The media is buzzing about the Great American Solar Eclipse that takes place Monday, Aug. 21.
It’s a historic event that last occurred 99 years ago. To be clear, 99 years ago is when the last total solar eclipse traversed the entire continental United States (lower 48 states).
To put that timeline in perspective, only one of the following inventions existed 99 years ago: FM radio, electric hair dryer, electric washing machine, frozen food, folding wheelchair and “talky” movies. Read further for the answer.
The last total eclipse that traversed part of the United States was 38 years ago, but in 1979 the total eclipse was only visible in five U.S. states (Washington, Oregon, Idaho, Montana, North Dakota). Have a look at the following map of the 1979 total eclipse path through the United States.
Figure 1- 1979 total eclipse path through the US. Source: NASA
It’s painful to think that in February 1979, when this eclipse occurred, I was a junior in high school in Oregon, living right in the path of the umbra (the moon’s shadow). I don’t recall the 1979 solar eclipse, but that doesn’t surprise me given the mind of a 16-year-old, at least mine.
Or, it could be the fact that was about 8:15 a.m. in February. Februaries in Oregon can be depressing due to the lack of sunlight. Anyway, it’s painful because today there are 37-year-old adults who were born after I graduated from high school. Time has flown by.
One of the points I was going to make in this article is how much GIS technology has improved since the last total solar eclipse in 1979, but that was 38 years ago. Given Moore’s Law, it should have improved exponentially in the past 38 years, and it has.
One way the evolution of GIS is displayed are the maps of the Great American Solar Eclipse of 2017. Let’s start with this basic one illustrating the path of the moon’s shadow as it traverses the United States:
My office is in Lake Oswego, and my house is just east of Lake Oswego, as illustrated here:
Figure 3- Solar Eclipse 2017 Oregon path. Source: eclipse2017.org
As you can see in the above map, my house and office are really close to the 100 percent eclipse path. In fact, using the following interactive map, I determined that from my house the sun will be 99.77 percent eclipsed.
Figure 4- Interactive 2017 Eclipse Map. Source: NASA
Now, for some cool animations. Back in 1979 (even 2000), animations were tough to produce. With today’s computing power and software, it’s quite straight-forward and quick to produce high-quality animations. The following is a screenshot from a 48-second animation from NASA’s YouTube channel showing the path of the total eclipse.
Figure 5- 2017 Solar Eclipse animation. Source: NASA
As GISers, you know that software is the engine. Engines need fuel to run. With GIS, fuel is data. For this next animation, two key pieces of data enable a new level of accuracy in plotting the umbra.
The first is the topography (surface map) of the moon. It’s not as round as it appears from Earth. Its surface has jagged edges from varied terrain just like the Earth.
The second is the vantage point on the Earth. In producing the following animation, NASA used SRTM elevation data collected from the Space Shuttle Endeavor mission in 2000. In 2014, the U.S. government released high-resolution SRTM data (30-meter) to the public. As a result, the following animation incorporates high-resolution data with unprecedented accuracy.
Figure 6 – 2017 Solar Eclipse animation using high-accuracy topo and SRTM data. Source: NASA
Where are you going to be on August 21st?
The fascinating part of this event is that no matter where you are located in the continental United States, you’re going to experience the effect of the solar eclipse.
As I mentioned above, at my house and office, I’ll experience about 99.77 percent eclipse. If I drive 15 miles south, I can experience 100 percent eclipse. The challenge is going to be traffic. It is expected that a few hundred thousand tourists will visit Oregon for this experience.
Traffic is already heating up. Gas stations may run out of fuel. Grocery stores may run low on food. I have no idea what to expect for traffic if I decide to make the 15-mile drive. I assume country roads as well as I-5, Oregon’s major interstate road, will be jammed and everyone will be driving at a snail’s pace and when the actual event is in progress, stop on the side of the road.
If I was a betting man, I’d say I’ll make the trek with a tank full of fuel and a sack lunch (~10:15am is go-time in Western Oregon). I’ll take one piece of equipment to document the event, my drone. If I plan it right, I should be able to grab some incredible images, not necessarily of the solar eclipse itself, but of the crowds of people mesmerized by the event. Follow my Twitter for updates.
Lastly, it was the electric washing machine. That’s the only invention listed in the opening paragraph that existed in 1918, when the last event like this occurred. The next one won’t be until 2045. I think I’ll make the 15-mile drive on Monday.
I just returned from the 38th Annual Esri International User Conference (Esri UC), which is the largest gathering of GIS (geographic information systems) professionals in the U.S. No GIS event in the U.S. is close to its scale.
Every year for the past 38 years (I presume, as I’ve only attended the last 11), Esri President Jack Dangermond begins by spending time during the kick-off plenary session painting his GIS vision. I appreciate that he doesn’t just dive into Esri-product-specific information. Granted, I know he’s setting the stage for that, but why wouldn’t he? He has a vision, and the products Esri develops will naturally follow that vision. Every year during his plenary presentation, I look for striking statements he makes. This year, a statement that struck me was:
“GIS users come from nearly every field of human endeavor.”
Remember this slide from the Esri UC Plenary in 2015?
The concept was that historically, geospatial technology has been a technology for scientists, but as geospatial awareness builds with business consumers and then mainstream consumers, the users of geospatial technology will count in the millions and, eventually, billions of users. One could argue that location-based services (LBS) have already reached more than one billion as consumers use geospatial technology in their mobile phones for navigating.
Without geospatial technology, the mobile phone would just display latitude/longitude, offering no situational awareness. That’s not what the above slide is referring to. Geospatial awareness for the business consumer (and mainstream consumer) is becoming more about analytics. A communication tool, a decision-making tool. … not only for the scientist, but for a much wider audience.
Of course, some will say I’m just “drinking the Esri Kool-Aid.” I would agree, except for one point: It’s actually happening. Think about it.
Clearly, geospatial technology has reached thousands of users. (Reference the above slide.) Also, it’s clear that geospatial technology has already reached hundreds of thousands of users. We know this from market research, and even Esri has stated in the past it has about 350,000 customers of its enterprise, desktop and mobile products.
How about millions of users? Check out the following slide Mr. Dangermond presented at this year’s plenary session…
…4.4 million!
That’s more people that live in the State of Oregon (where I live). That’s more than one percent of the entire U.S. population. That’s the number of ArcGIS Online users.
If you’re still not convinced about the direction of the trend, then consider the number to the right of 4.4 million on the slide above: “+30%.” That means a 30 percent increase in ArcGIS Online users (presumably from this time last year). If you look closely at the slide, you’ll see that 30 percent is the lowest number. Map tiles served increased 95 percent to 3 billion. Open data downloads were more than 40 million, an increase of 200 percent.
Esri is a fascinating business case. With any other business model, it would be very difficult to accomplish what Esri has. Three points stand out to me:
Esri has remained a privately held company. In other words, they didn’t “go public” and risk polluting its culture. Also, being a privately held company held means Esri can make major strategic decisions (such as shifting to web GIS) very quickly without having to worry about Wall Street or the next quarter’s financial report. This is very rare, and makes it very difficult for other companies to compete with Esri. Esri says it spends 28 percent of its revenue on R&D (research and development). In comparison, Microsoft spends 13 percent.
The key management team has stayed intact. Senior management turnover is a killer in the technology world. Every time a key strategic manager changes, a company, or portion of it, is paralyzed until the next senior manager gears up. Six to 12 months can be lost during this transition. That’s an eternity in tech.
Focus. This is a function of leadership and a stable management team. Esri isn’t perfect, but they’ve done a solid job for being a billion-dollar organization.
Ok, enough of my armchair quarterbacking. Following are some quick observations.
Mobile GIS is king
The Collector and Survey123 user base is expanding, fueled by the rapid adoption of iOS and Android devices as field data-collection tools. Add to that the growth of high-accuracy GNSS receivers for the GIS professional.
This is a perfect storm of technology convergence that’s resulting in a paradigm shift in high-accuracy GIS data collection. In other words, there’s a ton of demand for iOS/Android mobile devices running hardware-agnostic data collection software (such as Collector or Survey123) connected to a high-accuracy Bluetooth GNSS receiver.
UAVs
The UAV technical sessions were jammed with people. If you’ve kept up with my GSS Monthly newsletter the past couple of years, you can see why. You can use an inexpensive UAV (~$1,500) to generate centimeter-level orthophotos, 3D models, volume calculations and elevation contours.
