Applications – Trajectory Magazine We are the official publication of the United States Geospatial Intelligence Foundation (USGIF) – the nonprofit, educational organization supporting the geospatial intelligence tradecraft Tue, 20 Feb 2018 16:12:19 +0000 en-US hourly 1 Applications – Trajectory Magazine 32 32 127732085 Weekly GEOINT Community News Tue, 20 Feb 2018 16:10:08 +0000 IARPA Initiates 3D Imagery Modeling Program; DoD Seeks PNT Support; Maxar to Relocate Corporate HQ to Colorado; OGC Announces Earth Observation Hackathon; More

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IARPA Initiates 3D Imagery Modeling Program

The Intelligence Advanced Research Projects Activity (IARPA) launched a new research effort to develop automated modeling algorithms that construct visual representations of satellite and aerial data. Called Creation of Operationally Realistic 3-D Environment (CORE3D), the multi-year effort will support the use of models for rapid response to military or humanitarian crises in remote areas. The activity has contracted with General Electric, Vision Systems, and Applied Research Associates to support the program.

DoD CIO Seeks Positioning, Navigation, and Timing Support

The Defense Department’s Chief Information Officer released a solicitation memo for a contractor to provide programs and systems engineering supporting the DoD’s positioning, navigation, and timing (PNT) enterprise. The selected contractor will also assess cyber vulnerabilities and potential areas of risk throughout the PNT sector.

Maxar to Relocate Corporate HQ to Colorado

Maxar Technologies announced plans to transfer its corporate headquarters from San Francisco to Westminster, Colo. The move is expected to generate approximately 800 jobs in the region, and serves to unify the company’s executive team and future shared services organizations.

e-GEOS Awarded Australian Maritime Safety Authority Contract

e-GEOS was awarded a contract to provide the Australian Maritime Safety Authority (AMSA) with data from Italy’s COSMO-SkyMed satellites—marketed as the world’s only dual-use radar Earth observation constellation. AMSA will use data from the four operational satellites to monitor oil spills and illegal waste dumping as well as to coordinate emergency operations at sea.

OGC Announces Earth Observation Hackathon

The Open Geospatial Consortium is calling for participation in its Earth Observation Exploitation Platform Hackathon. The event seeks to determine whether results from the recent OGC Testbed-13 research initiative are fit to use as a basis for future programs. Participants will establish research design decisions, identify missing elements, and choose the best solution for the upcoming Testbed-14 program. The hackathon will run from March to May, and a webinar is scheduled Feb. 19 for those interested in participating.

TerraGo Introduces New GXP InForm Application

TerraGo launched its new GXP InForm app, an add-on module for BAE Systems’ GXP Xplorer platform. InForm, built using the TerraGo Magic platform, allows users to customize forms, maps, and workflows to support diverse operations anywhere in the world. Mobile features including basemaps and forms are accessible via the app even without a network connection.

Peer Intel

Peraton announced David Myers was appointed president of its communications sector. Myers will lead the sector’s strategic development and growth in government satellite and Earth-based communications markets.

President Trump nominated Lt. Gen. Paul Nakasone as the new head of the National Security Agency (NSA) and U.S. Cyber Command. Nakasone will succeed current NSA and Cybercom chief Adm. Michael Rogers, who plans to retire by spring.

NGA’s former associate director of capabilities Dr. Anthony Vinci was promoted to the agency’s newly created chief technology officer role. Vinci will focus on integrating cutting-edge technology such as artificial intelligence, computer vision, and augmentation with the agency’s people and processes.

Photo Credit: e-GEOS

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Fitness Tracking & Privacy Fri, 02 Feb 2018 16:29:29 +0000 Strava's global heat map inadvertently reveals locations of U.S. military bases

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When exercise tracking company Strava published a global heat map visualizing where people run and cycle throughout the world, the map inadvertently revealed sensitive U.S. military data not meant for public dissemination. Because a percentage of Strava’s users are military personnel exercising with Fitbits or other fitness trackers, the heat map also revealed the locations of active U.S. military bases in war zones.

In total, the heat map shows roughly one billion activities from Strava’s 27 million global users between 2015 and 2017. Areas such as London and Amsterdam (where the app is most used) glow yellow and white, while low-activity areas are shrouded in darkness. Combat areas and remote desert locations are predictably dark, except for illuminated paths inside the walls of known and classified military bases. Users on Twitter and Reddit have already identified military installations and routine patrol routes in Syria, Ukraine, Afghanistan, Yemen, Somalia, and more.

The danger of this information’s availability online is heightened by Strava’s “segments” feature, which gives anyone with an internet connection the ability to de-anonymize data and personally identify individual soldiers. Segments are small geographic areas where users can compete with their neighbors for the best performance and compare their stats to a public leaderboard. According to Wired, anyone can create a segment via Strava, meaning anyone can see the names and times of individual Strava users in certain regions, such as those exercising at classified outposts. The Guardian, for example, was able to identify 50 service members stationed outside an airfield in Afghanistan. This could give nefarious actors the opportunity to glean patterns of life from individuals stationed at military bases—information that could be transformed into actionable intelligence against U.S. soldiers and operations.

Strava does offer users the ability to turn off data collection, but some users report being unaware of this option or confused by the steps required to deactivate location sharing. Strava CEO James Quarles addressed the controversy in an open letter: “We are committed to working with military and government officials to address potentially sensitive data. Our engineering and user-experience teams are simplifying our privacy and safety features to ensure you know how to control your own data.”

While this security oversight has garnered more press coverage than most, it is not an isolated incident. As location-based services continue to proliferate, companies will release that data for one purpose without considering security implications elsewhere, or the legal and regulatory changes that will follow. According to Kevin Pomfret, a former satellite imagery analyst and member of the Department of the Interior’s National Geospatial Advisory Committee, security lapses like this are a natural consequence of diverse businesses (like Uber and others) collecting and sharing global location data.

“I’m not sure [Strava] should be held at fault,” Pomfret said. “We’re just in this evolving nature of laws and policies that we’re trying to come to grips with. In the geospatial community, people understand these sensitivities, but all these other companies collecting and using [location] information don’t have insight into those issues.”

NPR reports the Pentagon is reviewing its GPS and wearable electronics policy to determine whether further training or guidance for service members is necessary and if smart device protocol at sensitive locations should be amended.

Photo Credit: Strava

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The Ethics of Volunteered Geographic Information for GEOINT Use Thu, 01 Feb 2018 08:02:29 +0000 The wide variety of VGI available today naturally leads to myriad potential GEOINT uses

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VGI Defined

What is volunteered geographic information (VGI)? Renowned geographer Michael Goodchild coined the term in 2007 in response to the growing phenomenon of laypeople creating and sharing mappable data via the internet. Since that time, geographers have debated the scope of the term and how it differs from related concepts, such as public participation GIS, which existed prior to Web 2.0 and its concomitant collection of user-generated content. VGI is a broad term, and one way to categorize types of VGI is to consider the intentionality of the volunteer. From most to least intentionality, we might identify five categories/levels of VGI: 1) a volunteer who is actively involved in framing the project; 2) a volunteer who helps devise the goals and collect data, but does not analyze data or make scientific findings; 3) a volunteer who knowingly contributes VGI for a particular purpose; 4) a person who contributes VGI for a different purpose; and 5) a person who unwittingly creates VGI.

Examples include persons involved in citizen science projects (Levels 1 and 2), OpenStreetMap users (Level 3), a Facebook user who knowingly shares a geotagged photo which is then downloaded and shared widely (Level 4), and a person who has unwittingly enabled cell-phone tracking on various smartphone apps (Level 5). Levels 4 and 5 might be considered contributed geographic information (CGI) or ambient geographic information (AGI), rather than true VGI. In such cases, while the contribution may technically be voluntary, the information is volunteered for a different purpose than it might ultimately be used or even unknowingly.

