GPS World

Category: Lidar

  • A Free GIS Tool Just Got Better

    A few months ago, I wrote a little about ArcGIS Explorer (AE), a free GIS viewer from Esri. It’s a nice tool for non-GIS users who want to view GIS data. Looks like another feature is creeping into AE to make it a bit more powerful. Bern Szukalski, product strategist and evangelist at Esri, blogged earlier this week about new functionality in AE that will allow direct GPS support. In other words, you can connect a GPS receiver (Bluetooth or otherwise) to a device running AE and be able to visualize and record GPS data as its tracking.

    Borrowing from Bern’s Blog, following is a 2D map as he was driving, showing the waypoints and tracks as he was moving. He said he set AE to collect a GPS point every 10 seconds, centering the map as he moved. GPS waypoints and tracks are stored as notes.

    (Click to enlarge.)

     

    The next screen shot shows his path in 3D. Green represents GPS points/paths collected by mouse click. Yellow represents GPS points/paths collected at 10-second intervals.


    (Click to enlarge.)

     

    Bern blogged that he was using a borrowed $18 USB GPS receiver in this example. Don’t pay much attention to the accuracy (or inaccuracy) of the GPS positioning. He could have just as easily connected a sub-meter or centimeter-level GPS receiver (outputing NMEA 0183 messages) and had enough precision to accurately position the center of a 6-inch water meter cover plate on the sidewalk. That’s where this is headed, folks.

    A Quick Note on the Annual GITA Conference

    I didn’t attend the annual GITA (Geospatial Infrastructure Technology Association) conference this year, but I received several reports that this was the last GITA annual conference. That’s pretty sobering (but not surprising), given that it was the 34th such conference that started in the late 1970s. I blogged last year that I thought this years was going to be a really tough one because it wasn’t co-locating with another conference as it was last year with ACSM (American Congress on Surveying and Mapping). Although the demise of the GITA annual conference was predictable, it’s still sad to see it go. Last year, I thought the technical presentations were quite good and clearly demonstrated a need for continuing promoting and developing geospatial apps in the world of infrastructure. Without the GITA conference, I wonder where these folks will go to share their knowledge and experiences. I’d like to reiterate that there are too many niche conferences related to GIS. GIS folks can’t afford the time or expense, and neither can GIS sponsors/vendors, to attend three different small GIS conferences in a 90-day window. What I wrote a year ago is just as relevant today.

    Let’s discuss conferences for a minute

    As good as the content was for both the GITA and ACSM conferences, the attendance was horrible. If there were 1,000 people there (for both), I’d be surprised. At this pace of decline, something’s got to give. I attended the annual GITA conference in Seattle in 2008. If I recall correctly, there were about 1,400 attendees. This year, in 2010, there were maybe half of that including exhibitors. Next year, the GITA conference is operating as a stand-alone conference in a suburb of Dallas, Texas. I predict it might be even worse than this year. The ACSM annual conference is not doing any better, but rumor has it will co-locate in 2011. The two conferences won’t be co-located next year. It’s a time for conferences to start working together.
    Size Matters

    It’s a vicious cycle. The fewer attendees there are, the less interested vendors are in exhibiting and sponsoring the event. Each year, attendance erodes until it doesn’t make sense any longer. Now is the time for conference consolidation, especially in the GIS industry. GIS is tough to segment because it stretches across so many industry boundaries. In April alone, there was the GIS-T (GIS in Transportation) conference in West Virginia, the GITA/ACSM co-located conference in Phoenix and the ASPRS (American Society for Photogrammetry and Remote Sensing) conference in San Diego. All of these are small conferences that are becoming increasingly difficult to justify, financially, for both the operators and the attendees. I can safely say that attendees and vendors certainly would prefer to attend one conference in one location that includes GIS-T, GITA and ASPRS rather than three separate conferences spread out all over the US. They need to consolidate at the same time in a single location.

     

    I suppose the demise of the annual GITA conference is part of the consolidation I wrote about. Being accelerated by the current economy, people will just stop attending some conferences and pick/choose the conference(s) they feel fit their needs the best.

     

    Upcoming Events/Publications:

    Following are a few upcoming events you might be interested in:

    Webinar: April 21st. “LightSquared and GPS: Our Story So Far”. I’ll be participating in a moderated discussion about this issue. If your organization relies on GPS, I strongly encourage you to register. If you aren’t available during that time, register anyway and you’ll be provided a link to view the webinar at a time that’s convenient to you.

    Space Weather Workshop: April 26-29. I’ll be presenting at this conference and blogging about what I hear in order to keep you informed about space weather as the next solar cycle warms up.

    Western Forester: April issue. Look for my article and accompanying articles on Lidar, laser rangefinders, GPS and other emerging technologies that concern the forester and other natural resource professionals.

     

    Thanks, and see you next week.

    Follow me on Twitter at http://twitter.com/GPSGIS_Eric

  • New Technology in Forestry: Are You Ready?

    In the early 1990s, I recall being tasked with training a group of foresters on how to use a new-fangled handheld data collector the company I worked for had developed, along with various pieces of software on it for traversing, timber cruising, vegetation surveys, profiling, etc. Being fairly young and somewhat inexperienced, I didn’t fully understand the challenge of trying to convince a group of seasoned foresters to put away their pencils and “Rite in the Rain” tally cards and pick up an electronic gizmo in which they punched in their cruise plot info, traverse bearings, and various other pieces of field data. Of course, being involved in the development of the new-fangled handheld data collector, I thought it was the best thing since sliced bread. Who could deny the value of error-checking to check for typos, graphic plot of traverses, and no transcribing back in the office?

    It’s too bad none (of mostly none) of the foresters in the room felt the same way.

    “I see how it will help the office people, but what’s in it for me?” questioned one.

    “It takes longer for me to punch it in the data collector than it does to write it down,” argued another.

    Upon sensing the building resentment, the HFIC (Head Forester In Charge) stood up in front of the room full of 40 or so foresters and said, “Well, folks, this is the direction we are going, so you need to get with the program.”

    Eventually, most of them adopted the new technology and some even embraced it. But some of the more technologically-resistant folks would go as far as using “Rite in the Rain” paper to record data in the woods only to return to their truck and enter it into the data collector. However, I believe after a period of time they became quite adept at data entry in their truck, so much so that the data collector eventually made its way into the woods with them.

    That was 20 years ago. The 80386 was the mainstream computer CPU, e-mail was still a novelty, websites were few and far between, and a mobile phone was about the size of lunch box.

    DuraRite “Rite in the Rain” Pocket Notebook

    Since that time, it seems like the forester has been bombarded with one mind-bending technology after another.

    Sorry to break the news to you, but technology is not settling down anytime soon. Following is a taste of where I think some of the technology is heading. In this issue, you’ll also read from my colleagues their take on the various technologies they work with on a regular basis.
    GPS

    Of course, GPS is close to my heart as I have written for GPS World magazine for many years and have been involved with GPS for more than 20 years. My first 10 years in GPS were spent developing GPS mapping products while the past 10 years have been spent as a power user of all sizes and shapes of GPS receivers, from ultra-miniature receivers giving mediocre accuracy to some of the highest -precision receivers ever made.

    Since GPS has been around a long time, you may think that is has reached a level of technological maturity. In some respects, you would be right. It’s been used by foresters since the late 1980s, albeit it has evolved significantly since then.

    In the early 1990s, GPS mapping receivers used for forestry were backpack configurations with handheld data recorders. WAAS didn’t exist, DGPS/beacons didn’t exist, Bluetooth didn’t exist, RTK Networks didn’t exist, and Selective Availability (SA) was active. SA meant that GPS autonomous accuracy (without any sort of correction) was about 100 meters. To improve accuracy, users had to post-process their GPS data using GPS base-station data. Public GPS base stations were virtually non-existent, and the Internet access was not commonplace, so most folks had to install, manage, and maintain their own GPS base stations.