UAVs are another tool in the box, and one that I think most GIS users will eventually have access to. UAVs will continue to get cheaper and better. The challenge will continue to be how to consume UAV data efficiently into your GIS workflow.
Structure from motion
I see this technique being implemented with many technologies like UAVs and other devices. If you haven’t looked at the GeoSLAM device, the Zeb Revo, it looks incredible. With it, the GeoSLAM team scanned the San Diego Convention Center in 2 hours at 1.5-centimeter resolution.
The handheld Zeb Revo by GeoSLAM.Using the Zeb Revo, the GeoSLAM team scanned the San Diego Convention Center to 1.5-centimeter resolution in two hours.
The user simply walks around with it as it scans an area. No tripods, no setups. Just walk. It’s expensive, but so were GPS, UAVs and 3D scanners when they first entered the market. The beauty of the GeoSLAM product is its simplicity. Check out this three-minute YouTube video:
BYOD GNSS receivers
The transformation is here. Trimble is finally on board with the Catalyst, in a big way. No more proprietary GNSS handhelds. You pick the device you want to use (an Android smartphone or tablet) and the software you want to use, then select the BYOD GNSS receiver (submeter, decimeter, centimeter) you want to use. This is the way it is supposed to be. If you think about it, it was backwards for so many years!
Oh, and I forgot to mention. At nearly 18,000 attendees (that’s the high number I heard), this was the largest Esri UC in history. As someone who has attended the past 11 Esri UCs, this was the best one yet because I could feel the technology (hardware and software) really starting to come together to form practical solutions that can be deployed in a large scale.
Thanks, and see you next time. Follow me on Twitter.
It’s been a few months since I’ve published a GSS Monthly newsletter column. What a busy few months it has been. It’s been all about UAVs, high-precision GNSS projects and GIS, with some conferences and workshops sprinkled in between. High-accuracy GNSS technology and UAV technology are hot trends— red hot.
UAVs: Prosumer and mapping on a slope
Obviously, consumer UAVs have exploded in the mainstream consumer electronics market during the past five years. Since the FAA began requiring UAVs to be registered in late 2015, far more UAVs have been registered (~700,000 to date) with the FAA than manned aircraft (~320,000).
In fact, the number of registered UAVs aircraft eclipsed registered manned aircraft more than a year ago! The FAA reported that at any one point during the day, there are ~7,000 manned aircraft flying in the U.S. airspace. That begs the question, how many UAVs are flying above our heads at any one point in time? No one can answer that question.
On the coattails of consumer UAVs in mainstream America is the use of UAVs in the USA’s commercial world. Since the FAA opened the floodgates in August 2016 to allow almost anyone to fly UAVs for business ($150 and answer 42 out of 60 questions correctly), lots and lots of companies are buying inexpensive “prosumer” UAVs and extracting tremendous value from them.
Prosumer electronics is equipment and software targeted at the consumer market but also good enough to be used for business. The UAV market is a perfect example of this. DJI, by far the biggest UAV manufacturer in the world at $1B+ in annual revenue, targets the mainstream consumer market and sells a huge number of low-, medium- and high-end UAVs to businesses. Think about it: You can buy a DJI Phantom 4 Pro at your local Apple Store and the next day be generating one-foot elevation contours on a project site!
Following is an example of a papermill I flew a few weeks ago. I flew it in less than one hour (50 acres), generated an orthophoto with 2.4-cm/pixel resolution and a digital elevation model (DEM) with 4.79-cm/pixel resolution.
Figure 1. 2.4-cm/pixel resolution orthophoto, 50 acres.Figure 2. DEM with 4.79-cm/pixel resolution of the same flight.Figure 3. Zoomed-in image of the same DEM.
The detailed data above, generated from a $1,500 UAV, is clearly outstanding. By the way, the purpose of the project was to determine the volume of the various stockpiles, which I’ve not computed yet. But if the volume calcs are close enough to the traditional terrestrial-based measuring methods, the UAV return on investment (ROI) argument will be hard to beat.
It takes ~14 hours each month to measure all the stockpiles on this site using traditional terrestrial measurement tools. Also, the measurements must be taken on the weekend when the site activity is minimal. It took less than one hour to fly the entire site, and I flew it twice (one time west-east direction at 80/80 overlap and one time north-south at 70/70 overlap) to make sure I had enough data. I mean, seriously, I drove 1.5 hours to the site. Why not spend another 20 minutes to fly it in a perpendicular direction?
To date, I’ve only flown relatively flat sites such as construction sites, agricultural fields, and industrial sites. That was until a couple of weeks ago. While I’ve become pretty comfortable at flying open and relatively flat sites over the past 18 months, I’ve not ventured into flying a site with a lot of elevation changes and tree canopy. I finally did that earlier this month, and it was both challenging and rewarding. There are a few problems on sites with major elevation changes and tall tree canopy:
A. Maintaining visual line of sight (VLOS) as required by the FAA.
B. Flying in such a manner that the image-processing software has good quality data to work with so you can generate the products you need.
The mission planning/control software plays a very important roll in this process. Well, it always does, but it really does in this case. Typically, the mission planning/control folks want you to fly at a consistent height above the ground so your overlap is consistent. This is very difficult to accomplish if you’re flying a site with a lot of elevation change. In that case, they typically tell you to launch from the highest (or nearly the highest) elevation point and fly at that elevation.
The problem this causes is that you could end up flying 500, 600 or 700 feet above ground level (AGL). For example, if you are flying a site with 500 feet of elevation change and you instruct the mission planning/control software to fly at 350 feet AGL, at some point in the project the UAV will be at 850 feet AGL. That can be a problem from both a regulatory standpoint (FAA allows UAV flights up to 400 feet AGL) and an image-processing standpoint.
Fortunately, the mission planning/control software I use just introduced a Terrain Awareness feature. It uses SRTM (Shuttle Radar Topography Mission) elevation data. Granted, it’s 30-meter pixel elevation data, so each elevation block is 30 meters x 30 meters, so I really wondered if the resolution was high enough. The site I was going to fly was only 60 acres in size and had 550 feet of elevation change. Note that the trees on the site had already been harvested, so the land was relatively clear. There’s about a 550-foot difference from the projected launch point (purple dot) to the northern and western end of the site. Following is the mission plan for the site I was planning to fly.
Figure 4. 60-acre site with ~550 feet of elevation change.
To give you an idea of the slope, the solid red lines in the following image are 100-foot elevation contour lines. The green triangle is the projected UAV launch point. This was a great launch point because I could see the entire site and maintain VLOS.
Figure 5. Site topo with projected UAV launch point.
I chose to fly the mission at 300 feet AGL. I figured it would be high enough if there was some “slop” in the SRTM elevation model. Still, I was concerned about the resolution of the SRTM data because at 300 feet AGL, my UAV would be flying below the launch elevation due to the extreme elevation slope on the site. Remember, the Terrain Awareness feature of the mission planning/control software is based on the SRTM elevation data, and not based on any sensors in the UAV itself — if the SRTM elevation data was incorrect, my UAV might crash into the ground.
Following is the SRTM elevation data along with the flight path data displayed in the mission planning/control software.
Figure 6. The projected UAV flight path based on the SRTM elevation data.
The moment of truth came when I launched the UAV from the start point (purple dot) and watched it rise to 300 feet AGL to start its mission. The first few swaths were uneventful. After that, it started to fly into the canyon, following the terrain as programmed, then rise up from the canyon during each pass. It was a thing of beauty to watch.
Unfortunately, about 70% of the way through the mission, it started raining, so we called it quits. However, we proved that at least on the four sites I flew that day, the SRTM data and Terrain Awareness feature were effective in collecting data in steep-slope environments. Following is the 2.69-cm/pixel orthophoto generated from the flight. Note the tracks where the logging rigs pulled the logs up the steep slope.
Figure 7. 2.69-cm/pixel resolution orthophoto.
Following is a zoomed-in view of the UAV launch site.
Figure 8. Zoomed-in view of the orthophoto.
Following is an image of the 5.37-cm/pixel DEM generated from the flight data. Notice the logging tracks.
Figure 9. 5.7-cm/pixel image of the DEM generated from the flight data.
Following is a zoomed in view of the 5.37-cm/pixel DEM image.
Figure 10. Zoomed-in 5.37-cm DEM image of UAV launch point.
