Tracy has worked with Exelis for over 10 years and is an expert in enterprise data management, particularly as it relates to the Defense and Intelligence community. Tracy has a BS in Electrical Engineering from Rochester Institute of Technology (RIT) and an MS in Software Development and Management from RIT. She really enjoys working with the users of our software to help them solve real world problems. In her free time, Tracy enjoys a good bike ride.
Author: Tracy Erwin
We are living in a changing information landscape associated with social media, high-speed networks and distributed information sharing from people all around the world.
There is a movement in open source software and communities of thousands of people voluntarily contributing data. Contribution of geospatial data, what some call Volunteered Geographic Information, has raised concerns on data quality. However, there is a benefit to this type of data produced by end-users having significant local expertise instead of a central authority (i.e. government and businesses) that may not be aware or capable of detecting changes in local environments.
OpenStreetMaps (OSM) founded in 2004 is an example of people from across the globe working together to collect and contribute data to the free, editable map of the world. They were instrumental in aiding the near real time crisis mapping of the 2010 Haitian earthquake. This effort established a model for non-governmental organizations (NGOs) to collaborate with international organizations. Volunteers from OSM and Crisis Commons used pre-existing satellite imagery to map the roads, buildings and refugee camps of Port-au-Prince in just two days to build a digital map of Haiti's roads. This became the backbone for software that helped organize aid and manage search-and-rescue operations.
Figure 1: Example zoomed in area of former Haiti renderer on openstreetmap.nl The Haiti custom rendering set up by User:Ldp which shows damaged buildings and refugee camps mapped within OpenStreetMap using specialGeoEye/DigitalGlobe imagery.
OSM also played a significant role in the Ebola virus epidemic in West Africa. Locations of roads, towns and buildings was unknown. There was an immediate need for geospatial data and maps.
Figure 2: Pascal Neis Map showing OpenStreetMap activitiesduring West Africa Ebola Outbreak
We are witnessing a shift in how geographic information is created and shared with contributions from passionate communities. Transparency and movement in collaboration is expanding as shown by National Geospatial Agency (NGA) teaming with Digital Globe, ESRI and OSM supporting disaster relief efforts in response to the Ebola epidemic in Western Africa (2014) and the Nepal earthquake (2015).
For the Ebola epidemic, NGA used ESRI’s ArcGIS Online, OpenStreetMap foundational data and DigitalGlobe commercial imagery and human geography data sets to provide a public website with 500 data layers, more than 200 products and about 70 applications. The website was viewed more than one million times over the period of October 2014 to February 2015.
Figure 3: A DigitalGlobe WorldView-2 satellite image ofMonrovia, Liberia, taken April 8, 2014, is overlaid with DigitalGlobe Landscape+Human features. Photo Credit: DigitalGlobe
NGA followed its Ebola response method by launching a public website to assist with relief efforts the day after Nepal was struck by a devastating earthquake on April 25, 2015. The Nepal site hosts unclassified GEOINT data, products, and services. DigitalGlobe made its high-resolution satellite imagery available online. Volunteers tagged damaged buildings, roads, and other areas of major destruction using DigitalGlobe’s Tomnod crowdsourcing platform. In addition to the offerings that DigitalGlobe has made available, DigitalGlobe and Exelis Visual Information Solutions (a subsidiary of Harris) put their new partnership to good use with Amazon instances that allowed free access to the data and ENVI image analysis software for anyone that wanted to lend their image analysis skills to generate useful products for response and recovery efforts.
Figure 4: PhotoCourtesy of Digital Globe The Tomnod team has released a Nepal earthquake dataportal with a dynamic map of the latest crowdsourcing results.
DigitalGlobe’s partnerships and recent effort to open source MrGeo is making it easier for data scientists and engineers to apply their expertise on spatial data. Crowdsourcing is moving to the next level beyond crisis mapping to big data analytics. In June, DigitalGlobe partnered with the United States Geospatial Intelligence Foundation (USGIF) to co-sponsor the first GEOINT-focused Hackathon.