Broadening the discussion through further demonstrations, an example of VGI at the most collaborative levels is suggested by Dr. Mordechai Haklay, a leading researcher of GIS and citizen science: Professional and non-professional astronomers often work together on projects that are integrated at all levels, including the definition of the scientific question, field collection methods, and analysis. Haklay suggests that environmental justice projects often involve VGI at slightly less collaboration, wherein community residents work with environmental scientists to define the project goal and to collect data, but do not perform scientific analysis.

Another step down is seen in Dr. Elisabeth Sedano’s study of outdoor advertising in Los Angeles, wherein residents helped to map billboards using a web map for a project whose goals and methods were shared with the volunteers but were defined by the researcher. The lowest level of collaboration in VGI is seen in projects based on geotagged social media posts, such as tweets, as users have voluntarily shared their location but without the specific intent to add to any project beyond their chosen social media platform.

Because there is no intentional collaboration, Dr. Anthony Stefanidis of George Mason University suggests such “volunteered” data should be characterized as ambient geographic information (AGI) rather than true VGI. In other cases, users may not realize an app is set to record their location, or their location contribution may technically be voluntary, but was volunteered only as a means to be able to participate in a particular web-based activity, where consenting to provide user location, for example, is a requirement to proceed. These categorizations are important to understand; ethically, they help define the intended use of the information as volunteered by the provider.

Current Thinking on the Ethical Use of VGI

With respect to VGI contributors, the discussion of ethics generally focuses on privacy. Regarding the aggregator and distributor of VGI, ethics might also involve legal liability, responsible use, and data quality considerations. Studies of VGI often focus on social media posts during disaster and crisis events, in which data accuracy can have vital consequences, whereas private sector data quality is less an issue than invasion of privacy. In the commercial sector, outdoor advertisers are combining location-based services, big data on consumer spending patterns, and digital sign displays to make real-time changes in advertisements based on nearby individuals. One of the experts in the field of VGI is Dr. Peter Mooney of Maynooth University, Ireland. He states that private data in the VGI context are often any geographic data or information that can be linked to an individual contributor who created, collected, or edited it. A key aspect of project planning therefore is to consider whether data to be collected needs to be linked to its creator for the purposes of the project. Linkable data should only be collected if the project depends upon it and with the consent of the creator. When linkable private data are collected, protections should be established to ensure the data are only used according to the purpose for which the creator consented or to take active steps to de-link data if linking is no longer required. If linkable private data are collected, it then becomes necessary to establish some protection that ensures the data are only used according to the original purpose defined before the collection of the VGI started. When VGI data collections are considered a resource for new and maybe unforeseen beneficial uses and research, it is arguably more important that these data do not provide linkable private data about the individuals who contributed it.

In a geospatial intelligence (GEOINT) context, the question that should be asked is whether location information in itself is private data or can be linked to individuals. The answer often then depends on the location accuracy. Many location data are accurate enough to be connected to one individual or to a small group of individuals (like an office or home). Sometimes this information is even combined with precise time and date. Mooney notes that there is no common solution; rather, the collection of point-based geographic data for a specific purpose may need to have high geographic accuracy which produces a possibility that the geographic features close to the collected points could be used to infer other information. Supporting Mooney’s work, Barbara Poore, a research geographer from the United States Geological Survey, notes that the possibilities surrounding the use of location data associated with an identifiable contributor or embedded GPS information from cameras might entice an unethical use of the VGI. Finally, recognized methods to protect or hide information fidelity of data exist, such as making location information blurry or fuzzy and anonymizing the data by making private information available only per contributor’s preferences.

  • This article is part of USGIF’s 2018 State & Future of GEOINT Report. Download the PDF to view the report in its entirety and to read this article with citations. 

Possible GEOINT VGI Use

The wide variety of VGI available today naturally leads to a myriad of potential uses for VGI as GEOINT. The use of VGI can be leveraged to significantly enhance conventional intelligence capabilities for Department of Defense (DoD) and homeland security organizations. The upsurge of web-based technologies that allow individuals to voluntarily develop applications and provide information offer numerous opportunities to improve GEOINT collection, management, retrieval, and dissemination. VGI technologies currently being developed and used by the mainstream population can likely be adapted for use with multi-echelon security access. In this, the use of VGI type sites as a structure for collection, management, retrieval, and dissemination of classified geographic information could provide the defense and intelligence communities with quickly evolving and continually improving technologies.

Recent lessons learned from operations in conflict areas such as Afghanistan and Iraq have demonstrated a need for improvements in GEOINT collection methods. VGI is a potential mechanism for increasing the number of sensors populating information databases. In this context, every person on the battlefield (including soldiers) is a sensor; therefore, all those on today’s and tomorrow’s battlefields are possible GEOINT providers. Careful investigation, however, into potential incentives for volunteering information is necessary to fully understand the quality of the data provided. The management of intelligence using newly developed technologies and methodologies is significantly different from conventional schemes. In this, a number of questions arise:

  • Should databases be populated without restriction and how is the accuracy of the information verified? Contributors may interpret the world differently. For example, what someone calls a bus terminal may be a bus station, stop, or bench to someone else.
  • Is a database manager needed to supervise the data published? Some algorithms for data validation might not be able to reach common sense conclusions that a human monitor would be capable of reaching. New technologies now allow the users to become database managers. Websites such as eBay and Amazon allow users to rate each other. Wikimapia allows users to change previously submitted VGI.
  • Is it possible for a VGI site to be self-correcting, self-improving, and self-assessing in order to continually judge the quality of the information? A meticulous study of the supervision methods for the provided information is required. In this, data comprehensiveness for VGI should be considered, as many people are not volunteering their information, which could lead to bias in the data or skewed datasets if some users submit multiple VGI. In some cases, a person’s use of multiple devices could lead to the impression that the VGI is from multiple people.

LTC Ian Irmischer, Ph.D., from the United States Military Academy at West Point, noted that from these questions, it appears that GEOINT searches inherently arise from the possibilities of vast information collection. A powerful geospatial search engine that appropriately prioritizes information is essential for the efficient use of VGI. Recognizing that national security users often need geospatial information for immediate response situations, the search engine should be able to conduct network analysis of requested information and analyze the spatial components of the data. Standardization of automated metadata inclusion is likely required to allow the users to query and access needed intelligence. As a result, the compiled VGI must be able to be disseminated and visualized by the user facilitating interoperability between provided data formats and a common operating platform that can be efficiently interfaced by sensors and operators.

Defense and intelligence users would require limited training if currently existing VGI collection methods were integrated. Sites such as Google Earth and Wikimapia are intuitively designed, have widespread use, and are familiar to citizen sensors, organizational sensors, and operators in need of information. Resultant from all of this, VGI has many compelling uses for operators that require GEOINT for situational awareness. The use of citizens as sensors vastly increases the possible GEOINT collection capabilities by governmental organizations. A detailed examination of how VGI and associated technologies can improve the collection, management, retrieval, and dissemination for these organizations could advance local and national level crisis reaction and security.

The National Geospatial-Intelligence Agency (NGA) has progressed quickly into the VGI space through its creation of the NSG Open Mapping Enclave (NOME). NOME is an online tool kit that allows the National System for Geospatial Intelligence (NSG) to contribute and benefit from the power of open content. As a crowdsourcing method to harness tools to create, assemble, and disseminate geographic data provided voluntarily by individuals, crowdsourcing products such as Wikipedia and OpenStreetMap collect useful geospatial information for NGA analysts to produce GEOINT products. By allowing users to contribute their expert knowledge to maps, VGI opens up geospatial data to communities that in the past would rely on their own limited collection resources and proprietary technologies. NOME challenges conventional geospatial collection and dissemination methods to reduce costs, improve accuracy, and enhance mission planning and execution.