The mission was successful in proving that SRTM elevation data was sufficient enough to fly a mission with a dynamic AGL. It handled the steep slopes by maintaining a sufficient AGL elevation as I hoped it would despite only having 30-meter x 30-meter block elevation resolution. The image processing software seemed to like the UAV data, as you can see from the results above. I didn’t have to spend any additional processing time over and above what I usually spend in order to generate these products.
I did experience a hiccup with the mission planning/control software running on my iPad Mini 2. It turns out that the Terrain Awareness feature in my mission planning/control software requires some extra CPU horsepower — the software overpowered my iPad Mini and crashed once during a mission. The UAV kept flying its intended course as instructed, but it stopped taking photos when the software crashed, so I brought it back to the launch point.
After visiting the software vendor’s website, it became clear to me that it’s probably time to upgrade my iPad Mini to the latest model to keep up with the new features being implemented in the software.
A Quick Note on High-Accuracy GNSS
In March, I attended the Hawaii GIS conference and decided to perform some benchmark testing on a survey mark using WAAS and a high-accuracy GNSS receiver.
My goal was two-fold.
See how WAAS is behaving in Hawaii. WAAS in Hawaii is an anomaly because it’s far away from the Continental U.S. (CONUS) where all the WAAS reference stations are located (there’s one in Honolulu, but that’s it). In other words, Hawaii is the most challenging place for WAAS accuracy in North America.
See how many GNSS satellites I could track and use in Hawaii.
Holy moly, was I surprised at how good it was. I’ve tested WAAS in Hawaii several times in the past many years. The last time I tested it was in 2013 and the GNSS receiver I used (GPS + GLONASS) achieved a steady 80-cm accuracy. That was pretty darned good for WAAS in Hawaii at that time.
I packed up some receivers and hiked about 4 miles to a survey mark I could find in Honolulu. I was a great survey mark for testing because it was on the sidewalk of a quiet residential street. Following is a photo of the survey mark.
Figure 11. PID DK4162 survey mark in Honolulu.
I set up on the survey mark and then looked at the satellites the receiver was tracking. I wanted to know how many GPS, GLONASS, Galileo and BeiDou satellites were being used. Following is a screen shot.
Figure 12. Total number of GNSS satellites being used – 23.
Twenty-three GNSS satellites being used! Are you kidding me? This is more than double the number of GPS satellites being used. This illustrates the power of four-constellation GNSS that is only going to continue to get better over the next several years.
What surprised me the most was the number of Galileo satellites being used, and this was before two Galileo satellites were declared healthy in late May.
My next test was to evaluate WAAS accuracy. Who cares how many satellites the receiver is using if the accuracy isn’t improved? I plumbed the receiver antenna on the survey mark and plotted ~7 minutes of data.
Figure 13. Accuracy plot compared to the DK4162 survey mark coordinates.
Yep, that’s about 30-cm accuracy over a 7-minute period. That’s better by a factor of two compared to the accuracy I saw in 2013. Sure, WAAS has improved somewhat, and maybe the ionosphere was particularly happy that day, but I have to believe that the additional GNSS satellites contributed the most to the improvement in accuracy. In the next few months, I’m going to be performing more tests with WAAS and RTK on my GNSS test course near my office. I’ll keep you posted on the results of those tests.
The Esri International User Conference – July 10-14
As usual, I’ll be attending the largest gathering of GIS professionals in the U.S. next month, the Esri International User Conference. 16,000 of our colleagues will descend upon San Diego to share, network and enjoy the spatialness that we have for one another.
If you’re interested, I’m giving a couple of presentations at the Esri UC:
Tuesday (July 11), 08:30 a.m., Room 28B (subject to change)
Paper Title: An Efficient, Accuracy Mobile GIS Workflow using RTK GNSS
Session Title: Mobile Data Collection
This is cool project I worked on with WaterOne, a large water utility, to design a real-time, high-accuracy GNSS workflow in the Esri environment. They are collecting data at the centimeter level for mapping their above-ground assets as well as new construction using tablet computers and RTK GNSS receivers.
Thursday (July 13), 8:30 a.m., Room 29C (subject to change)
Paper Title: UAV (drone) applications for water utilities
Session Title: Applied GIS: Three Unique Examples
This is some groundbreaking work I’ve done with American Water on using UAV technology for mapping and inspection. We did a lot of experimenting during the proof-of-concept phase to figure out what applications are practical and which aren’t.
I’ve attended a couple of Esri events these past couple of months. They are on the move. For a big software company (est. $1 billion in annual revenues), they are reasonably nimble. Of course, if you’ve worked with Esri software, no doubt you’ve been frustrated at times, but considering the size of the organization and the dynamic nature of GIS technology, it’s understandable.
Keeping up with the GIS technology makes me dizzy at times; I can only imagine what it’s like in the Esri roadmap planning meetings. Thank goodness Esri is a privately held company (versus a public company listed on a stock exchange). Being a privately held company gives Esri executives the flexibility to make and implement decisions quickly without worrying about quarterly (or even annual) financial performance.
Following are roadmap slides for some of the Esri mobile GIS products. Incidentally, did you know that mobile GIS apps are the hottest in the Esri software suite?
Collector for ArcGIS
The big news for Collector is that it’s being rewritten using a runtime library. The current Collector will be enhanced and supported (per the above image) for the foreseeable future. Once the new runtime version of Collector (CollectorX) has caught up to legacy Collector, the legacy Collector will begin the road to retirement. In the meantime, version 10.4.3 will likely be released sometime in April. It will implement GPS point averaging, renaming photos and Workforce integration.
Esri Collector for ArcGIS roadmap.
Expect another Collector release (10.4.4) with minor enhancements before the Esri User Conference (UC), which will take place July 10-14 in San Diego, California. According to Esri, Collector and mobile GIS in general (such as Survey123, Workforce, Navigator), are the hottest products in the Esri software suite, and iOS continues to be the dominant device that Collector is being deployed on.
ArcGIS for Windows Mobile
For those of you still working on the ArcGIS for Windows Mobile platform (not to be confused with Microsoft Windows Mobile on handheld devices), remember that at last year’s UC, Esri extended support (patches and hot fixes) for ArcGIS for Windows Mobile will be discontinued in July 2017 and enter mature support (request cases, phone/chat, online support services).
ArcGIS for Windows Mobile (Water Utility Mobile Mapp app)
If you’re still using ArcGIS for Windows Mobile, it’s time to start thinking about adopting a new mobile GIS platform. Two Esri options are Collector for ArcGIS (iOS, Android and Windows) and ArcPad (Windows and Windows Mobile). Before you start pummeling me about ArcPad, it’s a powerful and flexible mobile GIS. Unlike Collector, its user interface and functionality can be highly customized (see example screenshot below) and hit ArcGIS Online and ArcGIS Enterprise (ArcGIS Server) in real time, just like Collector.
Esri ArcPad – highly customized
Survey123 for ArcGIS
Quickly moving along, Survey123 for ArcGIS (iOS/Android/Windows) has become a powerful tool for collecting mobile GIS data, with one of its key features being data-collection forms using conditional logic (for instance, if/then) and the ability to create forms using Excel. Following is Survey123’s product roadmap.
Survey123 for ArcGIS roadmap.
Navigator for ArcGIS
Navigator for ArcGIS (iOS/Android) is an interesting product owing to the ability to integrate one’s roads into the app. Navigator includes standard Street Map data with turn-by-turn directions. What’s cool about adding proprietary roads is that one can navigate to rural, proprietary assets (like a pipeline valve) using turn-by-turn directions. The time savings to guide folks to assets in an unfamiliar geographic area can be compelling.
Navigator for ArcGIS.
Workforce for ArcGIS
Rounding out the mobile apps is Workforce for ArcGIS, which is a simple workforce management tool for assigning and coordinating field work crew tasks. Assign a task along with a location to a number of work crews and monitor the progress of the tasks as they are completed.
Workforce for ArcGIS Road Map
ArcGIS Online
All of the above apps are free to use with the exception of Navigator, which is $50 a year per device. In other words, when you buy an ArcGIS desktop license, you get access to these apps as well as ArcGIS Online.
ArcGIS Desktop & Pro
A quick word about ArcGIS Desktop: Esri is beginning to transition away from ArcGIS Desktop and towards ArcGIS Pro. Expect Esri to start encouraging you to move that direction, too. If you already have an ArcGIS Desktop license, you have access to ArcGIS Pro.