Participants were requested to apply their expertise to DigitalGlobe Geospatial Big Data to create an open-source solution. There were two goals that participants were tasked with: (1) Expose their team’s thinking and build in hooks so another team working with another geography or outbreak could modify the solution to a new set of conditions and (2) determine why certain areas of West Africa were unaffected by the Ebola outbreak and predict where additional outbreaks might occur.
DigitalGlobe made available their imagery, human geography, elevation data, geospatial social media, and OpenStreetMap features available via a set of open APIs. The first place team’s solution focused on travel and revealed an “Ebola superhighway” along the coast of West Africa. See more details of the results here.
On the horizon
The crowd source community and collaboration analyzing massive amounts of distributed data to draw insights about a situation can result in increased productivity and innovation. Tapping into this collective intelligence results in diverse perspectives that are critical factors to moving innovation further, faster.
I suspect we will see more crowdsource problem solving as large amounts of globally distributed data continue to grow at a rapid rate and look forward to the collaboration solving tough, real-world problems.
Categories: ENVI Blog | Imagery Speaks
Situational Awareness for small UAVS (sUAV)
When I hear situational awareness (SA), I automatically think of Jagwire given that I have worked on this product from its inception. It is a geospatial data collection, management and dissemination system providing SA primarily for the warfighter and now reaching new markets.
As a participant at AUVSI show in May 2015, a different form of a SA system piqued my interest, that being sense-and-avoid (SAA) also referred to as detect-and-avoid (DAA). Aircraft can collect data providing situational awareness to various users and the pilots of the aircraft themselves need an understanding of their SA to prevent collisions. This is where sense and avoid systems come into play.
Photo courtesy of SKYTECH
Just prior to the show, colleagues from another division of our company launched Symphony RangeVue, an airspace situational awareness tool designed for unmanned aerial system (UAS) operations in the U.S. It can be used as a sense-and-avoid addition to UAS ground control stations having flexible geo-fencing tools to alert operators when a UAV approaches airspace boundaries or when other aircraft are in the vicinity.
What is SAA/DAA?
The names is self-describing, sense or detect an object around the aircraft such as other aircraft and natural threats like birds and avoid to prevent airborne collisions. UAVs need to be able to react to each other and with their surroundings. The technologies to create these SAA systems exist and there are systems being developed and tested for large unmanned vehicles used by the Air Force and Army. However, it is the integration and the size, weight and power (SWAP) of small-unmanned aerial vehicles (sUAV) that are proving to be challenging. Unlike traditional aircraft and larger UAVs, lower altitudes and speed are contributing factors too.
Why is it important?
Besides the obvious of safety, in order to have commercial UAVs fully integrated into the National Airspace System (NAS), the FAA must certify a sense-and-avoid system, which provides airborne collision avoidance capability. This year, the FAA has made it easier for the first small commercial UAVs to share the NAS (section 333 FAA Modernization and Reform Act). Furthermore, they have established an interim policy to speed up airspace authorizations for certain commercial unmanned aircraft operators who obtain Section 333 exemptions.
Photo courtesy of 3DR - FAA granted Section 333 authorization for commercial use of 3DR drones
Section 333 exemption holders automatically receive a “blanket”200 foot Certificate of Authorization (COA) and abide by a set of flight restrictions such as being within visual line of sight (VLOS). The details and can be found on the FAA website. This is a big step forward for this rapidly evolving technology and industry. You might be asking, “Does this mean Amazon will be delivering our packages via a quad copter”? Not yet and not likely, anytime soon.
The technologies and challenges
In order to see aircraft as well as wildlife, many sense-and-avoid systems use a mix of sensors: cameras detecting both visible and infrared,radar, LiDAR, including traffic collision avoidance system (TCAS) and automatic dependent surveillance-broadcast (ADS-B). Not all aircraft are equipped with TCAS and ADS-B systems and only detect other aircraft with a corresponding transceiver or transponder.
Manual sense and avoid relays the information to the UAV pilot.The sense and avoid technology has to be small and light in weight for sUAVs,which poses a challenge. Sufficient payload capabilities, its size and weight, need consideration if using traditional methods such as radar for the detection of other aircraft. In addition, the speed of the small UAV is typically slower than other aircraft. To identify aircraft travelling at faster speeds requires a much quicker reaction time from sense and avoid technology in order to avoid collisions. Further complexities are the power consumption and battery life of UAVs, as well as the need for the technology to operate indifferent weather conditions.