The use of VGI for GEOINT is also relevant to humanitarian assistance and disaster management operations and functions. In his work on crowdsourcing VGI, Flávio Horita concluded that the scientific literature about the use of VGI in disaster management is growing, with a significant increase in the number of publications since 2010, noting that the predominant research area was disaster response. Fewer studies were devoted to mitigation and preparedness, while none dealt with recovery. His explanation to this was that response is the most visible part of disaster management and is also more likely to attract the attention of volunteers. However, the challenge for researchers remains how to advance knowledge about methods that include VGI in mitigation and preparedness activities such as risk analysis and early warning systems, as well as in the recovery phase, by helping communities reorganize their routine and create mechanisms to prevent disasters from happening in the future. Horita continued, “This research also showed that VGI is commonly used to manage floods and fires. The prevailing media for sharing VGI was found to be social media (i.e., Twitter, Facebook, YouTube, etc.) and mobile devices. Interestingly, very few of the reviewed papers address VGI platforms like Ushahidi2, Elva 3, OpenStreetMap, and Wikimapia.” 

Ethical Use of VGI for GEOINT: Do the Rules Change?

There are ongoing discussions about the ethical use of VGI for GEOINT and whether the standard ethical considerations for VGI use apply. There is concern for targeted data analysis and use, and there appears to be potential for both positive and negative impact. Four areas of concern are noteworthy:

  • Data exploitation methods (including commercial, online, and offline use cases).
  • Relevant, geographic scale.
  • Bounded areas of data exploitation (geo-fences, group audience demographics, etc.).
  • Individual protection considerations.

Stefanidis noted in his GeoJournal article that harvesting VGI and ambient information brings forward novel challenges to the issue of privacy, as analysis can reveal information the contributor did not explicitly communicate. Stefanidis said this is not a new trend. For example, Google uses the information it collects to improve its customer service. Similarly, Twitter makes money by licensing a tweet gateway to search engines, while companies can pay for “promoted tweets.” This trend has already spread to location information. For example, TomTom uses passively sensed data to help law enforcement determine the placements of speed cameras. iPhones store location data of which the user may be unaware. Stefanidis said the public is making progress in highlighting the issue of privacy-relinquishing when sharing location information. Sites and apps such as and Creepy (a geolocation aggregator) have demonstrated the potential for aggregating social media to pinpoint user locations. In this, trying to protect people’s identities in times of unrest is also a well-recognized concern. For example, the Standby Task Force suggests ways of limiting exposure and delaying information for the recent unrest in North Africa. Stefanidis further stated, “But the power of harvest AGI stems from gaining a deeper understanding of groups rather than looking at specific individuals. As the popularity of social media is growing exponentially, we are presented with unique opportunities to identify and understand information dissemination mechanisms and patterns of activity in both the geographical and social dimensions, allowing us to optimize responses to specific events, while the identification of hot spot emergence helps us allocate resources to meet forthcoming needs.”

Although ethical concerns exist with the use of VGI for GEOINT, we posit some recommendations for going forward: 1) security and safety of the collective takes precedence; 2) personal information may and should be leveraged to ensure the security and safety of said person; 3) accepted, generalized, targeted information passing (aka advertising) should be used as a starting point when communicating general alert notifications; 4) VGI identification can and should be used for general (non-targeted) reverse information passing; 5) more descriptive VGI identification can and should be used for targeted information passing in response to a disaster/emergency/conflict; and 6) caution should be used when using VGI identification for psychological operations in a mission plan (often connected to some form of a military, operational response).

Inherent in the recommendations is that security is a vulnerability, especially with advances in technical capabilities and increasing sophistication of sponsoring enterprises (criminal, opposing government, or otherwise). Security breaches are becoming more common (or more commonly reported), whether accidental (such as a lost, unencrypted laptop or careless disposal of old equipment) or intentional attack. At some point, security breaches are a possibility. In not knowing how the compromised data will be used, unpredictable consequences can ensue. From this and in concert with the recommendations above, targeted advertising and information passing (from the third recommendation above) represents a base level in which no personal information about an individual is necessary. More descriptive VGI identification (from the fifth recommendation above) is recommended when safety is paramount and response time could be a life or death situation; the more information available to assist in evacuation and rescue efforts, the better. In this, one must keep in mind that first responders (in the field) may not have time to sift through data. Someone offsite (or resident within an app) would likely need to filter the information down to the necessary components for the responder to act quickly. More information can sometimes be too much information, depending on the context. Finally (from the sixth recommendation above), in conflict or psychological operations, deadly consequences could result if the opposing force acquires the information, whether or not the VGI aggregator/distributor is aware of the obtainment.

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The Vanguard of Commercial GEOINT Wed, 31 Jan 2018 17:20:46 +0000 From self-driving cars and “drones as a service” to crowdsourcing exercise routes, the commercial world continues to leverage GEOINT in new and creative ways

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First we told our devices how to locate themselves, then we gave our computers the power to parse the profusion of data those devices generate. Now, those devices are returning the favor by providing useful information about the world around us. But many of us have only begun to realize all the possibilities these changes have opened after creeping up on us from multiple directions.

“We sort of slouched into it,” said Dr. Todd S. Bacastow, a professor of practice at USGIF-accredited Pennsylvania State University. “It’s certainly been within the last five to 10 years that we’ve begun to see this massive amount of data and all the opportunity within it.”

Around 25 years ago, only approximately 15 percent of the information collected in the world was geo-tagged, observed Dr. Steven D. Fleming, a professor of spatial sciences with the University of Southern California’s Spatial Sciences Institute, which is also accredited by USGIF to grant academic GEOINT Certificates.

Now? “Most of the world’s data is geo-tagged—I think it’s 85 to 90 percent,” Fleming said. “We know where a banking transaction starts and where it ends. We can track digits. We can certainly track where people are.”

That’s the story of how geospatial intelligence (GEOINT) has generated new perspectives on the natural and built environment. But the next chapter—how companies take these possibilities and turn them into new products and services—includes many plot twists.

These four companies illustrate only a few of many ways the commercial world is leveraging the power of GEOINT.

Teaching Cadillacs to Drive Themselves

The form of GEOINT many people know best is the digital map—for example, the latest Geography 2050 conference in New York City focused entirely on mobility. The ability of a phone to locate itself and then offer directions customized to traffic conditions was the stuff of science fiction 30 years ago. But as impressive as the digital cartography of Google and others can be, it’s not precise enough to feed directly to a self-driving vehicle.

So Cadillac decided to commission its own maps before it could include its highway-only Super Cruise self-driving option in the 2018 CT6. The carmaker turned to a Livonia, Mich., firm named Ushr to take navigational mapping to the next level.

“The difference about an autonomous driving map versus a navigation map, we’re concerned about the lane delineators, the slope of the road,” said Chris Thibodeau, senior vice president of Ushr. “In a navigation map, none of that information is needed.”

Plus, an autonomous driving map needs accuracy beyond what GPS can deliver—down to 10 centimeters. Ushr sent cars packed with LiDAR sensors on a tour of America’s highways—220,000 miles driven since 2013.

“It took us about a year and a half to collect and process all that data,” Thibodeau said.

Layered over original LiDAR imagery, Ushr roadway data includes details like cross-slope, lane width, lane markings, and more, all globally geo-referenced to sub-10 centimeter accuracy. Data is available every 0.5 meters along the road. (Image credit: Ushr)

In September, I had the opportunity to take a CT6 on loan from Cadillac for a test drive from Washington, D.C., to Cleveland, and the results were a kind of magic: Once the CT6 recognized it was on a highway in its database, a steering-wheel icon lit up on the dashboard to advise me that Super Cruise was available. I’d press a button to activate this mode, and the top of the steering wheel illuminated in green to show the car had taken over.