The focus of Esri development is going to be on the ArcGIS Pro platform, so you’ll need to head that direction eventually. ArcGIS Pro is Esri’s next-generation 3D, analysis, image processing and data management GIS platform.
Operations Dashboard for ArcGIS
Finally, I’d like to mention Operations Dashboard for ArcGIS. While it’s not a mobile GIS app, it certainly leverages data collected by mobile GIS. Another free app from Esri, Operations Dashboard allows one to create an executive dashboard showing a variety of charts, maps and gauges for monitoring project progress. It is available as a Windows client and a browser-based application (think iPad).
An executive doesn’t need to have a piece of Windows software installed to view an executive dashboard. Simply email a link to the custom dashboard and they can view it on their iPad while on the go. Dashboards can be customized with widgets and map tools using the ArcGIS API for Javascript.
Whether you love them or not, Esri is pushing the technology envelope. For a company like Esri that thoroughly dominates an industry, it would be easy for them to sit on their laurels, enjoy the fruits of their labor and be averse to taking risks. Hand it to the Esri team for continuing to stick their necks out.
Upcoming events
For those interested, I’m conducting a couple of one-day workshops in Oregon and Washington in May:
This workshop explores the growing trend of using smartphones and tablets (BYOD) for high-precision GNSS/GIS data collection.
I hope to see you at one, or both, workshops. We already have quite a roster registered, so sign up ASAP if you’re interested in attending.
Editor’s note: In the next month or two, look for an update and continuation of January’s column, “3D GNSS data and the GEOID.” It’s a complicated subject (see if you can spot the error in the article), but one that needs attention.
Reconciling data with disparate horizontal datums is a headache, sometimes a big headache, and sometimes a brutal migraine, especially with large enterprise databases. NAD83? WGS-84? ITRF08? The acronyms seem endless. Then there’s different variations of NAD83, WGS-84, ITRF08. Combine that with the myriad of datum conversion options in GIS software, and you’ve got a perfect opportunity to really mess up your 2D data.
The idea behind a horizontal reference frame (datum) is that anyone whose data is tied to that reference frame should be spatially “compatible.” Some pretty solid horizontal reference frames exist. In the United States, it’s NAD83/2011.
For vertical reference, it’s not so easy.
A common term used when referencing elevations is Mean Sea Level (MSL). If you’re interested in high-precision elevations, MSL is a dangerous term because it’s a regional reference and tends to be referred to as a global reference. The fact is that MSL is different depending on where you are located. MSL in Boston is different than in Miami, different than in Galveston, and different in Seattle so it’s not a suitable reference in a generic sense.
So, what does one use for a vertical reference in order to combine various datasets?
In the United States, the current vertical datum of the National Spatial Reference System is NAVD88. We can get into an entire discussion about how NAVD88 was created, but in an attempt to keep it simple, let’s talk about how to check if your elevation data is referenced to NAVD88. In the United States and other countries, there are survey marks on the ground that serve as points that you can reference.
In the United States, a database of survey marks can be accessed via the NGS Data Explorer website. To use it, simply type in the name of the city and click on Find Marks.
To choose an area within a city, you can use your mouse to pan to where you want, then click Find Marks again to refresh the survey marks. A legend on the right side gives you a definition of each symbol. Focus on the GPS-specific symbols because GPS is the easiest way for you to check the accuracy of your vertical data. For this example, I clicked on a symbol for a “GPS and Approx Height” survey mark. Following is what is displayed:
Above is the standard NGS Data Sheet format for all survey marks in the database. The PID (Permanent Identifier) code is a unique number for the survey mark. In this case, it is AI2002.
The Current Survey Control section on the data sheet provides the key information, including the latitude, longitude and height (elevation) information for the survey mark. Notice the NAVD88 height under the latitude/longitude.
The easiest way to check the accuracy of your vertical data is to use a high-precision GNSS receiver and collect a point on the survey mark. By high-precision, I’m referring to a standard RTK GNSS receiver capable of centimeter accuracy such as pictured below:
You could use a sub-foot or sub-meter GNSS receiver as long as you understand that your elevation accuracy error will be about twice that of your horizontal accuracy. For example, a sub-meter GNSS receiver elevation accuracy will be about 2 meters. For this discussion, let’s assume you’re using an RTK GNSS receiver.
Even though the vertical datum in the United States is NAVD88 and the NGS Data Sheet clearly shows that value, GNSS receivers don’t typically output NAVD88 elevation values. GNSS has its own vertical reference, a reference ellipsoid that approximates the shape of the Earth (GEOID). So, when your GNSS receiver reports elevations, it generally reports them as the Height Above Ellipsoid. This value, as you can see below, is quite different than the NAVD88 elevation….about 23 meters different.
The following graphic depicts the relationship between the ellipsoid, geoid and NAVD88 (surface height).
Remember, GNSS reports in Ellipsoidal Height (HAE). In order to convert this to NAVD88 height, you need to add the GEOID height. It starts to get a little complicated here because the model that defines the GEOID height is updated every few years.
Notice in the above graphic that the GEOID height refers to GEOID03. GEOID03 is the United States GEOID model released in 2003. The current GEOID model was released in 2012 (GEOID12B). The GEOID model changes because better data is being collected to further refine the GEOID model. The changes in the GEOID value from one GEOID model to the next (such as GEOID09 to GEOID12B) can be significant (many decimeters). Note that the ellipsoidal height will not change when the GEOID model is updated, only the GEOID height and the resulting NAVD88 height.
Since the GEOID models change somewhat frequently (every few years), most GIS data-collection software doesn’t incorporate the latest GEOID model, or any GEOID model at all. GPS receivers have a rough GEOID model built in so they can output a “surface elevation” that gets it close (within a few meters) to NAVD88 elevations as opposed to outputting ellipsoidal height, which is many meters in error.
Lastly, all GPS receivers output NMEA data strings, which are consumed by GIS data collection software. GPS receivers typically display this data (or output via Bluetooth or serial port) once per second. One of the key data strings, the GGA message, contains elevation data and looks like this:
If you would like to see a complete description of this NMEA data string, I wrote an article describing it here. Otherwise, I’d like to focus your attention on the elevation part of the above data string.
The ninth field of the string (495.144) is the elevation is this case. It is the surface elevation value, but not an accurate representation of NAVD88 elevation. The reason is due to the 11th field of the string (29.200), which is the GEOID value used in this example.
The GEOID value in this example is derived from a rough GEOID model built-into the GNSS receiver. It’s not accurate. Each receiver is different, but this value can be off by a few meters.
Interestingly enough, the GNSS receiver doesn’t output ellipsoidal height (HAE), which is the native elevation reference for GNSS receivers. To compute the ellipsoidal height, you need to subtract the inaccurate GEOID value (29.200) from the surface elevation the GNSS receiver is reporting (495.144), which in this case would be 495.144 – 29.200 = 465.944 meters. Clear as mud?
Now, let’s say you wanted to use an accurate GEOID value from the latest GEOID model and apply it to your data. You would have to perform the following calculation:
495.144 – 29.200 = 465.944 Ellipsoidal height. ###this is to remove the incorrect GEOID value.
Now, you would need to add the accurate GEOID value to the Ellipsoid height (let’s assume the accurate GEOID value is 31.45 meters).
465.944 + 31.45 = 497.394 meters (NAVD88).
Now, when 497.394 refers to NAVD88, this is assuming your GNSS receiver is accurate to a few centimeters in elevation. Of course, applying an accurate GEOID value to an elevation being output by a Garmin handheld doesn’t make much sense because the inaccuracy of the Garmin elevation is much greater than the rough GEOID model used by the Garmin.
Well, this concludes my stepping-off point for a discussion about elevations in what is sure to become a series of articles about the accuracy of GIS elevation data and how to check the elevation accuracy of your GIS data, as well as how to collect it.
Structure from motion (SfM) is a photogrammetric range imaging technique for estimating three-dimensional structures from two-dimensional image sequences that may be coupled with local motion signals, according to Wikipedia, which I think is reasonably accurate in this case.
Simply put, one can snap a series of photographs using the camera in your smartphone, unmanned aerial vehicle (UAV) or other photographic equipment and produce a 3D model using software that is built using the SfM technique.
