and stereo system (triple ARCAs). The multi-spectral version of Iris One system allows the color
RGB images recorded by camera modules mounted on one ARCA to be co-registered with and
superimposed on the corresponding near infra-red (NIR) images collected by the cameras mounted on the
second ARCA. The Iris One stereo system, with three ARCAs, can be oriented either in the cross-track or
the along-track direction. Vary-format camera modules and different types of lens produce various ground
coverage. There are two typical settings for the Iris One stereo system. The 60 % longitudinal overlap along
the flight line that is produced when the cameras are programmed to expose overlapping sets of images in a
stereo convergent configuration gives a base: height ratio of 0.6 –unique in the industry. When the system
is equipped with 9x29 MPIx camera modules and 135mm lenses and rotated by 90 degrees into the crosstrack position, the system yields a 0.34 base: height ratio, similar to that achieved by the overlapping stereo
images that are produced by conventional large-format digital mapping cameras.
(a)
(b)
Figure 1- (a) This figure shows the ARCA(s) into which varying-format camera modules can be inserted.
(b) The geometric arrangement of an ARCA configuration; each ARCA or set of ARCAs generates a single
metric frame ingestable by any 3rd party photogrammetric workflow.
As such the iOne STKA allows to configure combinations of camera modules (CMs) that yield cross
track collection efficiencies from 20,000 pixels upward of 60,000 pixels cross track, as well as frame sizes
along track in excess of 19,000 pixels (depending on how the arrays are aligned). Table 1 depicts part of the
developed Iris One systems family. For a detailed technical description of the ARCA and its functional and
collection efficiencies please see Petrie, Gordon 2012.
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3. Iris One Ortho/MS 19 kps
Iris One Stereo with
configurable B/H .6 or .3
depending on ARCA cross
track or along track
orientation
Iris One Infrastructure
Mapping System (IMS)
Isis Earth™ Software
Isis Sky™ Software
A highly agile and robust system for ortho wide area collection
Based on B/H .6, only sensor in the industry with engineering quality
imagery equivalent or superior to film. The same system can be “rotated”
to achieve higher collection efficiencies whilst achieving .3 B/H.
A powerful, very light and compact sensor that provides ortho, multispectral, backward and forward oblique, all in one pass
Post processing software that is integrated with Iris One sensors used to
generate accurate ortho images.
Near real-time onboard (in-flight) ortho processing software that is
integrated with Iris One sensors.
Table 1- The Iris One family of sensors and software based on the iOne STKA is capable of handling
numerous collection scenarios.
For engineering-quality metric application, high accuracy and resolution requirement in both geometric
and radiometric aspects must be met (Cramer, 2006). The geometric accuracy of the Iris One digital
imaging sensor systems is achieved from laboratory calibration of each camera module, the arrays set, as
well as calibration flight using BINGO (Kruck, 2010; Hwangbo, 2012). With highly accurately determined
geometric properties for the complete camera module set in the ARCA array(s), the Iris One system is able
to produce virtual frames from each ARCA CM set which is defined as single central perspective,
distortion-free image. The simple geometry of the ARCA Virtual Frame image makes it compatible with
the traditional workflow of any photogrammetric software. Moreover, radiometric calibration explores
camera’s radiometric properties to naturally link image data with actual scene for high-quality imagery
production. For further in depth technical details on both geometric and radiometric calibration procedures,
please refer to Hwangbo 2012 and Guevara-Wang 2012).
(a)
(b)
Figure 2- VI’s geometric calibration facilities: a). Distribution of control points used for laboratory
calibration (red dots are located on a 2D calibration wall and blue stars are located on a 3D calibration
frame); b). Calibration field with distribution of ground control points.
3. INTRODUCING THE CONCEPT OF KPS
A kps is the number of pixels across track covered by a sensor on the ground, in other words, the
number of pixels in the swath. 1 kps = one thousand pixel wide swath. Therefore the number of pixels
allowed by an iOne sensor to collect is defined as kps, or kilo pixel swath. So depending of the application
the sensor can be as small as 7 kps to as large as it is required by the mission of the sensor, all using the
same base architecture –feature that yields very fast sensor deployment time.
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4. Why kps? It is often difficult to differentiate the competing claims of different digital aerial
camera manufacturers when it comes to efficiency. There are many aspects that contribute to the
efficiency, but one simple measure is for the same aircraft speed, how much area is collected per hour of
flying?
There are many factors that go into the design of a successful aerial metric geoimaging project,
including but not limited to camera focal length, CCD size and flying height. For digital cameras, the
project is designed for a specific nominal ground sample distance or GSD. No matter what flying height,
focal length, or CCD size, the amount of area covered is the nominal GSD times the number of pixels in the
selected width of the CCD array (x or y orientation – typically the largest number of pixels on the CCD is
in x so if more depth is desired the CCD can be rotated with x becoming y).