The UAV industry is rapidly evolving on many fronts. For example,DJI's recent announcement of the first guidance system, a sense and avoid hardware addition. A combination of ultrasonic sensors and stereo cameras allows the UAV to detect objects up to 65 feet away and keep the aircraft at a preconfigured distance. The guidance system works with DJI's new Matrice 100 UAV.
Photo courtesy of DJI: DJI’sGuidance and the Matrice 100 UAV with the Guidance
Down the road…
This exciting new industry is still young with incredible growth and possibility ahead. Once the hurdles of safety and reliability are solved,it will open the door to allowing UAVs to share the airspace and become used for a wider range of purposes other than monitoring crops fields, utilities and the like.
The Federal Aviation Administration’s (FAA) announcement last week was welcomed news for the U.S. Commercial Unmanned Aerial Vehicle (UAV) market. On February 15, the FAA released proposed rule changes. The key components of the new proposed rules include keeping UAV’s well clear of other aircraft and mitigating the risk to people and property on the ground.
Prior to the Proposed Ruling this week exemptions were required, were lengthy and they were strict. For example, On January 5, Douglas Trudeau became the first Realtor to obtain an FAA exception to fly an unmanned vehicle to capture video of houses for sale, but he was required to follow 33 detailed restrictions laid out in a 26-page letter.
Legally flying a UAV requires the user to have a regular pilot’s license , pass an aviation medical check up, be assisted by a spotter, request permission two days in advance, and limit flights to less than 35 mph and below 300 feet.
Key takeaways of new FAA proposal
What does this mean?
In addition to the mentioned key components of the new proposed rules of safety, the proposed new ruling is opening the doors to commercial markets. The following are a few examples of possible small Unmanned Aerial System (UAS) operations that could be conducted under this proposed outline:
The industry is expanding and only limited by our imaginations
It is exciting where the UAV market is heading! We often see and hear about UAV’s snapping pictures and acquiring video. In addition to traditional RGB sensors used in consumer cameras, there are infrared, thermal, Ladar/LiDAR and hyper-spectral, including a host of other types of sensors providing information that the naked eye cannot see. As this industry continues to move forward, I suspect that similar to the defense industry, there can and will be vast amounts of data collected requiring management, dissemination and processing solutions. Hence, there is a need for a content management and dissemination system.
There is the obvious desire for real-time awareness pertaining to disaster response and news media coverage. In addition to real-time response, I believe there is a requirement for a content management system to archive data for historical trending and post processing to yield actionable information.
Over the last couple of years, we have seen news about UAVs
and their utility in commercial and civil markets. I have a particularly strong interest in UAV
technology that reaches back to my days as an Electrical Engineering student designing
a hovercraft resembling a quad copter, controlled via a software application
providing aircraft position and other telemetry back to the pilot. Adding to
this industry interest is that one of the FAA’s test sites is nearly in my
backyard, Griffiss International Airport Unmanned Aircraft Systems (UAS) in
Rome, N.Y. Furthermore, in early August 2014,
the FAA approved the Northeast UAS Airspace Integration Research (NUAIR) and
Griffiss International Airport’s first official Certificate of Authorization (COA)
to test unmanned aircraft. This first COA allows operation of unmanned aerial
system for agriculture led by Cornell Cooperative Extension (CCE). CCE has
provided tremendous benefits to our local agricultural industry and I am pleased
to see that they are getting this effort started.
CCE will fly a UAS manufactured by Precision Hawk. Precision
Hawk’s Lancaster Hawkeye Mk III, a small fixed-wing aircraft, will carry
visual, thermal and multi-spectral sensors. The UAS will fly below 400 feet over
farms in western New York evaluating field crops such as corn, soybean, wheat
and alfalfa. The collected data will be used to monitor crop growth, insect
activity, disease spread, soil conditions and more.