To assist you in capturing the photos on your smartphone to generate a 3D model, Autodesk has a free mobile app called 123D Catch. Using the app, you can create a 3D model of nearly any object you can imagine. Following is a one-minute YouTube video from Autodesk that succinctly shows the process of capturing photos using an iPhone camera with Autodesk’s free 123D Catch app and how to generate a 3D model.
Today’s smartphone cameras offer incredible resolution. My Samsung Galaxy S7 has a 12-megapixel camera. The iPhone 7 offers the same resolution. Modern iPads have an 8-megapixel camera, which is fine for 3D modeling.
So, think about this for a minute. What value can you derive from shooting images from your smartphone? If you need to know the volume of a pile of material (e.g. construction), your smartphone running the 123D Catch app can do it. The requirements are straight-forward:
You need to be able to walk completely around the pile and shoot many overlapping photos, filling the camera frame with the pile. Every surface you want modeled should be visible from at least four photos from different angles.
Avoid shooting featureless photos (e.g. walls, water or snow surfaces). Or, if a background is featureless, add a feature to the surface like a small target (similar to photogrammetry ground control targets but much smaller).
Avoid shooting reflective surfaces.
Don’t shoot moving objects (e.g. vehicles).
Try shooting in well-lit areas.
Taking it a step further, the camera doesn’t have to be in your smartphone. You could use a camera mounted on a vehicle that could provide a different perspective. Something like a … drone! Yes, SfM-based software like Agisoft Photoscan allows drone pilots to exploit photographs shot from their aircraft.
In the past few years, I’ve written a lot about drones and my adventures in using them. Following are a series of images as a result of one of my UAV flights. A total of 500 photos were shot at 80 percent overlap from my drone flying at 200 feet AGL (above ground level). The photos were imported and run through Agisoft Photoscan.
The first screenshot (Figure 1) is a 2D view of the 3D model generated from processing 500 digital photos through SfM.
Figure 1
Figure 2 shows the camera location of each photo. Remember, the UAV was flying at a consistent altitude (200 feet AGL) and was taking photos with an 80 percent overlap.
Figure 2
Figure 3 is an oblique view of the 3D model. If I wanted to improve the quality of the 3D model (e.g. the sides of the building), I would have flown the drone again in a flight pattern perpendicular to the first pattern. Note the pile of material at the lower part of the screen and to the right of the pond.
Figure 3
The final screenshot, Figure 4, is a zoomed in view of the pile of material.
Figure 4
Since a 3D model has been created, clearly a DEM (digital elevation model) and DSM (digital surface model) can be generated, as well as associated 3D products like elevation contours and volume calculations.
Enough of the drone talk.
With your smartphone, you’ve got everything you need to create a 3D model of your children, your Christmas tree, your pet, your vehicle or other valued object. Give it a try. It won’t cost you anything but some of your time.
Start by downloading the Autodesk 123D Catch app. You might want to view this six-minute video describing how to plan a shoot for best results.
https://youtu.be/D7Torjkfec4
To process the photos and create a 3D model, install the Autodesk ReMake free version.
Once you’ve installed ReMake, take a look at this less than four-minute quick start for importing photos and processing them in ReMake.
Times have changed, and the technology landscape is much, much different today than it was as recently as ten years ago when GPS was the driving-force technology for geospatial users and geospatial equipment, and the exclusive concern of many companies in the industry. In that era, their challenges were to design the best performing receiver in terms of accuracy, size, weight, ruggedness and so on.
Now, GPS technology has been commoditized in mobile devices (the GNSS chip in your smartphone costs about $1.50), and high-precision GNSS is heading in that direction. It’s hard to make a living designing “GPS boxes.”
Sure, GPS is still a core technology offered in most hardware products that geospatial professionals use, but it’s not the centerpiece. It’s all about system solutions, of which software (and hardware besides GPS) is a major component.
As just one example of this overall industry trend, let’s look at how the message of system solutions was abundantly clear last week at the Trimble Dimensions User Conference in Las Vegas. This event reportedly drew 4,400 attendees from more than 80 countries.
More than 4.400 attended Trimble Dimensions at the Venetian Hotel.
Virtual/Augmented(AR/VR) Reality
The Trimble Dimensions general plenary discussion didn’t feature the latest GNSS technology. In fact, there was barely a mention of GNSS. Nonetheless, the cool factor was present, with the highlight being a live demonstration of virtually reality using Microsoft HoloLens goggles and Trimble SketchUp software.
Over the years I’ve written quite a bit about augmented and virtual reality. This technology has a bright future for locating hidden assets (think underground and inside wall infrastructure) and visualizing design ideas. For this technology to work, it’s not just about having a set of goggles. One needs software and an accurate geo-database.
During the plenary, architect Greg Lynn demonstrated the value of virtual reality technology by “displaying” a building concept on an empty table on the stage. Lynn and a colleague donned HoloLens goggles while a camera was set up with HoloLens goggles to display what they were “seeing” through the HoloLens.
AR/VR reality are a step closer to being a practical technology to deploy in the field. In a way, AR/VR technology seems to be taking the same path as tablet computers. Tablet computers existed way before the iPad was introduced. They were expensive, and history is littered with failed tablet computer ventures, just like Google Glass failed in the AR/VR world.
I remember paying ~$2,500 for a Fujitsu Stylistic tablet about 10 years ago for my work. Like the Stylistic, HoloLens isn’t cheap. It’s $3,000 for a development kit and $5,000 for the commercial version. It’s not priced for the average consumer, but the attraction is undeniable and due to the price tag; industrial markets will pick it up before the consumer market will.
It might take a Steve Jobs-like push to punch it through the finish line, but it’s just a matter of time before AR/VR technology is commonplace.
Solutions
Hardware isn’t sticky. Software is. Even better, hardware and software bundled tightly together is the sweet spot. Dimensions showed how, more and more, geospatial technique is geared around solutions, not boxes.
Trimble partner solutions area at Trimble Dimensions 2016.Trimble solutions area at Trimble Dimensions 2016.
One case in point: I took a 45-minute ride from the Venetian Hotel on the Vegas Strip to the outdoor demonstration site in the desert east of Las Vegas.
The demonstration site was a playground for heavy equipment utilizing Trimble hardware and software — from tractors to scrapers to bulldozers and paving machines. It’s difficult to imagine the scale of the outdoor demonstration site, so following are a few images.
Demonstration site facing south with the Las Vegas Strip to the southwest.
I caught a ride in a fully autonomous tractor that was outfitted with guidance technology (GNSS using RTX satellite correction service), collision avoidance sensor and display console. It repeatedly stayed within the track defined by the orange cones you see in the above image.
What good is autonomous guidance without collision avoidance? A sensor on the front of the tractor senses objects and either avoids them, slows down or stops. Trimble says they are working on perfecting the turns at the end of each line where traditionally a driver had to take control. This is a difficult task when the tractor is pulling an implement such as a planter or sprayer.
In the not-too-distant future, tractors will be completely hands-free from start to finish.
Wi-Fi radio.
Back inside the Venetian Hotel, I saw this little beast. No, it’s not a funky GNSS antenna. It’s an industrial Wi-Fi radio. Yes, Trimble owns some pretty cool outdoor Wi-Fi technology vis-à-vis Fidelity Comtech, a company that Trimble acquired in 2015.
I’ve set up outdoor Wi-Fi infrastructure before in relatively benign environments (think agriculture), but I didn’t use anything like this. This equipment is built to propagate outdoor, long-range Wi-Fi connectivity in nasty, noisy environments like shipping terminals and construction sites. It can reshape the antenna pattern on the fly in microseconds, and shape the beam width/range to cover a specific geographic area.
GNSS Gear
Even though I’ve been talking about how this isn’t a just a GPS or GNSS environment anymore, I can’t leave without investigating the latest GNSS gear.
Check this out.
Trimble Catalyst software GNSS receiver.
In the past, I’ve written about GNSS software receivers. They exist, but require some serious computing power. Well, some smartphones have powerful CPUs, such as the Samsung Galaxy 6 and 7. Trimble has developed a software GNSS receiver called the Trimble Catalyst that uses the CPU of a Samsung smartphone as the GNSS receiver…dual frequency. The antenna on the range pole is just an antenna, albeit an L1/L2 antenna. Using an RTK network, Trimble says it can deliver centimeter accuracy. Wow.
