The iOneTM Infrastructure Metric-Mapping System
A Paradigm Shift on Co-Mounting and Co-Registering Geoimaging Sensors with...
2. iOne STKA ARCA BASED DESIGNS
The iOne STKA is an optimal set of software, hardware, methods and procedures geoimaging
c...
Iris One Ortho/MS 19 kps
Iris One Stereo with
configurable B/H .6 or .3
depending on ARCA cross
track or along track
orien...
Why kps? It is often difficult to differentiate the competing claims of different digital aerial
camera manufacturers when...
4. INTRODUCING CoCo
In 1998 VI designed, built and operated its first generation of digital aerial imaging and mapping
sen...
4. INTRODUCING iOne IMSTM
The Iris One Infrastructure Metric-Mapping System (iOne IMS) camera system based on the iOne
STK...
This system will support the same analysis functions in other transmission corridors such as railways,
pipelines and other...
Fig. 7- (a) iOne IMS Oblique sample image (b) Oblique image and automated extraction of
features of interest for further d...
GSD Min/Max
•
•
•
•

Oblique Camera Minimum GSD: 0.44”
Oblique Camera Maximum GSD: 1.0”
Nadir Cameras Minimum GSD: 6”
Nadi...
The iOne IMS was designed for ease of use for the operator and minimal training requirements to
be proficient at operating...
6. CONCLUSIONS
This paper has described the iOne STKA, the CoCo technology and its new embodiment the Iris
One Infrastruct...
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The ione infrastructure metric mapping system (ims) armando guevara

  1. 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. © The iOne IMS Visual Intelligence -- LiDAR News 1
  2. 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. © The iOne IMS Visual Intelligence -- LiDAR News 2
  3. 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. © The iOne IMS Visual Intelligence -- LiDAR News 3
  4. 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) © The iOne IMS Visual Intelligence -- LiDAR News 4
  5. 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. © The iOne IMS Visual Intelligence -- LiDAR News 5
  6. 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) © The iOne IMS Visual Intelligence -- LiDAR News 6
  7. 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 © The iOne IMS Visual Intelligence -- LiDAR News 7
  8. 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 © The iOne IMS Visual Intelligence -- LiDAR News 8
  9. 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 © The iOne IMS Visual Intelligence -- LiDAR News 9
  10. 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%. © The iOne IMS Visual Intelligence -- LiDAR News 10
  11. 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). © The iOne IMS Visual Intelligence -- LiDAR News 11

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