Informed by its database, the CT6 stuck to a lane as if it were a rail, slowing and accelerating as needed to compensate for traffic around me. All I had to do was keep my eyes focused on the road ahead—something the car itself watched for, using an inward-facing camera to ensure I was still paying attention.

Ushr is now looking to drive down the costs of its mapping solution, in part by applying machine learning techniques to recognize road features such as stop signs and crosswalks.

“We’re also spending a good amount of engineering resource today on basically automating those feature identification and feature extraction algorithms,” said Brian Radloff, Ushr’s vice president of business development. He added this would allow Ushr to begin mapping secondary roads.

Cadillac might not need that data—company president Johan de Nysschen told me in 2016 that bulky LiDAR sensors needed to detect pedestrians would not fit with a Cadillac’s style—but Ushr has other customers in mind.

“Some municipalities are looking at potentially using this data [in place of conducting their own surveys] if it’s accurate enough,” Radloff said. “When Amazon’s talking about things like drone delivery having a very precise HD map those drones can follow [it could] be another kind of further-out-there application of this technology.”

Bringing Eyes to the Skies—For Rent

Unmanned aerial vehicles, more commonly known as drones, are one of the most public symbols of GEOINT’s new era. But many companies that could benefit from the ability of drones to extend human senses to places that are difficult or dangerous for humans to reach lack the budget and expertise to buy their own systems.

That’s where D.C.-based Measure comes in, offering drones and analytical tools clients can hire for particular jobs. This business model—what it calls “Drones as a Service”—has given the firm extensive insight into what drones can and cannot do.

“Agricultural is probably one of the most overhyped applications for drones,” cautioned Abigail Lacy, Measure’s vice president of sales. “Anybody you talk to who’s been in the drone space for more than two years would probably tell you that.”

A drone’s different perspective can, however, make a difference at the margins by gathering data points about exactly where in the field a crop is flourishing or struggling.

“A lot of them really derive from just having the eye in the sky—not just the RGB, but the NDVI,” Lacy said, referring to the Red-Green-Blue of traditional imagery and the Normalized Difference Vegetation Index that a near-infrared camera can produce to indicate the presence of live vegetation.

That, in turn, can allow for a more precise, cheaper application of fertilizer.

But many farmers remain skeptical. “They just tend to be slow adopters when it comes to technology,” she continued. “They’re really hesitant to drop money on all of this different equipment.”

Measure is more bullish about the potential for drones to provide insight for industries such as construction and energy. Lacy cited solar farms as one example, touting the ability of drones to answer questions before construction, such as: “How productive will the solar farm be?” and “Am I going to have water runoff issues on the site?” Once the site is in operation, drones can help identify malfunctioning panels.

Measure doesn’t disclose its rates, but Lacy cited internal research that the company’s service can yield $7,200 in annual savings on a 10-megawatt solar facility compared to traditional inspections.

She noted drones don’t just operate at a lower cost than manned aircraft, they can also get lower to the ground. The firm relies mostly on visual and thermal cameras.

“We are keeping a close eye on how LiDAR is evolving,” she said, but added that so far costs are too high and quality is too low.

The firm also often has to deal with a lesser GEOINT hindrance—every company seems to have its own proprietary software. “You’ll get 15 different software providers that all have a unique system,” Lacy said.

Measure hopes automated data processing will cut down on its own overhead, but the real “game changer” would be automation of a drone’s flight—which, in turn, will require a loosening of regulations that today ban drone flights beyond a human operator’s visual line of sight.

Fusing Maps and Live Data

Now that so many mobile devices come equipped with GPS receivers—meaning the apps on those devices can also geo-tag user activities—coping with the massive scale of the resulting data becomes a challenge.

“As the variety of channels and devices that connect customers, companies, and physical assets increases, so too do the ways to measure and analyze spatial information,” a 2016 Forrester report observed. “One of the great challenges for effectively making use of location data has been integrating it with other data sets and analysis to provide deeper context and insight.”

That’s a big theme in the work of MapD, a D.C.-based firm that’s made a specialty out of integrating live data with maps.

One of its most fascinating demos tracks the last several weeks’ worth of geo-tagged tweets around the world, placing them on the map and color-coding them by language. Users can search for keywords and hashtags or just float the cursor across countries to see what is trending. For example, the large rectangle hovering over Finland turns out to be @EveryFinnishNo, a bot that tweets out the Finnish word for a new number every minute.

Another MapD demo offers a similarly granular look at ship movements around the U.S. from 2009 to 2015, both offshore and in lakes and rivers. “Tug” is overwhelmingly the most popular type of vessel, with more than five billion records.

MapD’s New York City taxi ride data set currently totals approximately 1.2 billion records. (Image credit: MapD)

A third demo provides a look at nearly seven years’ worth of taxi rides across New York City, from 2009 to 2015. During that time, cash transactions outnumbered credit, at more than 632.1 million cash transactions versus more than 510.8 million credit—while more than 2.2 million rides were recorded as going uncharged.

The massive computational power provided by GPUs is critical to these efforts.

“GPU computing is really going to take data to the next level and analytics to the next level,” said Monica McEwen, MapD’s vice president for U.S. federal customers. She pointed to how this revolution in processing power allowed Verizon Wireless to accelerate its analysis of network problems.

“Historically, they had to do that in batch mode,” she said. “Today, they’re looking at that in real-time.”

Also important: Ensuring interfaces scale up to meet a density of data she predicted will mean “being able to display literally billions of records and have a response time in the milliseconds.”

“The pure volume of [data] makes it nearly impossible to present it in a fashion in which people can make meaningful sense of it,” McEwen said. As a result, MapD’s interfaces let users easily add or remove layers of data so they can focus on particular variables.

Crowdsourcing Exercise Intelligence

Strava, a workout-tracking app popular with many cyclists and runners, has a different challenge to address. Mashing up the location reports it gets from users can inform individual Strava athletes looking to find popular routes on its heatmap.

That trove of data soon caught the attention of urban planners, and that led to a complementary product: a database of cycling and pedestrian activity over time called Strava Metro.

“We started hearing from departments of transportation who said, ‘This is cool, but we can’t see the temporal details,’” said Brian Devaney, sales and marketing lead for Strava Metro. “We had to figure out a way to get all those GPS pulse points and aggregate them and anonymize them.”

Strava’s Global Heatmap of New York City reveals popular routes and activities. (Image credit: Strava)

Combining the heatmap with Metro required the firm to address privacy risks.

Part of its answer is privacy options. Users can choose to place a geo-fence around a home, office, or other location, hiding it and the last 500 meters of a route from the view of others. A more comprehensive enhanced privacy option suppresses even more data from the feeds of other Strava users, down to your last name.

The company won’t say how many users have exercised either option, but many customers never touch the default settings. To keep their information safe as well, Strava aggregates individual GPS measurements without reference to where users started and ended their workouts. The result is an alternative map in which a major highway like Interstate 66 in northern Virginia vanishes from view, while the bike trail next to it glows yellow but leaves no hint of where along the path one person started or ended their ride or run. Strava’s underlying maps, developed by D.C.-based Mapbox on top of cartography from OpenStreetMap, automatically show bike-and pedestrian-hostile roads in gray. Even in small towns like rural Lincoln, Va., enough users walk, run, or bike to leave a dense web of trails on Strava’s heatmap. To use this to get a sense of an individual’s whereabouts, you’d need to know where they live first.

Strava Metro, launched in 2014, offers customers not just the heatmap’s static view (updated once a quarter) of overall movements but also minute-by-minute data about how many people went in one direction on one street. Again, the company boils its data down to GPS points, this time showing direction and time, while removing everything else.