Normal block collection of a project will factor in a 30% side lap between flight lines. Examples of pixels
swath with “CCD configurations” of:
A.
B.
C.
D.
7 kps will have an effective swath 5051' wide
11 kps will collect a swath 8,043' wide
19 kps will collect a swath 13,280' wide
…and so on.
kps
7
11
19
Width
5,051
8,043
13,280
30% side
lap
2,165
3,447
5,691
In a project example with a flying speed of 150 miles an hour times 5,280 feet in a mile, the aircraft travels
approximately 792,000 feet an hour. Efficiency results for the above kps example are shown on the
following chart:
A
B
C
Traveled
Distance/hour
792,000
792,000
792,000
Width
5,051
8,043
13,280
sq feet
4,000,550,400
6,370,056,000
10,517,522,400
sq miles
144
228
377
Efficiency
1.00
1.59
2.63
Figure 3- Impact of kps in collecting at 1 foot pixels (30 cm)
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5. 4. INTRODUCING CoCo
In 1998 VI designed, built and operated its first generation of digital aerial imaging and mapping
sensor. In 2001 VI acquired its first LiDAR. Since then, VI has been at the leading edge of innovation by
improving the operational use of LiDAR technology tightly coupled (co mounted and co registered) with
aerial digital cameras with different kps and FOV according to mission. Recently VI integrated LiDAR
technology with its 3rd generation imaging sensor technology, the iOne IMS (infrastructure metricmapping system).
CoCo is a patented vehicle based data collection and processing system and imaging sensor
system and methods thereof. The apparatus’ and methods optimize the co-mounting and co-registering of
two or more sensors, for example, an EO camera system with a LiDAR rigidly mounted on a single plate
with IMU. The claims were directed towards the incorporation of the co-mounted and co-registered nature
into VI’s system for terrain mapping which obtained unprecedented sensor integration performance for
large scale and large geographic area mapping.
The integration of CoCo begins with mounting the two sensors together. The sensors must be
rigidly mounted on the same base plate so that aircraft flex is minimized. This flex needs to be less than
100th. The sensors must be mounted as close as possible and best practices have the two sensors mounted
over the same aperture. This is possible because the Iris One’s ARCA can operates without the need for a
gyro-stabilized mount. The nearness of the sensors is needed so that they can share the same ABGPS/IMU.
This is only possible also because the Iris One family of sensors have a light, compact and rigid design that
can be Co-mounted with out the need for an additional standard camera hole.
Figure 4- CoCo System Diagram
The lever arm measurements must be taken for each sensor so that when processed each sensor
has its own offsets. By sharing the IMU and GPS, all sensors are calibrated substantially the same epoch,
using the same GPS signal, ground targets and under the same atmospheric conditions. Basically this
means, each image pixel and each LiDAR pixel are referenced from the same location. This greatly reduces
compounded errors realized when calibrating each separately, using different GPS signals or under
atmospheric conditions. Separate sensor holes (with no co-mounting) with a shared IMU is not the same, as
the aircraft has its own flex that can change or move independent to each other which causes positional
errors which may work depending on accuracies needed. Separate IMUs is another approach but each IMU
will have its own biases and cause differences in yaw, pitch, and roll data.
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6. 4. INTRODUCING iOne IMSTM
The Iris One Infrastructure Metric-Mapping System (iOne IMS) camera system based on the iOne
STKA, integrated with a LiDAR system in CoCo mode, is an efficient, economical, one-pass, all feature
digital infrastructure capture system that can support numerous image data requirements using a helicopter
or fixed wing aircraft. From a single control interface, operators can capture and monitor imagery from
high-resolution oblique, wide swath multi-spectral, and optional thermal and video cameras referenced to a
single GPS/IMU reference system for common picture and overlapping display.
With its single pass, full capture capability, the system produces accurate, high-quality imagery
saving 50%-75% over less efficient aerial collection cost. With its multi-sensor ARCA based platform
architecture, the system can grow to accommodate additional sensors thereby further increasing
information value with little added data collection cost.
The iOne IMS configuration includes the following benefits:
•
•
•
•
Two camera oblique images (fore/aft) assures full coverage
Single wide-field NADIR cameras for full swath 4-Band coverage with high positional accuracy
Single operator control with on-board Quick-Look quality review
B/H = 32% at 700 ft AGL to support future stereo/corridor-wide DTM
Figure 5- (a) the iOne IMS dimensions –a small, light compact system that can be flown on rotary or fixed
wing aircrafts (b) iOne IMS capability to collect ortho, near infrared, backward and forward oblique –all in
one pass.