    In May 2000, one of the most significant events in GPS history took place. The U.S. Government turned off SA. Overnight, the autonomous accuracy of GPS receivers increased ten-fold. It was never turned on again, and years later it was announced the feature wouldn’t be designed into future GPS satellites. It is gone forever.

    Since then, GPS availability and accuracy has increased due to a number of GPS system advancements as well as GPS receiver advancements. The price of GPS receivers have also dropped significantly. In 1990, a GPS receiver designed for 2-5 meter accurate mapping was priced at more than $10,000. Today, a sub-meter accurate GPS receiver can be purchased for under $2,000. That trend is going to continue. In fact, GPS is going to change a lot more in the next 10 years than it has in the last 10 years.

    Last year, the U.S. government launched a new generation satellite (model IIF) that adds another signal for civilians called L5. Once enough satellites are in orbit broadcasting L5 (as soon as 2015), you’ll likely see very inexpensive, high-accuracy GPS receivers.

    The beauty of the L5 signal is that it’s supported by other GPS-like systems such as Europe’s Galileo. The European Union is scheduled to launch its first two operational satellites this summer with the second pair scheduled for launch in early 2012. The first 18 Galileo satellites are projected to be in orbit by 2015. Since Galileo satellites use the same L1 and L5 frequencies as GPS satellites, a receiver designed for GPS is easily designed for Galileo, too. One advantage of a GPS/Galileo receiver is that you’ll have more satellites in view, and for foresters working under tree canopy or on steep terrain, this will make mapping a lot easier and quicker. For example, today you might have 6-7 GPS satellites in view while you’re in the woods. With future GPS and Galileo satellites, you might have 12 or 13 satellites in view.

    GPS receivers are becoming cheaper, better, and faster. Similar to personal computers, GPS receivers have declined in price and will continue to decline in price. Don’t be surprised if you see high-precision GPS receivers for mapping being sold for $100-200 in the future. WAAS is going to support L5, too. Today, the best accuracy you can get from WAAS is around two feet. Once WAAS supports L5 (around 2020), it will be able to provide accuracy of around four inches to inexpensive L1/L5 dual-frequency receivers.

    The Russian satellite system (GLONASS) has brought a lot to the table for surveyors and engineers in the past 10 years. In 2000, it seemed the GLONASS program was dead in the water and heading for extinction. The Russian Federation has done a fantastic job of revitalizing GLONASS to the point that GLONASS has become a standard feature on high-accuracy GNSS receivers across the surveying and engineering industries. The value of GLONASS is not accuracy, but rather availability. If you’re in the woods and having trouble tracking enough GPS satellites, GLONASS can add another 5-6 satellite signals, which can be the difference between getting a shot or not in dense tree canopy.

    While GLONASS used to be a feature only offered in high-accuracy surveying receivers due to its complex design, you will start to see mid-range GPS mapping receivers utilizing GLONASS. It’s also likely you’ll see consumer GPS receivers offering GLONASS as well because in the past couple of months, two of the GPS chipset companies introduced GPS/GLONASS chips for the consumer market.

    Bottom line: GPS receivers are going to get significantly more accurate, cheaper, and work in more places than they do today.
    Satellite Imagery

    At the Esri conference la
    st summer, Lawrie Jordan, Esri’s director of Imagery Solutions and founder of ERDAS, said this is the most exciting time to be involved in imagery in his 40-year career.

    Commercial satellite imagery quality and availability is the best it’s ever been. It wasn’t that long ago that five-year-old, three-meter-pixel resolution, black/white satellite imagery was the norm. Today, GeoEye, DigitalGlobe, RapidEye, and Spot Image are delivering an amazing amount of digital imagery at even more amazing resolutions on a regular basis. Jordan predicts that in less than five years, every square inch of the Earth will be imaged (by satellites) constantly. He said we are already half-way there.

    There is no better technology than satellite imagery for capturing the devastating impact of large-scale natural disasters such as the March 11, 2011, earthquake/tsunami in Japan.

    The following image (half-meter resolution) of Miniami Sanriku Cho, Japan, was captured by the GeoEye-1 satellite on November 15, 2009, prior to the earthquake/tsunami.

    Courtesy: GeoEye

    The next image (one-meter resolution) was taken on March 12, 2011, a day after the fifth strongest earthquake in recorded history struck off the coast of Japan, creating a massive tsunami that caused devastating flooding and resulted in extensive infrastructure damage and loss of life.

    Courtesy: GeoEye

    The following one-meter resolution image was shot by GeoEye’s IKONOS satellite on March 23, 2011. According to GeoEye, this is the Indian Gulch fire burning near Golden, Colorado. As of March 24, the fire had consumed 1,500 acres and was 25 percent contained. GeoEye says this type of imagery may be used to assess and measure damage to forest and other types of land cover — especially when compared to a false-color image of the same area.

    Courtesy: GeoEye

    Bottom line: Commercial satellite imagery is becoming more readily available and at higher resolutions than ever before. Look for that trend to continue.

     

    Lidar

    Lidar (Light Detection and Ranging) is a remote sensing technology that is sometimes referred to as 3D scanning. Traditionally, LiDAR is thought of as an airborne technology with a scanner mounted in an aircraft that can map huge swaths of ground, collecting elevation data in order to create a digital elevation model (DEM) for topographic surveys and other types of analysis. While collecting the data is relatively quick (albeit expensive), a huge amount of data is collected and must be processed.

    According to the US Geological Survey (USGS), two problems have hindered Lidar for scientific applications beyond creating bare-earth DEMs.

    1. The high cost of collecting Lidar data.
    2. The steep learning curve on research and understanding how to use the entire point cloud.

    While airborne Lidar has been around for quite some time, terrestrial (land-based) Lidar has made a strong push in recent years, and has even made its appearance on mainstream television (Crime Scene Investigation – CSI on CBS, 2005). Working on the same concept of 3D scanning, terrestrial Lidar is not used from thousands of feet in the air looking down, but rather on a tripod scanning a room, or scanning a bridge from 200 feet in the distance.

    Courtesy: Wikipedia

    Personally, I coordinated a 3D scanning project many years to create a 3D model of a wrecked SAAB 9000 as part of an accident reconstruction project. The process of scanning was very quick. It was completed within a couple of hours. The process of creating a deliverable (this was circa. 2003), however, was another story. It was a very labor-intensive project that took weeks. Today, software to create a deliverable from these big “point cloud” files has improved dramatically and more increasingly, third party software developers are creating software tools that assist users in working with these data sets.

     

    Terrestrial 3D scanners first started making their appearance in the land surveying and civil engineering professions. 3D scanners are an efficient way to create complex as-built maps such as in refineries.

    Courtesy: Wikipedia

    They still have somewhat of a steep price tag today, but they were especially expensive when they were first introduced, well over $100,000 at that time.

    But terrestrial 3D scanning is hitting its stride and finding its way into other industries besides surveying and engineering. Yes, even forestry. Albeit in its early stages of development, 3D scanners are being hauled into the woods.

    Take a look at the following illustration courtesy of TreeMetrics of Ireland.

    Courtesy: TreeMetrics Ltd

    According to TreeMetrics, millions of points are collected with each 30 meter scan. After downloading the scan data, software filters irrelevant data and creates a 3D profile of each tree. The DBH, height, taper, straightness and volume are calculated for each tree. Trees that weren’t scanned due to heavy branches or other obstructions are modeled. Stem data files are then produced from which simulation models can be developed that will be used to estimate the product value before a tree is harvested. If harvesting is not done at that time, data is recorded and can be compared to future scans to monitor growth and health.