“We do buffer for privacy,” Devaney said of the company’s decision to obscure the start and end of a workout route.

And users can opt out of having their data used in Metro at all, although only “a fraction of a percent” have done so.

Customers such as city and state transportation departments as well as cyclist advocacy organizations use this data to plan or push for improvements such as bike lanes and wider sidewalks, then audit how the new infrastructure performs.

They can learn what corridors are most busy during peak commute times versus on weekends,” Devaney said. “A lot of groups are using the data to understand how behavior changes after they put in infrastructure.”

You can imagine that this data would also be enormously attractive to such businesses as athletic-wear manufacturers, but Strava has chosen to limit its sales of Metro data to organizations “working to influence policy and infrastructure.”

Eschewing commercial use of data gathered from workout-tracking apps happens to line up with one of the core privacy principles put forth last year by the Future of Privacy Forum.

What’s Next? Megacities, Drones, and Small Sats

In terms of its commercial evolution, GEOINT is barely old enough to run for office. What could it look like by the time this roughly 25-year-old discipline is old enough to run for president?

USC’s Fleming said a larger trend—humanity’s move to large cities, in which the height and volume of buildings make the traditional references of GPS unusable or suspect—will force a switch to more resilient location technologies that work better inside and next to large structures.

“We’re piling up people along the coastlines of the world, so we have to deal with megacities better.”

Many smartphone users have already seen this problem when location-based apps lose a GPS signal, decide a nearby WiFi router that happens to have been moved from one venue to another is just as valid, and vault the user to a spot miles away.

Fleming also expects drones to become even more on-demand, “where everyone expects them to be around and they’re providing things like public safety services.”

But a world in which the whine of quadcopter rotors is a normal part of the background din may take some persuasion by drone vendors.

Fleming’s colleague Andrew Marx pointed to a different form of GEOINT system: small sats.

“The advantage of a small sat is you can build up an activity of an object,” Marx said. “You can have so many repeat observations.”

But adding this temporal dimension to GEOINT will require further innovation to display it. The tasks MapD and Strava already face will only grow more arduous.

“It’s a struggle, because we’re trying to depict things in four dimensions,” Marx said.

Penn State’s Bacastow, meanwhile, warned about two trends people might not appreciate as much.

One is which countries are focusing their efforts in this area. “Many of our students in AI and deep learning are not from the U.S.,” he said, referring to a recent presentation by the University of Missouri’s Dr. Curt Davis. “Counting publications, you’d find that scholars from other countries, such as China, have a significantly larger number of publications than scholars from the U.S.”

Another is how different generations view the privacy implications of having their geo-location harvested by smartphone apps. Bacastow recounted a freshman seminar he taught two years ago about geospatial privacy.

“I thought students would be concerned and engaged in a seminar about their loss of privacy,” he said. “Quite honestly, they didn’t care. For them, while they understand the loss of their location privacy, as one student put it, ‘I want my pizza delivered to the right place with the push of a button.’”

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Weekly GEOINT Community News Mon, 11 Dec 2017 17:32:56 +0000 SpaceFlight to Launch 11 Satellites in January; Boundless and Monsanto Partner to Support Open Source Community; Avenza Maps Launches in GEOINT App Store; More

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SpaceFlight to Launch 11 Satellites in January

Rideshare service provider SpaceFlight announced the launch of 11 spacecraft from India’s Polar Satellite Launch Vehicle is planned for early January. Systems to be launched include Finland’s ICEYE-X1 SAR microsatellite, four Spire Global Lemur-2 cubesats, Astro Digital’s Landmapper-BC3, AMSAT’s Fox-1D cubesat, and others. The cubesat integration is already complete and the cargo is currently en route to India where it will await takeoff.

Boundless and Monsanto Partner to Support Open Source Community

Boundless and agriculture company Monsanto announced a partnership to contribute code to the Free and Open Source Software for Geospatial (FOSS4G) community. Among the contributions are: an OAuth Plugin that enables QuantumGIS users to determine what data on the system is accessible to the user; a CKAN plugin for QuantumGIS; and a Geoserver XAuth plugin. These codes will help establish smoother authentication systems and provide easier access to data for open-source users.

General Dynamics Awarded U.S. Air Force Operations Contract

General Dynamics Information Technology won the U.S. Air Force Distributed Mission Operations Center contract for infrastructure, development, and engineering support at Kirtland Air Force Base in Albuquerque, N.M. The ID/IQ contract is valued at $47 million, and enlists General Dynamics to develop and maintain simulation software and hardware, build network infrastructure, and integrate a live, virtual combat environment for warfighter training.

CACI Wins Army Airborne C4ISR Task Order

CACI International was awarded a $91 million task order to support the U.S. Army Communications-Electronics Research, Development, and Engineering Center’s flight activity, primarily focusing on surveillance and communications. CACI will provide systems integration, training support, and electronic and mechanical engineering design services. The company will also test new technologies in areas such as radio frequency, electro-optical, thermal, radar, and acoustic systems.

Avenza Maps Launches in GEOINT App Store

Avenza Systems has partnered with NGA to bring its Avenza Maps offline mapping application to the GEOINT App Store for download by defense and intelligence community users. The app allows users to import and access proprietary or classified maps, and includes unlimited access to the Avenza Map Store’s existing repository of digital maps. User-owned maps can be uploaded to the store for sale at the user’s discretion.

Northrop Grumman Retains Army Logistics Contract

Northrop Grumman will retain its nine-year, $750 million Army logistics services contract for support of aircraft used in intelligence, surveillance, and reconnaissance missions. The defense contractor will be responsible for program management, systems engineering, supply chain management, and aircraft modifications and upgrades to 75 ISR aircraft.

Photo Credit: Northrop Grumman

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Mapbox: Empathy and Fire Wed, 01 Nov 2017 14:48:40 +0000 Q&A with Robert Ames, director of government business and technology strategy

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Q: When did you begin working at Mapbox?

I joined Mapbox in March. Prior to that, I spent six years at In-Q-Tel—a technology innovation channel funded by the government. Before that, I spent 11 years at IBM, where I was deputy CTO for IBM Federal.

Q: Even though Mapbox employees don’t have official titles (and you made up one for the purposes of this interview), is yours a new position within the company?

It is a new position, recognizing that government is a big part of Mapbox’s business. I bring experience in inserting technology and innovation into government missions, and I bring a deep understanding of technology and mission problems that can be addressed by the emergence of mobility and the richness of location data.

Q: How has mapping fundamentally changed in the last decade, and what role has Mapbox played?

In the past five to 10 years, maps have gone from being this very fixed, stagnant, paper concept—a hard-to-consume medium, like pulling an encyclopedia off the rack—to being highly dynamic, responsive, and customizable. Today’s maps fuse contextual information such as what restaurants and friends are nearby.

Q: How is Mapbox preparing for the future of GEOINT?

In three important ways. First, we’re developing the mapping platform for the future. That platform is going to be critical in the mobile world. When you think about people deployed with limited connectivity, making these maps accessible at a low bandwidth is an area we’re taking forward for GEOINT.

Second is this notion of context—how do I understand what’s going on around me, in the past and currently, and how do I optimize my experience or outcomes?

Third, we see a future in which users can interact with maps in the space around them through augmented reality. Imagine being able to interact with a three-dimensional representation of the Earth that moves with you. This isn’t happening in the distant future, but soon.

Q: What do you consider most compelling among Mapbox’s projects?