Photo courtesy of Finger
Lakes Times a Precision Hawk Lancaster Hawkeye Mk IIIUAV
Precision farmers today use aerial and satellite remote
sensing imagery to help them more efficiently manage their crops. By measuring
precisely the way their fields reflect and emit energy at visible and infrared
wavelengths, precision farmers can monitor a wide range of variables that
affect their crops. Multi-spectral and thermal sensors allow farmers to view
problems that were not possible with the naked eye or with panchromatic aerial
Precision Hawk’s sensors will be collecting data at the
necessary wavelengths required to extract meaningful information to answer
questions such as “what is the health of my crop”. Using a UAV as the platform
for remote sensing still requires remote sensing practices to provide the most
accurate answers to grower’s questions. A fellow colleague identified a best
practices approach to ensure generation of output products of the highest
quality to solve a problem at hand. The
best practices approach is: (1) identify the algorithm needed to solve the
problem, (2) determine the wavelength input for the algorithm, (3) establish
what sensor(s) can collect those wavelengths, and (4) decide the platform
equipped to fly the payload.
The best practices were recently applied
comparing normalized difference vegetation index (NDVI) products using raw
sensor data from a UAS payload, and data that were corrected after applying
calibration to each band in the image. NDVI is a common benchmark for
determining vegetative health.
Figure1: UAS image and NDVI calculated from original image
prior to applying any data calibration or correction.
Referring to Figure 1(raw data)
Figure 2: UAS image and NDVI calculated after applying data
calibration and correction.
The results shown in Figure 2 with data calibration and
correction produce a more accurate assessment.
The results show that to provide the grower with the most
accurate information requires more than just collecting data and running that
raw data through an algorithm. Using best practices such as those identified by
my colleague, growers can focus on specific problems or information with
different sensors and algorithms. I would imagine that as this advances, there
would be automated processes that will automatically provide answers to grower’s
The benefits of utilizing UAV’s in agriculture is being able
to see a field in its entirety, which can be time consuming and unrealistic for
farmers to do on foot. The fields can be viewed as frequently as desired and at
a lower cost than utilizing a manned airborne platform or satellite imagery.
Additionally, UAV’s equipped with appropriate sensors can
use the collected data in a science-based approach, enabling them to identify problems
faster and execute treatment plans to prevent the spread of disease or pests that
could affect an entire field. Then they can fly the fields again repeating the
process within a week or two to monitor change. According to the agronomist
from CCE that will be flying the Precision Hawk UAV, farmers are spending tens
of thousands of dollars now on crop health: how green are the plants, as well
as tracking disease and harmful insects. Efforts like CCE’s will provide
insight into the benefit of UAV’s in the agricultural industry and what the
true benefit to the grower is. Of
course, the goal is higher crop yield resulting in higher profits. In addition,
reducing crop treatment costs by targeting only areas requiring it all while
reducing the negative impacts of farming on the environment that come from
over-application of chemicals.
I look forward to monitoring Cornell
Cooperatives Extension’s effort and will keep my eyes in the sky to see if they
may be flying the vineyards around my hometown.
As we celebrated Independence Day last month, the National Day of the United States, and as I reflect on the conflicts from the 18th century to present day, there have been considerable advancements in collecting information providing intelligence and situational awareness, where knowledge of the enemy is critical.
There have been significant technological advances in every conflict starting from the American Revolution to present day. Personally, I find the evolution of tactics, techniques, and technology throughout the centuries fascinating. The following is a very high-level timeline providing a glimpse of methods to collect and analyze meaningful information to weave the story, draw conclusions and take necessary actions with an emphasis on aerial reconnaissance.
During the American Revolution, examining intercepted mail was a means of gaining knowledge of the enemy, disseminating propaganda and misinformation along with spy rings using codes and ciphers to share gathered intelligence.
The Civil War had Union code breakers decoding Confederate messages and simple visual reconnaissance from a tethered balloon gathering tactical intelligence of troop movements and regiment size for both sides. The view from one-thousand feet above provided military commanders with a platform to see for miles around and generate maps depicting the battlefield. The first wartime air-to-ground communications took place with electronic transmission of information sent from a balloon linked to the telegraph, directly to President Lincoln on the ground. Two innovations that would continue as tools of intelligence gathering during this period are wiretapping and overhead reconnaissance.