    Bottom line: 3D scanning, especially terrestrial 3D scanning, is a technology you’ll see in the not-so-distant future, maybe even in the woods. Prices of 3D scanning equipment will continue to decline while software to handle the massive point clouds will continue to become more powerful.

    GPS, satellite imagery, and Lidar are only three of a number of advancing technologies that foresters will see working their way into their toolkit. Mobile phones are also advancing at a rapid pace, becoming significantly more powerful and performing many more tasks than just a phone. The more advanced mobile phones have a GPS chip built inside as well as street maps and aerial photos a la Google and Microsoft. If you look back at mobile phones 10 years ago and compare them to today’s phone, it’s hard to imagine where they will be 10 years from now. They could quite possibly be the central piece of office equipment for all your communications and document management.

     

     

    Thanks, and see you next week.

    Follow me on Twitter at http://twitter.com/GPSGIS_Eric

  • As Data Collection Technology Advances, So Does BIM

    My fellow geospatial editor, Art Kalinski, wrote about BIM (building information modeling) earlier this week in the GeoIntelligence Insider newsletter. I’ve touched on the subject before. All too often we think of GIS as it relates to outdoor infrastructure: street maps, utility systems, parcel maps, timber harvesting, land management, environmental management, etc.

    Last summer at the Esri Surveying and Engineering Summit, I attended a talk presented by Stuart Rich, chief technology officer of Penobscot Bay Media, LLC. He presented on understanding, documenting, and building systems to support spatial data infrastructure’s security requirements as well as initiatives to move GIS inside the building footprint.

    He said he was involved in using terrestrial LiDAR inside buildings to collect massive amounts of data. So much, in fact, that “the value of measurement is trending very close to zero” using very high-volume data collection at 250,000 points/second.

    Stuart’s Factoid: Only 16% of cities are mapped, with a big vacuum being building interior maps in urban areas.

    He also discussed the lack of attention to underground infrastructure mapping.

    Another example of BIM detail, as provided in Art’s article, is a building wall which, in most GIS, if it exists at all, is a single polyline, maybe two polylines in rare cases. Thinking in a GIS sort of way, a building wall ”could contain more than six layers of data: paint, drywall, framing, blocking, fire stops, insulation, etc.” Think about this for a minute. Imagine how the quality of decisions would improve if the building owner was considering renovating his building and had this sort of information and software tools available. The decisions about which walls to leave or take down and future layout, for instance, would likely change if this information was readily available.

    Honestly, for building design, and most kinds of design for that matter, CAD isn’t the right tool if you think about it. It doesn’t have the database or analysis tools behind the various points, lines, and polygons to make the best decisions. This is the foundation of the GeoDesign concept being promoted these days.

    Although I didn’t set out to write about GeoDesign, it’s very fitting. According to Wikipedia, “GeoDesign brings geographic analysis into the design process, where initial design sketches are instantly vetted for suitability against a myriad of database layers describing a variety of physical and social factors for the spatial extent of the project. This on-the-fly suitability analysis provides a framework for design, giving land-use planners, engineers, transportation planners, and others involved with design the tools to leverage geographic information within their design workflows.”

    Of course, as Stuart mentions and as I’ve written about before, a highly related topic is underground infrastructure (sewer, water, electric, gas, telecom). That’s a whole other subject and one that I’m close to as I spend quite a bit of time working with landscape architects who deal with underground infrstructure on a daily basis in their projects. For them, as opposed to “what’s inside the wall,” a landscape architect has to ask “what’s under the ground.” If he or she doesn’t know until the construction crew starts tearing down and digging, then the project risk increases substantially.

    A good example and story I read this week was a short interview that Directions magazine published about the San Bruno gas pipeline explosion which killed nine people. You can read the interview here. Essentially, it’s a lesson in spatial data management with respect to underground infrastructure, with spatial data accuracy being the primary theme.

    Data, Data, Data

    In the world of real estate, it is said the three most important features of real-estate property are location, location, and location. I think you can say that the three most important feature of a GIS are data, data, and data. It’s not the software tools we are lacking, it’s the data. That’s why revenue from GIS data over the past eight years has grown at a compound annual growth rate (CAGR) of ~15 percent, while GIS software has grown considerably less, according to research firm Daratech, Inc.

    Where Is the Data Coming From?

    Data collection technology is changing rapidly. Look at two key sources of geospatial data: remote sensing and GPS. Remote sensining, in particular, is well-suited for building interior data collection.

    At the same Esri Surveying and Engineering conference I mentioned above, Lawrie Jordan, director of Imagery at Esri, said that this is the most exciting time to be involved in imagery during his 40-year career.

    Commercial satellite imagery quality and availability is the best it’s ever been. It wasn’t that long ago that three-year-old, one-meter-pixel resolution, black/white imagery was the norm. Today, GeoEye, DigitalGlobe, RapidEye, and Spot Image are delivering an amazing amount of digital imagery at even more amazing resolutions. Jordan stated that in less than five years, every square inch of the Earth will be imaged (by satellites) constantly. He said we are already half-way there.

    Another form of remote sensing that’s busting at the seams is 3D scanning (terrestrial LiDAR). We’ve seen a lot of development in 3D scanning over the past 10 years. The equipment used to be pretty expensive, but the prices are coming down as the technology gains acceptance. I recall using the technology a number of years ago (circa 2003). I was tasked with an accident reconstruction project. Part of the task was to create a 3D model of a wrecked automobile. Traditionally, one would use a surveying total station and measure shot-by-shot at key points on the automobile. Even measuring 1,000 points on the automobile wouldn’t result in enough data points to create a reasonable 3D model. We decided to use a 3D scanner. We were able to scan the automobile in under two hours and collect a tremendous amount of detailed data.

    The good news is that we had a tremendous amount of detailed data to work with. The bad news was the same, we had a tremendous amount of detailed data to work with. I think it took us four weeks to produce a deliverable from the data. However, keep in mind that this was nearly eight years ago and software tools have come a long way since then (Safe Software, Leica Geosystems, Trimble, Topcon, all have software tools for dealing with 3D scan data), so the process in producing a deliverable today is more efficient.

    I’ve written and said this many times over: geospatial data fuels the GIS software engine. Esri and other GIS software developers are making very powerful GIS engines. In fact, the GIS software engines far exceed the quality of the geoespatial data we have to work with. BIM is a great example of that. There’s a substantial lack of BIM data, but with 3D scanning and other geospatial data collection technology advancing rapidly today
    , that will change. GIS will move indoors.

    Thanks, and see you next week.

    Follow me on Twitter at http://twitter.com/GPSGIS_Eric

  • Confessions of a Public GIS Manager: Does IT Outsourcing Really Save Money?

    In following up on my example of a simple GIS app for entering and displaying lat/lon coordinates from a spreadsheet (or text file), the discussion went from cloud to client and then back to cloud. The reason may surprise you. Recall that I was looking for the best solution for a reader who was looking for a simple GIS app to display gobs lat/lon coordinates.

    My first inclination was to use an online app (cloud) such as arcgis.com or Google Earth in order to stay away from the users needing to install and maintain software on their local desktop computers. No go. The functionality just wasn’t there. All along, my backup plan was to use a client app like ArcGIS Explorer. Well, after messing around a little and consulting with an online discussion group, that’s the route I went. I wrote about it last week.