Definitely the virtual reality space and its implications for mapping and GEOINT. Another exciting area: We want to bring machine learning and artificial intelligence to augment everyone’s understanding of their surroundings and continue to enrich people’s context around a map. We see our competitors moving in this direction, and we are actively investing in this area. Look at Snapchat’s SnapMap, which Mapbox helps power. It maps geo-tagged snaps that users have decided to share. If I’m interested in what’s going on in Dupont Circle or Trafalgar Square in London, or anywhere people are actively creating content, I can open SnapMap and see that content as a hotspot. It’s completely customizable, and the interface is intuitive and fun with this cartoony, emoji feel. But it is a very powerful and rich example of the future of context.

Q: What is surprising about Mapbox?

People are often surprised about our breadth and depth. We are the people that often enable the mapping you use, but you don’t necessarily know it’s Mapbox. Our maps are installed in approximately 4,000 applications worldwide.

Q: Your hiring strategy is somewhat nontraditional. According to your company website, “empathy” and “fire” are two traits Mapbox looks for in its employees. Can you explain this?

The company was founded by Eric Gundersen. He was inspired to create Mapbox when he was struggling with inferior maps while trying to monitor elections in Afghanistan. His intention was clear—to help make the world a better place. That’s led to the ethos of finding people who are passionate, no matter what their professional history. I’m an example of that. Before I got into IT, I was a professional opera singer.

Q: What results from cultivating a workforce with myriad backgrounds?

Mapbox has a diverse set of employees who come from rich and varied backgrounds. I believe this leads to an understanding that people interact with maps and information in very different ways. We believe it’s important to customize maps, the experience to the user, and the environment with dynamic styling. Cartogram, for example, allows you to upload a picture, and the application will style your map to match that picture. I took a picture of my cat, so I have my cat map. We just released a mapping style a week ago that looks like comic books. Things like that are the results of having folks from all backgrounds.

Q: What’s most exciting to you about the modern GEOINT space?

What’s interesting is that GEOINT is everywhere, because we all want to know what’s going on around us. Because of that, innovation is pouring in. I’m taking my daughters to Rome in a couple weeks. My entire search on activities and sites in Rome is a GEOINT-type application. I use such tools as Foursquare, which is powered by Mapbox, to identify interesting places. So if I want to take a tour, I find out where it is, what’s around it, and I read reviews—but it all starts with a geo-query. Then you go to social media and say, ‘I’m visiting this area, what should I do, what shouldn’t I do?’ and you get recommendations about places. We’re all thinking GEOINT without knowing it.

Featured image: Robert Ames (standing) speaks with colleagues at Mapbox’s D.C. office. (Credit: Marissa Fullord/Mapbox)

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Enabling Rapid Response Wed, 01 Nov 2017 13:05:43 +0000 Geospatial intelligence proves a powerful tool for paramedics

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In the Emergency Operations Center, a dispatcher takes a bystander’s cellphone call about a car crash on a poorly marked rural road. The report prompts the dispatcher to send regional air medics as well as the nearest local ground EMS crew. Next door, EMS managers analyze response statistics for a rapidly growing residential area.

Across town, an EMS crew teaches citizen CPR in a neighborhood with a high cardiac arrest rate. After training, a smartphone app will be integrated with EMS dispatch, so bystander CPR can be started in public spaces before EMS arrives. All of these activities, some long established and others cutting-edge, rely on geospatial intelligence (GEOINT) data and technology to save lives, yield better patient outcomes, and improve agency efficiency.

Early EMS operations used “static deployment,” with a set number of vehicles assigned to permanent stations. In the 1980s, increased call volumes without equal investment in EMS systems led to system status management, which was intended to optimize coverage based on temporal patterns of use.

The advent of computer-aided dispatch and automatic vehicle locator technology allowed dispatchers to determine the closest available ambulance for a call, but it took near real-time analysis and predictive analytics to make the deployment and use of resources truly effective. As economic stresses mandate that services accomplish more with fewer resources, dynamic deployment has become a mainstay in providing efficient and cost-effective coverage.

Dynamic Deployment

“In dynamic deployment, ambulances are directed toward the highest uncovered demand at that moment in time. Some call it ‘chasing the blob,’” said Dale Loberger, an active EMS member and a developer at Bradshaw Consulting Services, which developed the Mobile Area Routing & Vehicle Location Information System (MARVLIS). “Demand is constantly being re-evaluated in near real-time and resources are being matched to that demand as their level of availability changes.”

The MARVLIS system models the probability of future call locations based on historic data, near-real-time inputs such as dispatch and response times, and factors such as traffic conditions. The automated forecast is modeled through Esri’s ArcGIS platform and displayed as a mapping interface. Combined, MARVLIS GPS data, GIS modeling, and wireless communications allow EMS to “have the right units at the right places at the right times,” Loberger said.

The lower response times and decreased distances enabled by systems such as MARVLIS and Optima Predict from Intermedix help save lives in the subset of patients that must be reached in four minutes or less to survive. Jersey City Medical Center EMS doubled its return of spontaneous circulation rate in cardiac arrest victims after integrating MARVLIS into its operations in 2012.

A University of Pittsburgh team modeled fatal vehicle crash rates in Pennsylvania from 2013-2014 and distances from trauma resources using Fatality Analysis Reporting System data. They discovered a theoretical 12.3 percent decrease in mortality if two medevac units were to be reassigned to the higher-incidence areas.

“There was a big disparity for these patients, depending on where they live,” said Joshua Brown, a general surgical resident at the university medical center and lead investigator on the study. “It’s only recently that trauma systems analysts have begun to incorporate GIS tools into their work to achieve improved outcomes. That we could potentially reduce mortality by relocating only two helicopter units was a very powerful finding.”

Community Engagement

Focusing resources strategically to improve patient outcomes involves more than ambulance placement. According to the American Heart Association, more than 350,000 out-of-hospital cardiac arrests occur in the United States each year. Only 5.5 percent of these victims survive to hospital discharge. Improving survival rates from sudden cardiac arrest is a holy grail among the EMS profession, and providers are combining geo-location data, GIS modeling, and smartphone apps in this quest.

In Mississippi, American Medical Response analyzed new data for geospatial patterns, looking for hotspots associated with neighborhood type, rural versus urban patterns, and similar factors. In the Jackson metropolitan area, they discovered an association between citizen CPR/Automated External Defibrillator (AED) training and bystander CPR rates in certain neighborhoods. Since bystander CPR/AED use can double or triple the chances of surviving cardiac arrest, AMR increased outreach training to the areas with high arrest and low training rates. Improved bystander CPR and increased survival rates followed.

PulsePoint AED is a crowdsourcing app that allows users to report the location of AEDs in their community. (Image credit: PulsePoint)

“So much can happen during the critical minutes of an emergency,” explained Michael Arinder, M.D., director of clinical services for the south region with American Medical Response. “We recognized that we had the ability to see what happens in the moments before the arrival of trained personnel and we decided to use that to better serve the community. We knew that if it saved only one additional life, it was worth it.”

This focus on bystander CPR/AED inspired PulsePoint to create a smartphone app suite to bring citizen rescuers to the cardiac arrest victim. The PulsePoint Respond app sounds an alert when a cardiac arrest occurs in a public place. Users in the agency-defined notification area will see the victim’s location on a map. PulsePoint Respond incorporates data from PulsePoint AED, a crowdsourcing app that allows users to report the location of AEDs in their community. The AED location data is made available in PulsePoint Respond after being verified by local authorities. 

“PulsePoint is the marriage between technology and citizen engagement,” said PulsePoint spokesperson Shannon Smith.

To date, PulsePoint Respond has been activated more than 20,000 times and has more than 59,000 users.

911 for the Next Generation

Crowdsourced traffic information is another valuable geospatial tool that can benefit the EMS community. Genesis PULSE, a vehicular tracking system used for dynamic deployment, exchanges data on road closures and traffic conditions with navigation app Waze.