To be fair, it’s got some significant limitations such as it only uses GPS and Galileo, only runs on certain Android devices (it will likely never run on iOS devices), and eats up the smartphone battery. And although Trimble said it shares resources in a friendly manner, I must think that a rogue app or update might cause things to slow down. Although it won’t behave as snappy as RTK on an R10 and won’t recover as quickly from obstructions like trees, terrain and buildings, it most certainly could bring high-precision GNSS to a wide-array of previously non-RTK users.
Times have changed, and the technology landscape is much, much different today than it was as recently as ten years ago when GPS was the driving-force technology for geospatial users and geospatial equipment, and the exclusive concern of many companies in the industry. In that era, their challenges were to design the best performing receiver in terms of accuracy, size, weight, ruggedness and so on.
Now, GPS technology has been commoditized in mobile devices (the GNSS chip in your smartphone costs about $1.50), and high-precision GNSS is heading in that direction. It’s hard to make a living designing “GPS boxes.”
Sure, GPS is still a core technology offered in most hardware products that geospatial professionals use, but it’s not the centerpiece. It’s all about system solutions, of which software (and hardware besides GPS) is a major component.
As just one example of this overall industry trend, let’s look at how the message of system solutions was abundantly clear last week at the Trimble Dimensions User Conference in Las Vegas. This event reportedly drew 4,400 attendees from more than 80 countries.
More than 4.400 attended Trimble Dimensions at the Venetian Hotel.
Virtual/Augmented(AR/VR) Reality
The Trimble Dimensions general plenary discussion didn’t feature the latest GNSS technology. In fact, there was barely a mention of GNSS. Nonetheless, the cool factor was present, with the highlight being a live demonstration of virtually reality using Microsoft HoloLens goggles and Trimble SketchUp software.
Over the years I’ve written quite a bit about augmented and virtual reality. This technology has a bright future for locating hidden assets (think underground and inside wall infrastructure) and visualizing design ideas. For this technology to work, it’s not just about having a set of goggles. One needs software and an accurate geo-database.
During the plenary, architect Greg Lynn demonstrated the value of virtual reality technology by “displaying” a building concept on an empty table on the stage. Lynn and a colleague donned HoloLens goggles while a camera was set up with HoloLens goggles to display what they were “seeing” through the HoloLens.
AR/VR reality are a step closer to being a practical technology to deploy in the field. In a way, AR/VR technology seems to be taking the same path as tablet computers. Tablet computers existed way before the iPad was introduced. They were expensive, and history is littered with failed tablet computer ventures, just like Google Glass failed in the AR/VR world.
I remember paying ~$2,500 for a Fujitsu Stylistic tablet about 10 years ago for my work. Like the Stylistic, HoloLens isn’t cheap. It’s $3,000 for a development kit and $5,000 for the commercial version. It’s not priced for the average consumer, but the attraction is undeniable and due to the price tag; industrial markets will pick it up before the consumer market will.
It might take a Steve Jobs-like push to punch it through the finish line, but it’s just a matter of time before AR/VR technology is commonplace.
Solutions
Hardware isn’t sticky. Software is. Even better, hardware and software bundled tightly together is the sweet spot. Dimensions showed how, more and more, geospatial technique is geared around solutions, not boxes.
Trimble partner solutions area at Trimble Dimensions 2016.Trimble solutions area at Trimble Dimensions 2016.
One case in point: I took a 45-minute ride from the Venetian Hotel on the Vegas Strip to the outdoor demonstration site in the desert east of Las Vegas.
The demonstration site was a playground for heavy equipment utilizing Trimble hardware and software — from tractors to scrapers to bulldozers and paving machines. It’s difficult to imagine the scale of the outdoor demonstration site, so following are a few images.
Demonstration site facing south with the Las Vegas Strip to the southwest.
I caught a ride in a fully autonomous tractor that was outfitted with guidance technology (GNSS using RTX satellite correction service), collision avoidance sensor and display console. It repeatedly stayed within the track defined by the orange cones you see in the above image.
What good is autonomous guidance without collision avoidance? A sensor on the front of the tractor senses objects and either avoids them, slows down or stops. Trimble says they are working on perfecting the turns at the end of each line where traditionally a driver had to take control. This is a difficult task when the tractor is pulling an implement such as a planter or sprayer.
In the not-too-distant future, tractors will be completely hands-free from start to finish.
Wi-Fi radio.
Back inside the Venetian Hotel, I saw this little beast. No, it’s not a funky GNSS antenna. It’s an industrial Wi-Fi radio. Yes, Trimble owns some pretty cool outdoor Wi-Fi technology vis-à-vis Fidelity Comtech, a company that Trimble acquired in 2015.
I’ve set up outdoor Wi-Fi infrastructure before in relatively benign environments (think agriculture), but I didn’t use anything like this. This equipment is built to propagate outdoor, long-range Wi-Fi connectivity in nasty, noisy environments like shipping terminals and construction sites. It can reshape the antenna pattern on the fly in microseconds, and shape the beam width/range to cover a specific geographic area.
GNSS Gear
Even though I’ve been talking about how this isn’t a just a GPS or GNSS environment anymore, I can’t leave without investigating the latest GNSS gear.
Check this out.
Trimble Catalyst software GNSS receiver.
In the past, I’ve written about GNSS software receivers. They exist, but require some serious computing power. Well, some smartphones have powerful CPUs, such as the Samsung Galaxy 6 and 7. Trimble has developed a software GNSS receiver called the Trimble Catalyst that uses the CPU of a Samsung smartphone as the GNSS receiver…dual frequency. The antenna on the range pole is just an antenna, albeit an L1/L2 antenna. Using an RTK network, Trimble says it can deliver centimeter accuracy. Wow.
To be fair, it’s got some significant limitations such as it only uses GPS and Galileo, only runs on certain Android devices (it will likely never run on iOS devices), and eats up the smartphone battery. And although Trimble said it shares resources in a friendly manner, I must think that a rogue app or update might cause things to slow down. Although it won’t behave as snappy as RTK on an R10 and won’t recover as quickly from obstructions like trees, terrain and buildings, it most certainly could bring high-precision GNSS to a wide-array of previously non-RTK users.
I spent time this week at the Esri GeoConx conference in Phoenix, Arizona. The GeoConX conference is a gathering of ~800 GIS users from gas, electric and telecom utility companies.
I always enjoy listening to GIS professionals from utility companies because they are faced with the most interesting GIS and data management problems. High on the list is data integration. Not necessarily the integration of disparate GIS datasets (although that’s an ongoing challenge), but rather GIS data integration with other systems that manage work orders, financial systems and more.
I took a lot of pictures at GeoConX and I think they tell an interesting story about the issues GIS professionals at these utility companies are facing.
Eight hundred people from 44 U.S. states, and countries as far away as New Zealand, attended GeoConX.
Esri President Jack Dangermond re-emphasized the System of Record (authoritative data source), System of Engagement (collaboration/sharing), and System of Insight (analytics) concept that he introduced at the 2015 Esri International User Conference.
He also made a comment, which he has before, that Esri spends ~27 percent of Esri’s annual revenue on research and development. That’s about $230 million per year. To put in that perspective, in 2015 Apple Computer spent 4 percent of its revenue on R&D. Renown automobile innovator Tesla spent ~18 percent of its revenue on R&D. Toyota spent 4 percent.
Granted, those companies have significantly higher annual revenues than Esri, but you have to give Esri kudos for re-investing and keeping the company ownership closely held. If Esri was a public company, or had significant external shareholders expecting typical investment ROI (Return on Investment), shareholders would want a piece of that R&D budget in their pockets.
A devil’s advocate might say that a different corporate structure might pressure Esri to be more efficient with R&D spending, but I have a lot of respect for Esri’s chosen business model, which enables it to remain ably nimble.
Location-based services are “hip.” The 18- to 29-year-old demographic leads the pack in all usage categories. Getting “kick-back” from employees who are hesitant to trust or embrace GIS technologies? Just wait a few more years as the 18-29 demographic works its way through age groups like a rat in a snake’s belly.
This slide will be interesting to those of you whom have asked where GIS lies in the adoption curve. According to Esri, GIS technology adoption has passed through the “early adopter” stage and is building momentum with the “early majority.”
The BART (Bay Area Rapid Transit) presented its implementation of enterprise GIS. I’ve heard similar stories in the past, but perhaps their most interesting data was the statement that BART has derived $3.11 in value for every $1 invested in GIS technology.
A look at Esri’s software release schedule for the next year.