    Subsequently, a GIS manager from a public department (state level), wrote about his experience with client-based apps and his challenges with IT outsourcing. It really make one reconsider the cost effectiveness and efficiency of IT outsourcing. His perspective makes interesting reading:

     

    We didn’t go the ArcGIS Explorer route primarily because of the current war (GIS vs. IT) which scientific computing is losing badly at this point in time. Our State and many others are neck deep in smelly muck created by business computing’s IT consolidation and outsourcing.  I just got back from a meeting where I heard another round of horror stories from VA.

    For more than five years, our WAN-based users at regional offices throughout the state have ran GIS via Citrix with customized ArcGIS desktop apps written entirely in-house by our staff in VB and .Net.  We elected that strategy because at that time it was really the only serious option to allow access to the large amounts of data we had in our geospatial archive here at our headquarters. It was also attractive because back then we controlled our infrastructure and our LAN and were highly influential in WAN decisions because we had a very advanced computing environment here.

    Then came IT consolidation and the predictable downgrading of advanced Agency’s capacity so we’d be able to open really big word processing documents on our desktops. By that, I mean scientific computing like GIS, Remote Sensing, etc. apps were not considered seriously in that process even though we need to operate much closer to DoD or NGA-like computing capacity compared to the average accountant. After multiple attempts to modernize our Citrix and SAN, resources were turned down and we decided we’d better switch to a new approach.

    Because we’re charged serious bucks every time we put in a service call to have ArcGIS Explorer installed on an existing or new PC, we elected to go as thin client as possible. Everyone has a browser and we don’t have to pay to have that installed.  We initially developed some betas using ESRI’s JavaScript solution but browser differences (both different versions of the same browser and Microsoft vs. Firefox on individual PCs just inside our unit) caused many applications development problems so we abandoned development with that API.

    That’s when we elected to do a very serious Flex vs. SilverLight comparison and the rest is history. The new beta has a rainfall widget we’re particularly proud of. It grew out of our active mining program staff having to respond to horrific flash flooding typical in spring and summer in our state. This new app will allow staff to go to the permitted sites to check stability of sediment control structures where the most rainfall (… based on Nexrad) was projected to have fallen for the first time this spring.

    In April this year we’ll find out if our jobs are going to be outsourced or whether our state will modernize internally. The refusal to allow Citrix and SAN improvements is a harbinger of the way that will go I believe. We have been presented with 4 SAGs in the last decade. I wonder what the total count will after the first decade of outsourcing?

    Many potential problems exist for geospatial programs because of IT consolidation and the more recent potential of outsourcing GIS. IT consol first. My unit does a great many very large (… and long) computing jobs. We routiinely move data from one projection or datum to another. When you deal with thousands of raster tiles, a reprojection project can take weeks to accomplish successfully. We also do spatial analysis projects that take even longer. We recently used Landsat scenes and higher resolution commercial satellite data plus aerials from multiple dates to do change analysis. That job took more than a month on beastly PCs we’ve built up specifically for these very tough jobs.

    [[Our]] ICI is an old DoD concept I pulled back into use. We built these platforms after about a year of total frustration having our big jobs crashed from IT pushes of OS upgrades happening in the middle of producing badly needed new deliverables, network disconnects dropping out our license checkout connectivity to a remote license manager on the WAN, etc. I’ve already mentioned the failure to consider geospatial in upgrading infrastructure and improving bandwidth.

    Even keeping your servers local can be a big battle in the war.  We have an older county size LiDAR dataset (pre-.las) processed and delivered as a point cloud. We have new LiDAR from the same county and we’re trying to do a comparison of the two datasets. Depending on what USGS quadrangles are selected it typically takes 30 to 40 minutes to load up four 1:24K quad size tiles of the older point cloud data via our LAN at fast Ethernet speed. Move that to a WAN situation and we need to start it loading in the evening so it’s ready by the following morning (but that won’t work because of the auto-shutdown software on all the desktops that executes every evening a 7PM). And then there’s the joke about the virus checking software pushed out to every desktop, configured all the same for everybody and auto executed and the twenty-one staff that mapped over five terrabytes of GIS datasets on the SAN and their very fast new computers (sarcasm) being brought to the approximate speed of molasses running up hill because the virus checking code never stopped trying to check all five TBs on each of the twenty-one PCs.  It wasn’t much of a joke when the whole Agency’s networking speed dropped to a crawl! Need I say more about one-size-fits-all IT mentality shooting off their own feet!

    Negative aspects of outsourcing geospatial jobs are obvious. No contractor is going to know the individual program requirements like in-house staff and that’s a challenge even for us. Good example … the rainfall widget on the new beta app I pointed you to wasn’t requested by our mining folks until we approached them with the idea that we might be able to do something like that. Would there have been that kind of insights by a big corporate consulting firm like IBM or HP? I think not.

    On the good side of IT consolidation, if geospatial folks are pulled together into a core group I think that gives folks the chance to work on a broader spectrum of tasks not limited by the bounds of what one state government Agency desires, but rather the state as a whole. That could be a good thing. Also, it gives Agencies with a GIS effort, consisting of one or two folks, access to experts they’d not be able to otherwise tap into (GIS DBAs, geospatial applications development gurus, etc.) and that definitely would be a very good thing. Of course that hasn’t happened here. On the good side, with outsourcing GIS jobs, I’m clueless as to how that could ever benefit anyone except the recipient of the contract. The horrible stories from colleagues give me night terrors.  PC refresh cycles of 5 years, horrendously expensive SAN storage rates, etc. You name it, &
    nbsp;the customer is hosed by it.

    There really is a business vs. scientific computing all-out war going on all around us and as I said initially, too many scientific computing types have their heads down doing the exciting stuff while the fight rages on, without them even knowing about it. If you can wake them up to the reality that business computing “experts” may very well be building a scientific computingless future in which they’ll have no place (or job), it would be greatly appreciated.

     

    I’ll be writing more about this. It’s a serious issue and it’s not going away, especially with the geospatial industry continuing to put up strong growth numbers.

     

    Thanks, and see you next week.

    Follow me on Twitter at http://twitter.com/GPSGIS_Eric

  • Where the 3D Scanning Action Is, and Keeping It Simple

    I’m preparing for some conference presentations I’ll be giving in a couple of weeks. One of the subjects I’m covering is spatial data transformation, or traditionally known as ETL (Extract/Transform/Load) tools. I’ve written many times before that in the geospatial industry, data is the fuel. We, as users, have access to some amazingly powerful GIS software tools.

    Clearly, the geospatial enabler is data. Without it, it’s like having a fishing pole without a pond; a tool without a purpose.

    If you look at emerging geospatial technologies, where’s the data coming from? Yes, crowd-sourcing, GPS/GNSS, and imagery are, and will continue to be, volume sources of geospatial data.

    From an infrastructure perspective (civil engineering), 3D laser scanning is a particularly interesting source of high-volume geospatial data. Ground-based and airborne 3D scanners create insanely huge volumes of data. Although an emerging technology, these scanners (LiDAR technology) have been around for many years.

    I recall using this technology on projects 8 or 9 years ago to scan accident scenes and infrastructure such as bridges. The scanning time was amazingly efficient. In some cases, the scanning data collection sessions were done in a couple of hours. During that period, literally millions of data points were collected. For the first time, the ratio between labor expended on data collection and labor expended on data processing was extremely skewed towards data processing, and that was the headache.

    While scanning time was very short, data processing time to produce a deliverable was brutal, literally taking weeks. Granted, that was 8 or 9 years ago. Advanced software tools have made data processing more efficient today, but dealing with huge volumes of data is still a challenge. Some people say that scanning may eventually replace traditional surveying equipment that shoot and record one coordinate at a time. A land surveyor, on a really strong day, may be able to shoot and record upwards of a 1,000 coordinates. With a scanner, that same person could shoot and record millions of points in a day.