The iOne IMS sensor is designed to collect orthophotos (RGB and Near Infrared) and oblique
imagery (forward and aft) simultaneously with a LiDAR sensor. The collection of laser and imagery data is
being conducted to be able to support, for example, the generation of surveys of power line transmission
corridors.
The iOne IMS generated surveys support the following categories of analysis:
•
Inspection of transmission hardware mounted on towers
•
Right -of -Way Analysis
•
Inspection of power and relay substations
•
Power line sag and tension analysis
•
Encroachment of man-made and natural vegetation (e.g. trees)
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7. This system will support the same analysis functions in other transmission corridors such as railways,
pipelines and others as required. The nominal parameters for the oblique sensor system are defined below:
Nominal Distance between camera and target ft
850 ft
Estimated tower height (minimum)
60 ft
Estimated tower height, (maximum)
200 ft
Estimated tower height, (average)
120 ft
Tower covers % of image height (minimum)
75
Desired resolution of tower, inches/pixel
0.44
Figure 6- (a) Minimum Oblique Collection Geometry
(Nominal altitude = 700 ft, Range, 850 ft, GSD approx. 0.5 inches) (b) Nadir Ortho Collection Geometry
Features
Analysis Factors
Insulators/Conductors
Size, Texture, Condition, Nominal (0.44 inch) Max
GSD (1 inch)
Transformers
Size, Condition, Nominal (0.44 inch) Max GSD (1
inch)
Transmission Lines
Condition, Sag, Sway Distance, Nominal (0.44
inch) Max GSD (1 inch)
Transmission Towers
Condition, Size Envelope, Max GSD
Ground Vegetation
Location, Distance to Towers, Max GSD, Bands
Trees/Foliage
Location, Distance to Sway Line Limit, Bands
Fences
Location
Accuracy standards if processed with solid ground control
of Manmade Structures within Easement
Location
Roads/Access to Easement
Location
Examples of Electrical Infrastructure Feature Types that can be Collected- Sizes and Characteristics
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8. Fig. 7- (a) iOne IMS Oblique sample image (b) Oblique image and automated extraction of
features of interest for further detailed analysis.
The operational envelope of the iOne IMS is as follows:
Corridor (or Coverage) Min/Max for Nadir Ortho Camera
• Minimum Swath: 600 feet
• Nominal Swath: 750 feet
• Desired Swath: 900 feet
Corridor (or Coverage) Min/Max for Oblique Camera
• Minimum Swath: 100% of infrastructure feature surveyed Width & Height
• Nominal Swath: Minimum Swath to Support feature collected
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9. GSD Min/Max
•
•
•
•
Oblique Camera Minimum GSD: 0.44”
Oblique Camera Maximum GSD: 1.0”
Nadir Cameras Minimum GSD: 6”
Nadir Cameras Maximum GSD: +- 10%
iOne IMS sensor operation
• Single Operator
• Minimal Operations Workload; Flight technician-level skills
Altitudes (MSL) and (AGL) min/max
• Minimum Altitude (AGL): 600 ft
• Nominal Operations Altitude (AGL): 700 ft
• Maximum Altitude (AGL): 3,000 ft
Environment/Sun Angle/Time of Day
• Operations within +/- 20 deg sun angle range such that features are interpreted (detected)
in shadows.
• Platform Angle Range
• +/- Roll : system controlled
• +/- Pitch: system controlled
• +/- Yaw: system controlled
• Ground Speed Velocity and Tolerance: system controlled
• Features are interpretable in shadows.
Typical Mission Day
• Pre-mission calibration (boresight)
• 4-6 hours of collection
• Camera system operation is automated. No more than 5 minutes/hour operations
required for system operations monitoring
• 2TB on-Board SSD Data Storage (1-1.5 TB typical)
• 1 Hour Post Mission Data Quality Analysis
• On-site Imagery Review with Post-flight previewer software
The Iris One IMS will produce multiple image products for use in utility corridor status analysis and
asset assessment. These products are summarized as:
Image RGB Oblique of full features (e.g. Towers) -100% coverage- front/back (image pair)
o
o
o
o
GeoTiff with lat/long location center, image scale
One image per feature structure is generated – iOne IMS creates an oblique virtual frame
if the feature appears in two or more images. Feature virtual frames are minimized.
Provides KML with camera orientation during exposure (meta data option)
Google Earth KMZ file with image and camera locations (meta data option)
Provides Multispectral Image -Four-Band Orthos- (metrically co registered at 1:1 resolution
RGB+NIR)
The images are color balanced across for the mosaicing workflow.
o
o
Oblique Images maintain color saturation, intensity, and hue across the mission
Ortho images support color balancing and mosaicing methods
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10. The iOne IMS was designed for ease of use for the operator and minimal training requirements to
be proficient at operating the system. VI includes a flight planning software tool called TopoFlight
Navigator that is bundled with the iOne Isis Earth orthophoto system.