Photo courtesy of Wikipedia Union ArmyBalloon Corps: Intrepid being cross-inflated from Constitution at Fair Oaks, Virginia. The balloon Intrepid,one of six to eventually be constructed by Thaddeus Lowe and the Union Army Balloon Corps.
During World War I, there was the interception of telegrams, aerial reconnaissance and photography from airplanes. Versions of standard fighters and bombers were equipped with cameras for aerial reconnaissance. It was during WW I where air photo interpretation was first developed and the support of ground forces was nearly the only role of reconnaissance. It was during this period that the demonstration of increasing sophistication of imagery interpretation and exploitation techniques aimed at intelligence and cartography, such as the production of mosaic maps creating a broad view of the enemy’s trench network. Interpreters used stereoscopes looking for visual clues that might denote changes in the enemy’s position such as soil displacement or shadows identifying trenches, embankments, artillery batteries and troop movements.
Photo courtesy of Wikipedia Aerial_reconnaissance: An aerial reconnaissance camera of 1916 as operated by a British pilot of a B.E.2c
During World War II, aerial reconnaissance matures with collection and air photo interpretation becoming a considerable enterprise and playing a significant role for Allied victories. British and American reconnaissance aircraft were adapted combat aircraft having long range and high speed combined with the ability to fly at high altitude. They were unarmed to maximize performance while emphasizing the purpose of bringing back pictures without engaging the enemy. Analysis of photos took place at the Allied Central Interpretation Unit (ACIU) at Medmenham, with over 1,700 personnel. Photographs provided solid evidence quickly. Film could be developed, printed and interpreted within hours of a reconnaissance sortie. Photo interpreters used a stereoscope, enabling them to see in three dimensions to expose details they would not have seen otherwise. This allowed them to accurately select their targets and assess damage after bombing raids. Aerial photography and analysis played a crucial role in Allied bombing raids of the German rocket program helping to ensure the success of the D-Day landings and its eventual victory. Nighttime photo reconnaissance utilizing a high-powered flash was a significant American contribution to air intelligence providing critical intelligence about enemy strengths and troop movements.
During the period of the Cold War, there was the development of highly specialized and strategic high-flying reconnaissance aircraft to operate at altitudes well above air defenses (for the era), such as Lockheed’s U-2 and its successor, the SR-71 Blackbird. It is still going strong, outlasting its successor and has been in operation since 1955. The U-2 provided the evidence of Soviet missiles in Cuba in 1962, helping to avert a nuclear confrontation.
Photo courtesy of Wikipedia Lockheed_U-2: TR-1 in-flight (A third production batch of U-2R aircraft built for high-altitude tactical reconnaissance missions)
Today the U-2, upgraded given it greater reconnaissance and threat-detection, continues to gather and provide intelligence supporting a number of operations with its ability to direct flights to missions at short notice.
During the Cold War, there was the production and operation of strategic reconnaissance satellites. Advantages of satellite photographs is that they are available 365 days of the year with frequent revisit times, can capture large area footprints decreasing the need for creation of image mosaics, they can easily access remote or restricted areas, including hostile territory without putting pilots at risk of being shot down. The cons of satellite surveillance compared to aircraft are cost, the inability of quick placement over the target and lower resolution photographs.
These days we hear a lot about unmanned intelligence, surveillance and reconnaissance (ISR) platforms, providing situational awareness and information. Technological advances in communications allow for remote control of the vehicle and relaying data back over high-bandwidth data links in real time. An advantage of the unmanned aerial vehicle (UAV) is longer endurance flights at both high and low altitudes. Advanced sensors and full motion video have increased awareness and the information provided in near real-time; unlike the aerial information gathered in previous decades requiring development and analysis once the platform has landed.
Photo Courtesy of PBS.org: General Atomics Aeronautical Systems RQ-1 Predator.
Unmanned aerial systems have played a significant role in aerial ISR this past decade. Rapid advances in technology will continue, as they always do, and this leads me to believe that we will hear much more about activity based intelligence (ABI) and automated processing to handle greater data volumes.
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