    Data, Data, Data
    Ground-based and airborne LiDAR technology are clearly on the uprise. Last year, while most conferences were struggling to maintain the 2009 levels, even failing, the SPAR 2010 3D imaging conference was up 23%, according to their reports. The International LiDAR Mapping Forum conference also reported record attendance figures. Although the conferences are still in niche-mode (less than 1,000 attendees), the growth is steady.
    If you step back a bit and look at the big picture, the game is in data processing. Yes, equipment manufacturers will crank better and cheaper scanners, but turning those 3D point clouds into useful products is where the action is.
    You can see this with SAFE Software’s recently announced FME 2011 product. While historically focused on GIS and CAD interoperability, SAFE obviously sees the upside in the point cloud business as a major part of FME 2011 is focused on dealing with the massive amounts of data created from 3D laser scanning.
    Keeping it Simple
    Changing gears…
    With all this geospatial technology advancing faster than a rabbit on a motorcycle, it’s hard to slow down and look at the simple uses of GIS that still offer a lot of value. As much as most of us are pushing hard to implement more and more spatial data technology, it’s just as important that we introduce people to GIS, even a very simple version of it.
    This week, a reader asked me about the best way to display a map from a bunch of lat/lon coordinates (little or no attributes) in a spreadsheet. No complex attribute tables, no strange map projection, just a spreadsheet of lat/lon coordinates.
    This challenge gave me reason to revisit Esri’s freely available ArcExplorer software. It wasn’t my first choice, but it’s where I‘ll likely end up. I haven’t touched ArcExplorer (I know that’s not the name of the current software, read on) for quite some time (as in a couple of years or more). I use ArcGIS, AutoCAD and a half-dozen other spatial data software tools.
    When presented with the challenge, my first inclination was to push her towards arcgis.com in order to steer her away from having to download, install and maintain desktop software. No go. After a quick post to a support group, I’m told there’s not an easy way to add this data to an arcgis.com map. My other thought was Google Earth. Naah.
    I subscribed to Google Earth Pro for a year and it really is sort of cheesy, to me. Maybe it’s because my view is distorted from my experience with GIS software in the past, but it seems to me that Google Earth is still primarily eye-candy, and what I really wanted was an easy-to-use, light-weight GIS. However, I do hope that they continue pushing that technology forward.
    All along, I thinking my ultimate back-up plan would be to recommend ArcExplorer. I went to download it and remembered it’s now upgraded to ArcGIS Explorer. I remember reading and posting that news awhile back, but hadn’t taken the time to download and preview it. It’s a much different animal than ArcExplorer, and I like what I see so far. I haven’t tried to import any data yet, but from the menu selection, I can see it will accept the simple ones such as shapefiles, raster imagery, ASCII, and GPS exchange files. Most simple data sets can be converted to one of these formats using freely available software tools.
    ArcGIS Explorer Opening Screen
    This will be an interesting experiment, and one I will update you on, likely next week, as I try it with a sample data set from the reader.
    I really like the opportunity to introduce someone to GIS, even at just a simple level because I believe will open their eyes to other possibilities in the future. It empowers them to think more GIS-centric.

    Thanks, and see you next time.

    Follow me on Twitter at http://twitter.com/GPSGIS_Eric

  • LizardTech MrSID Generation 4 Files Now Supported in Global Mapper

    LizardTech announced the integration of its MrSID Generation 4 (MG4) SDK into Global Mapper version 11.01. Until recently, Global Mapper’s customers were not able to load point cloud datasets that were compressed to MrSID Generation 4 using LiDAR Compressor into Global Mapper. However, with the addition of support for MG4 in Global Mapper version 11.01 users can load point cloud datasets compressed to MrSID Generation 4 for use in volumetric analysis, contour generation, and visualization.

    “Adding MG4 integration to the latest version of Global Mapper is just another step to ensure that our customers have as many mapping tools possible at their fingertips,” said Mike Childs, Global Mapper Software LLC. “Based on user feedback, we believe this integration with LizardTech will bring added value to our customers.”

    “LizardTech’s goal is to give customers tools for using their point cloud data compressed with LiDAR Compressor in the applications they use every day,” said Jon Skiffington, LizardTech’s director of marketing. “Many of our customers use Global Mapper, but were not able to use it with MrSID files created in LiDAR Compressor. Now our customers can easily load point cloud datasets compressed to MrSID Generation 4
    into Global Mapper.”

  • GEOINT 2009

    The place to be if your job is intelligence and why what is where.

    By Art Kalinski

    When I was in graduate school at the University of North Carolina at Charlotte, Dr. Jerry Ingalls shared a succinct description of the “new” geography. He stated that old geography was merely the study of where everything was. However, new geography, with its spatial analysis tools, had significantly expanded the field of the study to “why what is where”  and knowing why we can start predicting new “wheres” based on known facts. That, of course, is where geospatial intelligence is today, and some of those tools and techniques identified the location of Iranian nuclear facilities long before they became public knowledge.

    IMG_0775Learning about the latest tools and techniques is the primary reason for conferences, and there is agreement in the geospatial community that GEOINT is the place to be. Organized by the United States Geospatial Intelligence Foundation (USGIF), attendance at the San Antonio conference was the highest it has ever been, according to USGIF President Keith Masback. Even with a weak economy, the over-arching opinion of all attendees was that the intelligence business will continue to grow regardless of world politics. By its nature, this conference really had many more “chiefs” than “Indians,” and many exhibitors spared no expense at the conference, knowing that they were reaching key decision makers.

    USGIF, a nonprofit educational organization created by the geospatial intelligence community, is the organizing force behind the conferences. There is heavy participation by the National Geospatial-Intelligence Agency (NGA) and other intelligence agencies, so the conference attracts top executives in the geospatial industry. The speaker and attendee list reads like a who’s who of the geospatial and intelligence fields.

    General Clapper, the Under Secretary of Defense for Intelligence, was a keynote speaker. He stated his belief that regardless of geopolitical decisions, he sees no decrease in the need for intelligence in Afghanistan and many other locations around the world. He further addressed the need for much faster turn-around of actionable intelligence and cited the joint efforts between the SIGINT (Signals Intelligence) and GEOINT (Geospatial Intelligence) communities.

    General Clapper discussed some of the work of the ISR (Intelligence, Surveillance, Reconnaissance) Task Force, which is seeking new technology and the Holy Grail of intelligence, automated target identification in complex environments. He also spoke about the benefits of commercial imagery sources and its use in an impressive NATO Fusion Center he toured.

    The second keynote speaker was Representative C. A. Ruppersberger, D-MD, chairman of the House Technical/Tactical Intelligence Subcommittee. The congressman addressed his concern that the U.S. is in danger of losing its preeminence in space because regulations are hampering development. He specifically addressed a need to overhaul International Trade in Arms Regulations (ITAR) that are hurting the U.S. commercial satellite industry. He also stated the need for additional research and development funding like the ones that built the U.S. space program and a greater emphasis on technical education. A troubling statistic he cited is that China has 440,000 engineers compared to the USA’s 65,000.

    Vice Admiral Murret, head of NGA, then spoke of his agency’s support not only for the military but humanitarian assistance in natural disasters such as flooding and earthquakes. He talked about the new NGA facility at Fort Belvoir and about how one third of his agency now works in St. Louis.

    In the exhibit hall close to 200 exhibitors demonstrated their latest efforts. Some highlights include:

    Cogent3D and Lockheed Martin demonstrated the release of GeoSketch, a plug-in for Google Sketch Up.  GeoSketch permits military users to build 3D models using the easy to use Google Sketch Up software. The tool permits users to import military UAV video imagery, oblique imagery, and other photo sources to rapidly build 3D models even if geo-referencing data or camera models are missing. The models can then be exported in common formats such as Google, Multipatch, or OpenFlight.