Tracking and traceability was one of the hot topics, especially in the natural gas industry. While the natural gas industry is driving the technology, once it’s developed there’s no doubt the concept and technology will seep into other industries. Better systems and data = better decisions and accountability.
NYSEG/Avangrid gets my vote for “quick and dirty” mobile GIS deployment of the year. Six months, 300 iPads, develop app, train staff, deploy tablets. No enterprise-level MDM (Mobile Device Management) system. Don’t accept that iOS 10.x update prompt!
Construction as-built data should be treated as a valuable asset, not a luxury that can be cut at the end of the project. As one who has created many construction as-built maps over the years, they are preaching to the choir. An accurate construction as-built housed in an accessible database is worth its weight in gold.
This slide shows “decreased GPS performance close to buildings and under trees.” Please read my column from last month.
Last but not least…
This slide is worth a thousand words. It succinctly illustrates the problem facing nearly all enterprise GIS that are loaded with legacy data.
This particular slide describes new attributes that are being added to Esri’s pipeline data model. The driver of this action is the fact that GNSS data being collected is likely more accurate than the legacy vector data. It doesn’t matter if it’s a pipeline, a tract boundary, a valve or any other infrastructure, the age-old question is “Why doesn’t my GPS data line up with my basemap?” The answer, nine times out of 10, is because the basemap is less accurate than the GNSS data. Therein lies the rub.
When this situation occurs, there are two choices:
“Move” the basemap data (I’m being overly simplistic) to match the more-accurate GNSS data.
“Move” the more-accurate GNSS data to match the less-accurate basemap data.
Common sense tells one to move the less-accurate basemap data to match the more-accurate GNSS data. However, moving basemap data can lead to all kinds of challenges. It’s the GIS house of cards. If you start moving the cards at the bottom of the structure, the foundation becomes weak and you’ll likely need to rebuild other parts of the basemap, which can be quite an undertaking.
To that point, coordinate fields (GPSX and GPSY, and soon-to-be GPSZ) are added as attributes to store the high-accuracy coordinates of the features. Then, believe it or not, the more-accurate GNSS data is moved to match the less-accurate basemap! It seems counterintuitive, but the logic is that sometime in the future as the basemap data evolves and accuracy improves, the high-accuracy coordinate values of the features are preserved as attributes and can be “brought out of storage” and placed into service at an appropriate time in the future.
Almost every enterprise GIS faces this problem. How are you handling it?
Thanks, and see you next month.
Follow me on Twitter at https://twitter.com/GPSGIS_Eric
Every year, some of the brightest minds and most influential people in the GNSS industry that guide the direction of global GNSS system deployments (GPS, GLONASS, Galileo and BeiDou) and design the most advanced GNSS receivers in the world, gather at the ION GNSS+ conference.
I almost always attend this conference, as it provides a look into what GNSS receiver researchers, designers and program managers are working on that will affect high-precision GNSS performance in the next few years and beyond. ION GNSS+ is a playground for someone like me, who’s knee-deep in high-precision GNSS.
The satellite constellations
GPS is what it is. It’s the most mature and reliable constellation of navigation satellites, period. All of the model IIFs have been launched. The U.S. Air Force launched the balance of them in 24-month flurry that ended in May 2016. The next-generation GPS III satellites aren’t going anywhere soon. It will be at least two years before the first GPS III is launched. Would sooner be better? Of course, but either way won’t have a major impact on high-precision GNSS performance since the constellation is capped at 31 satellites for the foreseeable future.
GLONASS is in the same boat as GPS. It’s not as reliable as GPS (remember this?), but it has been a valuable service for high-precision GNSS users for many years. GLONASS sats don’t necessarily improve GNSS receiver precision, but they certainly improve productivity by allowing high-precision GNSS users to work in impaired environments where GPS-only receivers aren’t nearly as effective. The GLONASS constellation is mature at 24 satellites (You can monitor it here.) and that’s not changing anytime soon. Much like the U.S. with regards to GPS, Russia is in replenishment mode with GLONASS. It is not a growing constellation.
The following is where the magic starts to happen with high-precision GNSS receivers:
Galileo (Europe) is ramping up: currently nine healthy satellites. From my office in Portland, Oregon, Galileo adds up to four additional satellites using a 10-degree elevation cutoff. Four more Galileo satellites are scheduled to launch in a couple of months (Nov. 17). All four are being sent into orbit on a single Ariane-5 rocket from a spaceport in French Guyana. The European GNSS Agency (GSA) reported it is planning similar launches of four in 2017 and 2018.
BDS or BeiDou (China) is also ramping up. Currently there are 17 healthy satellites, with most flying regional orbits in Asia, as opposed to global orbits. While China generally keeps its BDS plans out of public eye, but I’ve heard BDS officials state, on separate occasions, that a full constellation of 30 satellites providing global coverage will be deployed by 2020.
Following is a satellite visibility chart showing the number of GPS (green), GLONASS (red), Galileo (Blue) and BDS (yellow) that are visible from my office in Portland with a 10-degree elevation cutoff.
As you can see above, a four constellation configuration is starting to become interesting with Galileo and BDS contributing up to 7 additional satellites. In a clear sky environment, this may not be substantial; however, in an impaired environment (e.g. around trees, buildings, terrain), a few additional satellites can make the difference between staying productive or work stoppage. Even further, imagine four years from now when Galileo and BDS constellations are fully operational. In that scenario, there will be upwards of 35 satellites in view. Even before then, like two months from now when four more Galileo satellites are launched, each new satellite in orbit will add a marginal increase in GNSS receiver performance if your receiver is designed to track and use Galileo satellites.
Is more better? Almost certainly. If nothing else, it gives the GNSS receiver more signals to choose from and a lot of redundancy. This is especially true with RTK (real-time centimeter positioning), which is a satellite-hungry technology. RTK is easy in the wide open sky. It’s not so easy in residential areas with lots of trees, areas of rugged terrain and urban areas. More satellites doesn’t mean you’ll enjoy ubiquitous RTK precision in all environments, but it will translate into greater productivity, at the centimeter level, than what is possible today. Will productivity increase 10 percent or 50 percent — or more? That’s the only question.
Another high-precision GNSS technology that was discussed at length, and during several sessions, was Precise Point Positioning (PPP). There were quite a few technical papers and discussion panels on this technology. Real-time PPP services are commercial satellite subscription services like StarFire (Deere), RTX (Trimble), Atlas (Hemisphere) and Terrastar (Veripos). These services rely on a very sparse network of GNSS base stations to compute precise clock/orbit values then deliver them to the user via satellite or internet. The upside is that a dense network of GNSS base stations is not needed like with RTK; however, the downside is that high-precision PPP requires quite a bit of time to convergence to the desired precision (e.g. 10 centimeters). This can be as little as five minutes or as long as 30 minutes or more. This is acceptable in industries like agriculture where there is a clear view of the sky and the farmer only needs to wait for convergence one time in the morning. But, in environments where there are trees, buildings and rugged terrain, PPP convergence gets interrupted many times per day and to a point where it kills productivity. More time is spent waiting for convergence than working.
RTK fares much better in this environment. Yes, it will lose initialization in those environments, but it only takes a few seconds to re-initialize. From a productivity standpoint, I don’t get it. Real-time PPP is a step backwards from RTK. But, who says it has to be one or the other?
RTK’s greatest weakness is the requirement for consistent data connection to an RTK base or network of RTK base stations. By consistent, I mean that every second counts, without a hiccup. Wireless connectivity (like a cell phone network) is the most common RTK communication technology. Everyone with a cell phone knows that cell coverage can be spotty in certain geographic areas — even densely-populated ones. This is the Achilles heel of RTK, and where real-time PPP, delivered by satellite, can help. Some of the commercial services like RTX, Starfire and Atlas offer a type of hybrid RTK/PPP solution to optimize productivity. When RTK quits working, real-time PPP takes over until RTK returns. Organizations love tools that increase productivity, and this is a powerful combination.
Lastly, I can’t leave you without mentioning a presentation from Broadcom that I attended. Broadcom makes the GNSS chipsets used by Apple and Samsung in their smartphones. It’s crazy to think that Apple and Samsung pay under US$1 for each powerful GNSS chip used in smartphones. The challenge for Broadcom is that GNSS chips have become a commodity, so it’s a race to the bottom when competition starts to separate based largely on price.