TopoFlight Navigator is used to navigate the aircraft for image acquisition flights. A predefined
flight plan (e.g. provided using TopoFlight) is used as base data. The camera is triggered at the pre-defined
positions. The interface for every camera can be delivered or can be implemented by the operator. The
system consists of different modules to provide the capability to combine the actual TopoFlight Navigator
with any available GPS, IMU and camera system.
(a)
(b)
Fig. 8 (a) The iOne IMS and RIEGL VQ-480 combination mounted side-by-side on a common base plate
which is placed on a set of anti-vibration dampers – as viewed from the side at left and from above at right.
(b) The iOne IMS system mounted in an Aerocommander aircraft.
5. OPERATIONAL EFFICIENCIES
For many projects collecting LiDAR and Imagery together can lead to less flight time or eliminate
the need for an additional aircraft with separate sensors. Over the years since VI established the CoCo
approach, we have created for our users innovative ways to collect the data simultaneously. Some examples
follow.
5.1 Forestry
CoCo collection was used in several forestry projects where the Imagery FOV was 70° and the
LiDAR FOV of 45° (due to point density needed). Since the LiDAR was the limiting factor, VI devised for
its customer the flight plans to maximize each sensor FOV. To solve for this the imagery and LiDAR were
collected on even numbered flight lines during prime sun angle and LiDAR only was collected on odd
numbered lines during times of less than optimal sun angle. This improved overall collection time by using
the least number of lines and only one aircraft with one flight and ground crew. This approach allowed for
the imagery to be flown with the minimal amount of flight lines, which relates to less data to process, faster
deliverables and overall operational savings.
5.2 Infrastructure Corridor Mapping
CoCo was used in a corridor mapping project where the LiDAR was flown to create more accurate
DEMs for the ortho imagery. Sample case project collected 500 miles of pipeline. The customer wanted a 1
mile swath of imagery and 3500ft swath of LiDAR. Instead of using two aircrafts, one with a LiDAR and
the other with a digital camera, the projects was flown with both simultaneously, and by using an Iris One
19 kps the project was flown more efficiently- having both sensors collecting concurrently reduced costs
by 50%.
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11. 6. CONCLUSIONS
This paper has described the iOne STKA, the CoCo technology and its new embodiment the Iris
One Infrastructure Metric-Mapping System or iOne IMS, an efficient, economical, one-pass, all feature
digital infrastructure capture system that can support numerous image data requirements using a helicopter
or fixed wing aircraft. The operational improvements (data collection, time, cost) obtained by flying in
tandem the iOne IMS in CoCo mode can lead to great operational efficiencies and cost savings such as less
flight time and/or eliminate the need for an additional aircraft with separate sensors.
With the iOne STKA VI has created a robust and solid software and hardware Lego®-like
foundation to design and deploy any type of EO sensor, and if required, fused (“CoCo” - co mounted and
co registered) with any other passive or active sensor type in the most effective and efficient manner, e.g.
LiDAR, thermal, video, UV. The iOne STKA is backed by numerous patents and IP (methods, procedures
and software) that yield a very powerful plug-and-play sensor foundation. Methods and procedures include
but are not limited to robust geometric and radiometric calibration; very large virtual frame generation that
is ingestible by any traditional photogrammetric workflow (the ARCA array set behaves like one single
camera); ortho direct positioning onboard processing software that is the platform for event driven report
generation and more.
REFERENCES
Cramer, M., 2006. Calibration and validation of airborne cameras. Proceedings ISPRS Commission I
Symposium “From Sensor to Imagery”, Paris – Marne Le Valle, July 4-6, 2006.
Guevara, A., 2009. The ARCA of Iris: a new modular & scalable digital aerial imaging sensor architecture.
ASPRS 2009 Annual Conference, Baltimore, March 9-13, 2012.
Guevara, A.; Wang, W 2013. The iOne STKA Foundation for the Iris One Sensor Family. ASPRS 2013
Annual Conference.
Hwangbo, J, 2012. Iris One Stereo System, ASPRS 2012 Annual Conference, Sacramento, March 19-23,
2012.
Kruck, E., 2010. Developments and challenges in bundle triangulation, ASPRS 2010 Annual Conference,
San Diego, April 26-30, 2010.
Petrie, Gordon 2012. Visual Intelligence’s Iris One Airborne Camera Systems - Based on its iOne Sensor
Tool Kit Architecture. Emeritus Professor of Topographic Science in the School of Geographical & Earth
Sciences of the University of Glasgow, Scotland, U.K. E-mail – Gordon.Petrie@glasgow.ac.uk ; Web Site –
http://web2.ges.gla.ac.uk/~gpetrie/ - Geoinformatics Magazine (September 2012 issue no. 6/2012
http://www.geoinformatics.com).
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