    Digital Globe announced the successful launch of its newest high-resolution satellite, WorldView 2. Imagery from the new satellite will be available in a few months, doubling Digital Globe’s image-collection capability, including multi-spectral imagery.

    LEXISNEXIS news open source highlighted the tremendous wealth of data that it makes available to intelligence analysts. Appistry and NJVC had extensive information on cloud computing and their ability to deliver mission-critical data, including legacy data, to users around the world.

    Pictometry and Lockheed Martin announced their alliance and creation of a new service, Intelligence on Demand (IOD). IOD promises to be a game changer. (See October’s column for details.)

    Every conference I attend there is always a new technology that really catches my eye.  Ball Aerospace was demonstrating such a technology, Flash LIDAR. Flash LIDAR has been a laboratory curiosity for a while but Ball Aerospace has made it a functional tool. Most current LIDAR collections use a laser to scan the ground with the return being sampled resulting in a collection of points on the ground that provide elevation data from which a DEM or contour lines are created. Although this is a rapid process it is sequential and not instantaneous.  The resulting data can be very coarse or fine depending on the sampling interval.

    Flash LIDAR is what the name implies; an entire area is imaged in one nano-second flash. The laser is diffused over an area and flashed once. The resultant image is a broad but dense sample taken at the same instant rather than through a scanning process. Since the image is taken from the same point at the same instant, the data can be used to create accurate 3D models. Those models can then be draped with photographic images or even video frames. The process is so fast that 3D models can be created almost in real time.

    The below images are a practical demonstration of the Ball Aerospace process using Flash LIDAR combined with a live video camera. As each frame of the video image is taken, a simultaneous Flash LIDAR image is also taken from the co-located LIDAR unit. The photo shows the live video and point representations of the Flash LIDAR 3D surface and the resultant 3D image draped on the moving 3D model.

    It’s hard to tell from these still 2D photos but seeing this system in operation was impressive since the Flash LIDAR and resulting 3D models were continuous and perfectly registered. The only limitation of this demonstration was that human flesh is not a good “Reflective Surface.” Note that in the photo the Ball representative was very animated. This stop-action screen-capture shows him as he jumped up.  In all cases the Flash LIDAR kept up with the dynamic movements.

    Point cloud.
    Point cloud.
    Point cloud.
    Point cloud.
    Point cloud.
    Point cloud.
    Wire-frame image.
    Wire-frame image.

    This was an impressive conference that suffered from too much in too short a time.  Two tools that were very helpful was a daily newspaper, the Show Daily, that recapped the previous day along with the current day’s schedule. It was published, printed, and placed under our doors as we slept. The other useful tool was a daily video show with key presentations and interviews for those that were unable to be in two places at the same time. It was available at several break locations and on our in-room TVs. This has been done at other conferences but not as well as the execution of USGIF.

    The USGIF team deservers a “Well Done!”

  • 3D Geospatial Data

    The usage of three dimensional data in the geospatial industry is in its infancy. It makes sense to me. Sometimes, it’s hard enough for folks to obtain and maintain accurate two dimensional data, not to mention elevation! However, as geospatial technology continues to evolve, the availability of 3D geospatial data will evolve. I’m pretty sure that in ten years we will look back and be amazed at how little we used 3D geospatial data.

    But for now, what the heck are Mean Sea Level, ellipsoidal height, orthometric height, geoid height?

    Sources of accurate elevation data are difficult to find. Typically, you’re going to find elevation data from aerial photogrammetry projects, LiDAR missions or from GPS data collection projects. Since availability of this sort of data on the world-wide web isn’t as prevalent as 2D geospatial data, 3D geospatial data utilization isn’t main stream yet.

    There’s also the issue of the definition of elevation. Yes, just like there are differential horizontal datums, there are a variety of elevation datums. On legacy paper maps, elevations are typically displayed with respect to Mean Sea Level (MSL). MSL is an the elevation reference for local areas, but the Earth is not like a bathtub where gravity has an equal impact on the water in the bathtub that forms a smooth surface. MSL around the world varies tremendously. 2 meters MSL in New York is orders of magnitude different than 2 meters MSL in Hong Kong.

    MSL is a complicated subject in itself. Check out this web page on the National Geodetic Survey’s web site that provides definitions related to MSL. The Earth is not a perfect sphere and gravity influences vary by region. For centuries until recently, elevations were stated with respect to sea level because that was the most reliable and widely known reference.

    GPS has changed that. GPS uses an elevation model called the geoid which was intended to somewhat approximates MSL. There are a couple of good references that provide much more detail. They are worth reading. One is from ESRI written back in 2003 by Witold Fraczek. The other is from an NGS presentation given in 2007 by Daniel Roman.

    In fact, following are a couple of graphics from the NGS as well as one from Dr. Roman’s presentation that draws a clear picture of how GPS heights are related to MSL.

    H = Orthometric height (Mean Sea Level), h = Ellipsoidal height, N = Geoid height

    Note that the height determined by GPS is the ellipsoidal height, not Mean Sea level. The difference between the two can be tens of meters.

    Most GPS receivers have a rough model of the Geoid height built into it. However, it’s very rough and can be a few meters in error. To resolve this, significant efforts have been made in the two decades to create high resolution geoid models. Creating a high resolution geoid model (for a country) is a relatively large effort that requires very skilled people and specific equipment.

    Following is a similar graphic illustrating North American Datum of 1983 and GEOID03, which was the most recent geoid model of the United States (GEOID09 was just released).

     

    Finally, following is a graphic from Dr. Fraczek that depicts the relationship between the ellipsoid, MSL and the Earth’s surface. You can see here that at some points, the ellipsoid is actually above the geoid and at some points, it’s below the geoid.

     

     

    The purpose of this column is to point out that when you receive 3D geospatial data, you should inquire what about the elevation data is referenced to. Are they ellipsoidal elevations? Are they MSL elevations? If MSL, what was the resolution of the geoid model used?

    Flushing out horizontal datum inconsistencies in your GIS is, for the most part, pretty straight-forward. The 2D view is the norm and once you bring data into your GIS, you can compare the imported features to the existing features and identify fairly quickly if there’s a problem with the 2D data. The problem is that most GIS folks aren’t used to working in a 3D world. I speculate that most people figure that if the 2D data is reasonable, then the elevation (if it exists in the database at all) must be accurate. It would be interesting to hear from folks who are making a concerted effort in quality checking the heights used in their GIS.

    Even though GIS horizontal data is still far from perfect with respect to accuracy, at least I can see the road to success. The quality of horizontal data in the past ten years has improved significantly thanks to widespread availability of data collected via remote sensing and GPS data. I think that trend will continue as the widespread availability of accurate horizontal data continues to improve. The roadmap for 3D data isn’t so clear. Not only is there a lack of accurate 3D data, but also the models (eg. geoid model) for generating accurate 3D data continue to evolve.

    Applications for 3D data are expanding and are going to continue to expand. People, both inside the geospatial industry as well as the general public, still have a hard time visualizing 3D data. For example, a land development plan for a site can be communicated much more effectively if there’s a 3D visualization (either still image or animated video) that accompanies the engineering drawings. Following is a visualization of a particular golf course hole where the architect was trying to convey the design change to the golf course owner. The image on the top is the existing golf course. The image on the bottom is the proposed design. The data used to create the terrain model in these images was high quality 3D geospatial data.

     

    Thanks and see you next week.

  • The Struggles of a City GIS Manager

    This is real. The names have been omitted, but this is happening as I write at one city and I’m willing to bet many, many more cities around the world. The city is typical in the US. Its population is ~23,000. Geographic area is ~8 square miles. There are 430 acres of parkland, over 150 acres of designated openspace and 110 miles of sewer pipe pumping 2.3 million gallons per day.