Data after the first year of information exchange revealed that in 62 percent of cases Waze obtained accident notification up to 4.5 minutes faster than 911 centers. Although the implications are unsettling, Waze data provides PULSE users an advantage in rapid deployment—if, as in all GEOINT use cases, the data is accurate.

All geospatial data requires accuracy to be useful, but in public safety, accuracy can make the difference between life and death. Leaders in the field consider this a primary public safety challenge.

“Geographic Information Systems, when coupled with first-responder missions, private industry, and public policy can improve operational understanding and help PSAPs (public safety answering points) create and maintain reliable, dispatchable address databases,” said Mike King, emergency call-taking and dispatch industry manager for Esri as well as a member of the National Emergency Number Association. “All three disciplines are necessary for true success.”

The Next Generation 911 (NG911) initiative, spearheaded by U.S. Department of Transportation, seeks to design an emergency communications architecture that will transcend current limitations. Wireless mobile devices, Voice over Internet Protocol telephoning, and other modern technologies have rendered the 911 call center system outmoded.

According to King, core GIS capabilities, wireless and broadband use, and 3D routing technology, particularly for indoors, will be incorporated into NG911, but the parameters and solutions are evolving with the initiative.

Startup RapidSOS hopes to end geo-location fuzziness with a database that seamlessly integrates with 911 call centers. A cellphone call to 911 will ping the RapidSOS database, and geolocation information will be supplied to the 911 center. In trials, RapidSOS provided more accurate geo-location information than the wireless carriers tested.

EMS relies increasingly on GEOINT to provide effective healthcare.

In the coming years, the technology will continue to evolve with the proliferation of predictive artificial intelligence and machine learning algorithms, according to Nikiah Nudell, chief data officer for The Paramedic Foundation and a board member of the National EMS Management Association.

“Geospatial intelligence has become a powerful worldwide tool for paramedic chiefs and the public health and safety officials they often work with,” Nudell said. “In an environment where limited resources are being used to respond to dynamic critical incidents, having full situational awareness from an historic and real-time perspective is powerful.”

Featured image: The MARVLIS system models the probability of future emergency call locations based on historic data, near-real-time inputs such as dispatch and response times, and factors such as traffic conditions. (Credit: Esri)

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GeoQ Meets GitHub Wed, 01 Nov 2017 13:02:06 +0000 The power of the crowd builds upon NGA’s open-source platform to better equip first responders with geospatial information

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Accurate, up-to-date information is a first responder’s biggest asset. Data about infrastructure, passable roads, regional populations, and supplies is essential in a crisis, and can be more difficult to obtain in underdeveloped countries. Without immediate access to the right data, first responders scramble to assess damage and lose valuable time that would otherwise be spent helping people.

To assist with relief efforts in both domestic and international disasters, the National Geospatial-Intelligence Agency (NGA) developed an open-source web application that collects unclassified imagery from nontraditional sources. Called GeoQ, the tool is accessible on any internet browser and pulls together geo-tagged data from social media, maps, news, Earth imaging satellites, and more to provide response teams with a holistic picture of disaster areas in real time.

The problem we realized was a lot of people didn’t have this GIS or remote sensing background. They wanted something easy and intuitive to use, and that’s where GeoQ comes into play.
—John Mills, Penn State Applied Research Laboratory

Since its launch on code-sharing site GitHub in April 2014, GeoQ has been deployed for relief management efforts in more than 35 natural disasters, including tornadoes in Oklahoma, earthquakes in Nepal and Japan, typhoons in the Philippines, and the Ebola outbreak in West Africa.

Traditional damage evaluations can take up to 72 hours—during which relief agencies operate mostly “blind” on the ground. But GeoQ can provide a thorough damage assessment within 24 hours of an event, according to Ray Bauer, NGA‘s innovation lead and GeoQ project manager.

In the first ever applied use of GeoQ—a 2013 tornado in Moore, Okla.—“We were able to have 90 percent of the damage assessment done before we could get imagery from traditional sources,” Bauer said, referring to the period just after a disaster when relief agencies rush to compile data before deploying response teams.

Local Power

As data pops up online—such as geo-tagged photos on Instagram or helicopter footage from live news broadcasts—GeoQ’s crowdsourced workflow allows users to quickly receive and filter information to annotate at-risk areas. Emergency volunteers working online from relief agencies around the world are assigned manageable cells of land in the affected region and pore over the data, placing markers for things such as roadblocks and flood perimeters. 

Responding agencies can pull up the crowdsourced analysis on their computers or mobile devices, and can share information directly with other agencies. That shared accessibility is one of GeoQ’s primary benefits.

“In working with [federal, state, and local partners], we realized the inefficiencies of everyone doing their work a little bit differently,” Bauer said. “If you looked at the houses after Hurricane Sandy, they got marked with three or four Xs. Different organizations would come through and put a red X on the door … to show that they’ve already accounted for this property.”

With GeoQ, NGA hopes to standardize responder workflows and reduce that kind of overlap and resource waste to establish a more collaborative model of disaster relief.

Because of their access to tools and bandwidth for damage analysis, federal governments typically lead major disaster response efforts as requested by state and local authorities. GeoQ’s open-source approach helps give similar bandwidth to local responders so time isn’t lost communicating up the chain of command. Another benefit is geospatial intelligence (GEOINT) data held locally is often far more detailed and up-to-date than federal data.

“All disasters are local,” Bauer said, meaning that because disasters are primarily community-based in their impact, relief efforts should begin at the local level rather than the current model for disaster relief that puts most of the responsibility on federal agencies.

Bauer wants to flip the script with GeoQ to give more power to local entities such as fire departments and volunteer organizations, which are in a better position to provide immediate help but often lack sophisticated analytic technology.

“We’re giving them the fishing pole and teaching them how to fish,” Bauer said.

Members of Penn State’s Applied Research Lab (ARL) pose with National Geospatial-Intelligence Agency Director Robert Cardillo in the ARL booth at USGIF’s GEOINT 2017 Symposium. (Photo credit: PSU ARL)

NGA’s desire to share this local-first concept with the rest of the Intelligence Community and beyond is what led it to release GeoQ code on GitHub for free download and unrestricted use.

This means a user not affiliated with NGA could identify inefficiencies with the platform, alter GeoQ’s code, and upload the new, updated version on GitHub. If NGA approved the solution, it could be added to the source code. NGA hopes this low barrier to entry will encourage non-government organizations and private companies to participate.

“We’ve had several companies who have pulled the software down and have taken some of the ideas from GeoQ and started to implement it in their own software,” Bauer said. “That’s awesome. It’s about being open, transparent, and sharing ideas.”

Such a high level of transparency has led to significant leaps for GeoQ in the past three years.

Building Partnerships

GeoHuntsville, a nonprofit initiative in Alabama that unites organizations to improve disaster management, led an effort beginning in 2014 to integrate GeoQ with the operations of nearly every response agency within the municipality. This includes law enforcement, fire and rescue, medical, dispatch, civil air patrol, and more.

According to GeoHuntsville CTO Chris Johnson, “[GeoHuntsville] working groups were seeking a technology platform that would both visualize spatial data and capture tactical activities going on during an event.”

The organization wanted every Huntsville responder sent into a damage-prone area to be able to answer four questions: ‘Who am I?; Where am I?; How am I; and How can I report my activity back to the rest of the responding community?’

“We started using GeoQ to address the four questions, and also to help us break down workload, which it turns out GeoQ does very well,” Johnson said.

Now, GeoHuntsville utilizes its “Responders Working Group”—a collective of public safety specialists—to address prospective real-world challenges using GeoQ. GeoHuntsville’s technical unit, the “Geospatial Intelligence Working Group,” develops pilot programs and functional experiments based on those challenges to stress-test emerging tools and capabilities within GeoQ. NGA analysts as well as Federal Emergency Management Agency teams have participated directly in a number of these GeoHuntsville pilots.