To that end, Broadcom is testing a dual frequency L1-E1/L5-E5 GNSS chipset. They aren’t talking RTK … yet. But, they did present some preliminary results showing an increase in accuracy (by four times) over the single frequency GNSS chips being used in smartphones today. Take a look at the following slide.
u-blox, a company based in Switzerland, has developed a similar product, and presented it in a technical session at ION: a consumer-grade chip that does L1 RTK. They are initially looking at UAV use, but this could have many other applications as well. For details and performance data, see the cover story of the October issue of GPS World magazine, out soon.
It’s pretty clear that it’s only a matter of time before high-precision GNSS technology makes it way into mainstream smartphones. It may be another ten years or less, but it will happen. Why?
The answer is the same reason that people dream of ascending Mt. Everest.
A four-satellite dispenser for Galileo’s Ariane 5 is shown during shaker testing at Airbus Defence and Space near Bordeaux, France. The dispenser has had four Galileo engineering models attached to it for test purposes. (Photo: ESA)
In Geospatial Solutions’ sister publication, GPS World magazine, I’ve written quite a bit about how high-precision GNSS is going to significantly improve over the next few years.
Most GNSS users have receivers capable of using GPS (31 satellites) and Glonass (about 24 satellites). That generally equates to between 13 and 20 satellites in view with a clear sky and average terrain. However, add in variable terrain, some trees and perhaps a nearby building or two, and it can be a challenge to find enough solid satellites to track to obtain a high-precision GNSS position (less than a meter).
As the demand for high-precision GNSS positioning continues to grow, users are going to want to work in increasingly more difficult environments where high-precision GNSS struggles. More satellites will help, but they won’t come from GPS, nor GLONASS.
The GPS constellation is currently full, and is not going to grow any larger than 31 satellites (due to limitation in current GPS ground control software) in the foreseeable future. Even if GPS could fly more satellites, the orbit design accommodates only 27 satellites. GLONASS appears happy at 24 satellites and is not expanding anytime soon.
The answer lies in Europe, with China following.
After two decades of start, stop, restart, retool, regroup and start again, Europe’s Galileo constellation is real — very real. It’s all fun and games until Galileo starts launching four satellites at a time, which it is scheduled to start doing in a couple of months. Those four new satellites, added to the 12 in orbit (plus two in odd orbits), should be enough for Galileo to begin initial operation in Q4 of this year. Then, each new launch of four additional Galileo satellites will only improve the reliability and robustness of high-precision positioning. That’s a big deal for high-precision GNSS users.
Get ready for another jump in performance in high-precision GNSS positioning.
Do you remember the value that GLONASS added to GPS-only receivers 10-plus years ago? It was a premium feature on high-precision GNSS receivers in those days. Now, GLONASS is a standard feature on your smartphone.
Not very long from now, we’ll be making similar comments about Galileo. Satellite positioning in general, and high-precision GNSS positioning specifically, are satellite-hungry. As high-precision GNSS technology continues to embed itself deeper into a wide variety of industries, users will expect the technology to work. Some of those expectations, maybe many expectations, will be unreasonable. In dense urban environments? Under heavy tree canopy? In rugged terrain?
Unreasonable expectations are O.K. — that’s what pushes GNSS product managers and GNSS engineers to think outside of the box. More satellites will help meet some of the unreasonable user expectations.
What’s even better is that China’s global BeiDou system isn’t far behind Galileo. China’s regional BeiDou system (16 satellites in regional orbits over China) already makes China the best place in the world for high-precision GNSS positioning. Like Galileo, China’s global constellation is said to consist of 30 satellites.
That means in the not-too-distant future (about 2018 for Galileo and 2020 for BeiDou):
31 x GPS
24 x GLONASS
30 x Galileo 30 x BeiDou Total: 115
This translates into more than double the satellites in view that we have at this point in time. But, you don’t have to wait. Galileo satellites are usable this year if your receiver has been designed to use them. With each new Galileo launch, you’ll have access to four more satellites until the constellation reaches 30. The same goes for BeiDou.
Don’t take this wrong, GPS isn’t done. Not by a long shot. However, historically speaking, at one satellite per rocket launch, it’s only averaging about one launch every six months. To complicate things, the U.S. Air Force has launched all of the current GPS model (IIF) satellites and aren’t ready to launch GPS III satellites yet. See Don Jewell’s August column in GPS World magazine for details.
The good news is that the user community doesn’t have to rely on an expanded GPS constellation to improve performance any more than the “gold standard” it has become. The difference-makers are going to be Galileo beginning this year and BeiDou beginning in 2018. So, get ready folks, and fasten your seatbelt. The next generation of GNSS is about ready to begin, and your geodatabase is about ready to get a double-shot of Vitamin B.
This will be known as the day in geospatial history that the floodgates were opened for small drones to be used for business. On that day, the Federal Aviation Administration (FAA) officially introduced new rules (so-called Part 107) that allow businesses to fly small (under 55 pounds) unmanned aerial vehicles (UAVs) in the U.S. airspace for business purposes.
There are still a few rules that need to be adhered to, but no longer do “wannabe” UAV pilots need to go through the painful FAA 333 Exemption process to begin flying UAVs for business purposes. The FAA has created a pilot certificate specifically for UAV pilots called the “Remote Pilot Certificate” that does not require any manned aircraft training.
Previously, UAV pilots authorized by the FAA were required to at least have an FAA Sport Pilot Certificate, which required at least 20 hours of manned flight training, among other things. Deployment of the new Remote Pilot Certificate will begin just two months from now, in August 2016, according to this announcement by the FAA.
In a nutshell, following is the operating environment under the new Remote Pilot (Part 107) rules:
Remote Pilot Certificate.
Be at least 16 years old. Pass a three-hour aeronautical knowledge test at an FAA Knowledge Test Center, requiring about 20 hours of study. Pay a $150 fee. The certificate is valid for two years.
Complete FAA Form 8710-13.
Maximum operating altitude is 400 feet AGL, or 400 feet AGL (above ground level) from a structure (e.g. building, roof).
Visual observer (VO) is now optional (was required under 333 Exemption) except if the pilot uses First Person View technology, then a VO is required.
UAV must weigh less than 55 pounds.
UAV must fly less than 100 miles per hour.
You can’t fly over anyone who is not directly participating in the operation, and not under a covered structure.
You can pilot a UAV from a moving vehicle in “sparsely populated” areas, but otherwise must be stationary (e.g. no piloting from other aircraft).
Daylight-only operations.
Pilot can only operate one UAV at a time.
Operations in Class G airspace are allowed without air traffic control (ATC) permission. Operations in Class B, C, D and E airspace need ATC approval. See description of US airspace here.
Operator does not have to be a certificated pilot if a certificated pilot is along side the operator.
Pilot must maintain VLOS (visual line of sight) of the UAS at all times.
If you have a requirement that exceeds one of more of the above restrictions, the FAA says that as long as you can show that your operation can be carried out in a safe manner, you can request a waiver (Certificate of Waiver and Authorization – CoA) via an FAA portal.
The remaining major hurdle for commercial operations is the requirement to maintain VLOS, which still is required under the new rules. With a rotary UAV (e.g. quad-copter) like what I fly, this requirement is easy to adhere to since the UAV isn’t traveling very fast and if you simply let go of the control sticks, it will hover. With a fixed-wing (conventional airplane airframe) UAV, this is not so easy. A fixed-wing can travel 30 to 40 mph, and can be out of VLOS within one minute, and it’s always moving. Nonetheless, even with the VLOS rule still in place, the new Part 107 rules grant a new, easily accessible and powerful tool to collect high-precision geospatial data.
The good news for geospatial professionals is that more UAV companies are focusing on the professional marketplace.
In 2009, 3D Robotics started targeting the DIY (do-it-yourself) UAV market, then the consumer market, and now are focusing on the professional markets like GIS, construction, etc.
Because the rules have opened up to a much broader audience, expect more vendors to offer more products and services for professional UAV operators. For example, at the Esri International User Conference this week in San Diego, Esri showcased its Drone2Map software product that allows Esri software users to process and consume UAV data into the ArcGIS ecosystem.
It’s no longer hype, folks. UAVs are here to stay, and they are becoming an increasingly powerful tool in the geospatial toolbox. The great news is that will all the UAV hype over the last few years, there’s many different vendors offering UAV hardware and softwares for you to choose from. All that competition will be reflected in the quality and price of UAVs on the market, benefitting the consumer.