    The issue at hand? These economic times are tight and the city is considering cutting back the GIS department.

    To me, an interesting fact is that this is not a city that’s behind the technology curve. In fact, I think they’re ahead of it. Has the GIS Manager (current and previous) done such a good job that they’ve worked their way out of a job? They’re using state-of-the-art GIS software products such as ArcGIS Server, ArcGIS desktop, ArcPad and even developed their own custom app using MapObjects that’s in use on 100+ computers throughout the city departments. They’re also using high performance GPS/GIS receivers to keep their GIS up-to-date.

    To give you an idea, following is a graphic illustrating the layout of their GIS:

     

    They serve up and make available data to the public much more than other municipalities that I’ve dealt with. In addition to their internal users, they serve this data up to the public 24/7 via an online, interactive web interface. Their data layers include:

    Utilities – Sewer, storm, water, streets, street signs.
    Land use – city-owned land, parks, open space.
    Environmental – Contours, slope, wetlands, streams.
    Planning – Zoning, comprehensive plan, buildable land.
    Parcel mapping – Taxlots, easements, property info, plat info.
    Boundaries – City limits, neighborhood assoc, special districts.
    Site Addresses – Master address file, geocoding.
    Digital imagery – Orthophotography, LiDAR, DEMs.

    They also develop and support applications for other city departments. Users of the custom mapping application developed in MapObjects include the police (in patrol cars on rugged laptop computers), EOC (Emergency Operations Center), public works, parks, planning, engineering in addition to managers and office staff who are able to print their own maps instead of relying on other city personnel.

    Earlier this year, the city conducted a survey to measure GIS usage. Following are the results:

    GIS as a business tool image
    How does this compare to your GIS user base?

    Do you know how many people are utilizing your GIS and understand what they are using it for?
    Does the city management/city council understand the benefits the GIS provides?

    In a conversation I had with the GIS Manager, I think it was summarized best in the following statement:

    “How do you put a price on instantaneous information?”

    An example was used regarding utility infrastructure. How would one, without a GIS, communicate the status of the utility infrastructure system for a maintenance or development project? It would involve finding, organizing and collating paper maps (probably from different departments and maybe from different agencies, including utility companies) in a manner that would effectively and efficiently serve the requestor. That process would take several “man-days” and painfully slow interdepartmental/interagency coordination. And, at the end of the day, the product would most likely be substandard to a GIS-derived product.

    I equate it to, if I may be so bold and over-simplistic, to maintaining ones vehicle. You can choose to spend the time and money to change the oil, maintain the brakes, change the transmission fluid, change the windshield wipers, wax the exterior, vacuum the interior, etc. and the vehicle will run smoothly and reliably and serve you well. On the other hand, if one does none of the above maintenance, there is a high probability that you’ll have several catastrophic vehicle failures that will consume time, money and add undue stress in dealing with ongoing problems. Dealing with emergency situations is always orders of magnitude more expensive than regular maintenance.

    To me, that’s the issue.

    So, while you’re focused on building your GIS, it’s easy to get caught up in the technology and forget about the economics behind it. Someone is paying the bills and those folks need to understand the benefits of maintaining an up-to-date GIS if you expect them to continue to provide funding.

    Thanks and see you next week.

  • ESRI Con: LizardTech Unveils MrSID Compression for Raw LiDAR Data

    LizardTech’s LiDAR Compressor can convert cloud data into MrSID files that retain 100 percent of the original raw data at just 25 percent of the file size, according to the company.

    Derivatives can be extracted repeatedly from LiDAR files compressed to MrSID, LizardTech said. It can also reportedly reduce LiDAR file sizes by up 90 percent with no perceptible loss. The company introduced the LiDAR Compressor at the 2009 ESRI International User Conference in San Diego this week.

    LizardTech also unveiled an improved version of the MrSID format called MrSID Generation 4 (MG4). MG4 MrSID files support the compression of LiDAR data, which will allow users to view and access their LiDAR data faster, LizardTech said.

    LizardTech LiDAR Compressor is available for purchase now directly from LizardTech’s website or by contacting one of LizardTech’s sales representatives.

  • Duty, Honor, Country — and GIS

    The U.S. Military Academy at West Point was born of unique geography; more than 200 years later, it’s teaching modern mapping methods.

    By Art Kalinksi, GISP

    Last week, I had the privilege of meeting with members of the GIS Program of the U.S. Military Academy at West Point. The security guards at the gate greet visitors with the academy motto, “Duty, Honor, Country,” which permeates all endeavors at West Point. The Academy has produced distinguished graduates for more than 200 years, and is known for its extremely rigorous academic and military training program. The cadets may get a free education, but it requires dedication and a full-time commitment, as well as eight years of service as a commissioned Army officer upon graduation.

    The oldest engineering school and military academy in the United States got its start during the Revolutionary War, thanks to the unique geography of West Point. General George Washington was concerned that the Hudson River could provide dangerously easy access to areas north of New York and New Jersey, where the British could group to split the colonies. However, a narrowing and S-curve in the Hudson at West Point made British ships vulnerable, forcing them to drop their sails as they slowly maneuvered the tight passage. Thus were born the fortifications at West Point, and ultimately, the U.S. Military Academy.

    Today, West Point relies on GIS, which is focused in two Academy organizations: the Geospatial Information Science Program within the Department of Geography and Environmental Engineering, and the Geospatial and Environmental Services Division within the Department of Housing and Public Works. The operational GIS division is headed up by Kris Brown working through Essex, a Northrop Grumman business unit. Kris and his staff support significant public works projects, security, and emergency services. They also provide support for the military training ranges, as well as environmental and archeological efforts.

    Tools and Training

    The primary software environments used at the Academy include Autodesk CAD software and the ESRI suite of GIS applications. Pictometry oblique imagery and software seem to be the dominant choice for public works estimators, base police, and firefighters. The police frequently use of the oblique imagery for incident reporting, but only as simple annotated images. They don’t yet use the heads-up digitizing and shapefile creation ability, but are content to provide that information to the GIS staff for inclusion in the database.

    The Geospatial Information Science Program uses many of the same GIS resources, but for a different goal — the education and training of Army officers and future leaders. The program is led by Dr. John Brockhaus, and includes Colonels Michael Hendricks and Steven Fleming, both of whom have earned their PhDs and have extensive field experience. In addition, the program includes three rotating military faculty members with master’s degrees, and this year includes Michael Tischler, who is on loan from the Army’s Topographic Engineering Center (TEC, recently renamed the Army Geospatial Center [AGC]). Michael also has an extensive education and strong hands-on experience.

    All Academy attendees are exposed to GIS, but based on their major, some cadets expand their GIS education. Students learn GIS theory, but also have to complete hands-on projects that demonstrate their ability to accomplish tasks with the data and software. The program includes the traditional vector-based GIS of points, lines, and polygons, as well as grid/raster-based GIS with work in projections, topology, geodatabases, DEMs, LIDAR, and other topics. Since almost all graduates will be producers or consumers of intelligence products, there is a heavy emphasis on integration of remote sensing, CIR, radar, and imagery, both ortho and oblique. Although computer-based GIS forms the core of the program, cadets must also demonstrate the ability to use traditional paper maps, and even a compass.

    The West Point GIS Lab.
    The West Point GIS Lab.

    The program includes training in GIS software and applications from vendors such as ESRI, ERDAS, TerraGo, Pictometry, LizardTech, Trimble, Google, Microsoft, Oracle, Adobe, and many others. In addition, training in cartography and the use of experimental equipment is offered, including 360-degree video capture systems, LIDAR point cloud analysis systems, and integrative survey collection tools and techniques (such as ike-504 and NOMAD).