“Through this working collaboration, we’ve been able to add a lot of features to GeoQ. And the wonderful thing about that is it doesn’t just benefit us in Huntsville,” Johnson said. “We are sharing [these capabilities] with everyone through GitHub.”

In August 2016, GeoHuntsville teamed with the National Oceanic and Atmospheric Administration and the National Weather Service to explore the use of unmanned aircraft systems as a platform to deliver live imagery to first responders on the ground. That intake of real-time surveillance paired with the ability to track the unmanned vehicle was new to GeoQ.

In the same exercise, GeoHuntsville developed a YouTube filter within GeoQ. Now, an operator can pull up an effected area on his or her screen and query YouTube for a specific keyword, timestamp, or location to pull real-time video data as soon as civilians post it online. Such data could be instrumental in determining where to direct resources and avoiding repeat coverage.

Pennsylvania State University has also contributed to GeoQ’s field testing and open-source development.

John Mills, a technologist with Penn State’s Applied Research Laboratory (PSU ARL), worked alongside Bauer on NGA’s “Map of the World,” and took a lead in enhancing GeoQ’s automation and data analytics when it first launched.

Students in Penn State’s Red Cell Analytics Lab work with high-tech equipment to simulate threats and analyze information. (Photo credit: PSU ARL)

“The problem we realized was a lot of people didn’t have this GIS or remote sensing background,” Mills said. “They wanted something that’s easy and intuitive to use, and that’s where GeoQ comes into play.”

PSU ARL joined forces with the PSU College of Information Sciences and Technology’s Red Cell Analytics Lab to focus on predictive analytics and implementation of open-source software into local, state, and federal GIS workflows. PSU students test GeoQ in the field, with student-run analytics teams evaluating and managing security threats at events such as Penn State football games at Beaver Stadium and THON, the world’s largest student-run philanthropic event.

According to Mills, the Red Cell teams have focused primarily on two initiatives: exploiting social media to access data, and supplementing GeoQ with other open-source projects such as NGA’s Mobile Awareness GEOINT Environment (MAGE) app. MAGE allows users to create geo-tagged data reports containing observable photo, video, or audio records, and to share those reports instantly with other team members.

“I call it the Red Cell Army,” Mills said. “They were able to go out and use MAGE to do event observable collects, and then in real time, GeoQ was in the emergency operations center in Beaver Stadium and you could see all these [MAGE] data sets popping up. That allowed emergency response folks to better do force deployment.”

Additionally, Mills continued, PSU ARL supervisors and Red Cell Analytics Lab members meet with government stakeholders—including NGA—to observe workflows and brainstorm ways the process could be automated to improve GeoQ’s efficiency and efficacy.

Though the application’s development has been primarily focused on disaster relief, GeoQ’s collaborative model has broader possibilities. The tool is designed to be applied internationally and in other industries.

People on six continents have downloaded or shown interest in GeoQ on GitHub. For example, an insurance company reached out to NGA about using GeoQ for after-damage reports to show where agents made adjustments.

Archaeologists have shown interest as well, according to Bauer. GeoQ currently divides land into single kilometer cells, but perhaps, he said, the program could be used to divide land into centimeter cells to support the examination and analysis of historic excavation sites.

The Next Level

For the next generation of GeoQ, NGA is exploring gamification to incentivize more people in the GEOINT Community to use the program. For now, GeoQ still requires an entry-level background in damage analysis and data management to be used productively.

To encourage engagement, NGA released in late 2014 a gamification code within the program that rewards volunteer analysts with badges and points based on feature creation within GeoQ. For example, a contributor might gain five points for marking five damaged houses within their assigned cell—once they acquire 10 points, they’d earn a badge. Accumulation of badges leads to higher clearance to assist in further, more intense disaster relief.

Badges and other user awards can be exported into a folder called the “Open Badges Backpack,” where contributors can show off their expertise.

Bauer joked about his children’s enthusiasm for virtual games. “We can see how powerful this gamification is—now imagine if we can start to use it for good,” he said. 

According to Bauer, tests of this gamification technique during real-world events have engaged analysts working side-by-side in friendly competition to earn more points and badges.

Bauer said perhaps by incorporating GeoQ into emergency response training programs for the public “[NGA] could start to develop a community in the future where we have civilians participate in first response.”

Through its open source code, GeoQ and similar applications provide first responders and volunteers with unprecedented speed and ease of use in data sharing. The advent of open-source tools will help keep first responders informed and unified in their assessments of danger and damage, enabling superior aid and ultimately saving more lives.

Featured image: GeoQ allows anyone with a web browser and an understanding of geospatial tools like Google Earth and ESRI ARC products to support a project. Contributors focus on information within the image as well as outside the frame to rapidly assess impacts and changes of disasters over large geographical areas to produce detailed features from traditional and non-traditional data sources quickly. (Credit: NGA)

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Quantifying GEOINT Fri, 20 Oct 2017 16:42:49 +0000 Measuring the societal and economic effects of geospatial services

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Geospatial professionals regularly see the effects of their work on a global scale, such as when up-to-date maps and location data help save lives during disaster response or when elements of biodiversity in the world’s oceans and forests are preserved. But non-GEOINT-based consumers may not realize the extent to which geospatial information and services affect their day-to-day activities.

Some of the world’s largest corporations—Google, Apple, Microsoft, Facebook, and more—have invested heavily in the future of geospatial technology and information sharing. The developed world has come to rely on such services, including Google Maps and Earth, Yelp, Uber, and Zillow to procure information.

A new study commissioned by Google and conducted by AlphaBeta set out to quantify the ways in which digital mapping saves time and money for both businesses and consumers alike. The 92-page document outlines consumer, business, and societal and environmental benefits. 

According to that report: digital maps supported more than $1 trillion in annual sales for businesses in 2016; directly created 4 million jobs (and 8 million indirectly); cut travel times by 12 percent at a value of $264 billion; and can reduce vehicular carbon dioxide emissions by 1,686 million metric tons. Additionally, geo-services have decreased emergency response times by 20 percent and saved global consumers 21 billion hours per year as a result of faster, better informed shopping decisions.

As the mapping industry continues to grow and more detailed information sharing capabilities—such as retail inventory mapping, indoor wayfinding, and real-time mapping for autonomous vehicles) are explored—those numbers will surely increase.

Photo Credit: The Next Web

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Mapping Autumn Fri, 13 Oct 2017 14:40:11 +0000 Visualizing fall foliage and festivities

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Autumn’s vibrant colors have begun to show, replacing summer greens with warm gold and scarlet. Smoky Mountains National Park published its 2017 Fall Foliage Map visualizing the progress of the annual changing of the leaves from late August to mid-November. Travelers chasing the brightest foliage should consider the Rocky Mountains, the lower Great Lakes, and New England, all of which are at or rapidly approaching “peak foliage.” South Florida and south Texas will peak the latest in early November.

With Halloween just two weeks away, the most industrious trick-or-treaters will already be planning their candy-maximizing strategies. Nextdoor’s Treat Map app offers children a head start on conquering their neighborhoods. The app prompts users to mark their homes with candy corn or a haunted house, indicating whether visitors can expect something sweet or scary upon arrival. Parents can also use the app to track the location of their trick-or-treaters as they bounce from house to house.

Halloween isn’t the month’s only holiday; celebrate Germany’s Oktoberfest tradition with National Geographic’s new “Atlas of Beer: A Globetrotting Journey Through the World of Beer.” Written by Mark Patterson and Nancy Hoalst-Pullen, the book explores international craft brewing through 100 detailed maps, 300 photos, tasting notes, trivia, and travel tips. Ale aficionados can learn about regional drinking culture in 45 countries and on six continents, breweries and festivals, and the sudsy future of beer.

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