    Efficiency in Education

    To be selected for West Point, a cadet must be among the top one percent in terms of academics, drive, and motivation. But the clock and calendar are the real limiting factors of the program. Not only do cadets carry a very heavy academic load, they also have extensive military, sports, and leadership duties. The program is so tight that almost every hour is planned, with each minute important and accounted for. The bottom line is that no one can afford to waste time. Even the dining hall is an example of efficiency; 4,400 cadets are fed during one 30-minute seating.

    This highly disciplined use of time is apparent in the classroom as well. I sat in on a class Colonel Hendricks was teaching — what an eye-opener! In just one class, he covered three topics normally covered in three or more sessions at other schools: Boolean logic related to intersections, joins, and unions; SQL database selections; and grid cell input/output layer selections (map algebra). Covering this much material in one class is a challenge, but the handouts and the clear progression of the classroom session showed a thoroughness and forethought that I have rarely seen.

    Led by Colonel Hendricks, cadets learn about the details of GIS operations.
    Led by Colonel Hendricks, cadets learn about the details of GIS operations.

    Most of us have suffered through classes taught by inexperienced graduate assistants, and many PhD college professors, although knowledgeable, are not very good instructors. That’s not good enough for the tight timelines at West Point — delivery of clear and concise classes that maximize learning is mandatory. It was evident that a lot of planning and thought went into each aspect of this robust GIS program.

    Colonel Fleming explained unique training elements that are part of the West Point curriculum, but not found in typical GIS programs. They include exposure to services and resources available to the military from sources like NGA, USGS, ACE, TEC (AGC), including tools such as GeoPDFs, BAE Systems’ SOCET SET, and others.

    GIS Enables Future Combat Systems

    The Army has always relied heavily on maps, and that has not changed. What has changed is the form those maps are taking, and the speed of communication needed to coordinate modern operations. So where is all this heading? Future Combat Systems (FCS). (For those of you unfamiliar with FCS, there are several compelling YouTube videos that show the concept; search for the phrase “FCS Vanguards.”)

    The impact of FCS is apparent in the curriculum. Just as the Navy moved to Aegis systems that link every ship, aircraft, sensor, and weapons system into an integrated fighting machine, the Army is making each piece of battlefield equipment — and every soldier — a data collector and data user. FCS ties everything together, and GIS is the spatial data integration environment. For you old Star Trek fans, think of the Borg. The big difference is that although cadets are taught to work as well-coordinated teams, they are also taught to think for themselves and show leadership.

    For more than two centuries, West Point has trained our military leaders. During that time, mapping and other technologies have changed significantly, and they continue to evolve rapidly. What hasn’t changed is the West Point commitment to excellence, and to “Duty, Honor, Country.”

     

  • Voxels: Not Your Daddy’s GIS

    Can statistics and GIS build a more accurate geospatial picture?

    By Art Kalinski, GISP

    I’m a little late with this month’s column, but it was for a good reason: I had the responsibility (and honor) of swearing in my daughter at her Navy Officer Candidate School graduation in Newport, Rhode Island. It was a bizarre feeling seeing her stand on the same drill deck where I stood 37 years ago.

    Seeing all those fine young men and women at the ceremony reminded me what a privilege it was to serve. I may not have thought so at the time, but now, years later, I know it was. Since you won’t hear it enough, to all of you who are or were on active duty: Thank you for serving your country.

    Of course, there are other ways to serve as well, such as creating technologies that can support our first responders and military personnel. A few months ago, I learned about one that was new to me: voxels. With computers growing in power and speed, and richer, more complex datasets being developed, it will surely become more commonplace.

    The term “voxel” grew from the words “volumetric” and “pixel”; it describes resolution in volumetric 3D space, not camera or flat-screen resolution. Think of it as the difference between a checkerboard and the construction toy Legos. Voxels are spatial data structures that not only describe 3D space, but can also display statistically fuzzy data.

    3D Models: Simulation vs. Reality

    For those of you not familiar with voxels, let’s start with GRID or Spatial Analyst, which is a grid cell-based GIS. (If you need a refresher, see my column in the June 2008 edition of GeoIntelligence Insider.) Spatial Analyst is similar to a checkerboard: a 2D space consisting of square cells with values defined in the cells by the checkers. You can even show 3D-like effects by raising or extruding each cell based on elevation data, and then draping an ortho image over the resultant surface.

    People call this 3D, but it really isn’t; no matter which way you look at the model, the draped image is still a 2D photo. The other limitation is that, for the most part, all the elevation starts from a theoretical ground plane. There is no easy way to show holes in the space such as overhanging cliffs, caves, bridge underpasses, etc. (Yes, I know there are ways to get around this limitation, but not elegantly.)

    There have been efforts to create 3D models of buildings using ortho imagery by extruding the buildings from their footprints, but since the side views of the buildings are limited, the quality is poor and limited to one side, if any. This is where geo-referenced oblique imagery has benefited 3D model creation. Since the geo-referenced oblique images show each side of a building in very high resolution and contain the data needed to automatically generate the 3D wireframes, the resultant models are very easy to create and are not only photo-realistic, but photo-accurate.

    Although the application is still in its infancy, 3D models are also where voxels show the greatest potential. Since each volumetric cell is a 3D object in 3D space, complex 3D objects are easy to define. Just like the Legos example, you can build almost any 3D object with voxels. But Legos are solid little cubes, whose presence and location are not ambiguous; they can be there, or not there, period. They are never “maybe there” or fuzzy in their location.

    Voxels have another key benefit: they can be statistically defined. By that I mean that each voxel can display the probability that it exists. If you have data that clearly defines a particular area, that region will have a very solid and unambiguous appearance. But if the data is missing, weak, or sparse, the area will appear porous instead. This is where the human observer’s mind can — and does — fill in the voids. The observer automatically understands that there is incomplete data in those places.

    Building Body Models

    Voxels have been around for a while in the video gaming industry, for the very reason that caves and overhangs can be displayed. Their most serious use, however, has been in building the images created from MRI (magnetic resonance imaging). There they have been a boon to physicians, who can manipulate the 3D images, viewing them from any direction. Additionally, each voxel can have varying degrees of transparency, aiding the physician in comprehending the objects he or she is reviewing.

    This is an ideal environment for voxels, since the MRI scan creates very complete datasets to populate the voxel space. Each MRI scan, like the one shown at left, is a 2D “slice” of the 3D object. Assembling all the slices creates an almost perfect 3D model.

    Image courtesy of Lockheed Martin.
    Image courtesy of Lockheed Martin.

    Voxels and Imagery

    There are many more ways of building 3D models that are not as easy as assembling finite, regular slices of a 3D object, and this is where things get complicated and messy. Kirk Smedley and Mark Pritt of Lockheed Martin are leading a team of researchers exploring ways to apply voxel technology to transform the traditional “TCPED” imagery chain. (For more information on this subject, you can contact Smedley at [email protected].) TCPED (short for tasking, collection, processing, exploitation, and dissemination) is shorthand for the well-established life cycle of imagery, from capture all the way to desktop application.

    Lockheed’s work is based on the groundbreaking research of Dr. Joseph Mundy at Brown University, who continues to work very closely with Lockheed. The Lockheed/Brown team is performing some very sophisticated investigations into 3D voxel model creation using multiple imagery and data sources. None are as clean as the regular slices of an MRI, but instead are statistical products that generate probability distributions. Think principal component analysis, factor analysis, and Eigen value decomposition.

    Yes, it hurts my brain to even think about those long-forgotten statistical methods, but for the brave few who are comfortable in those environments, the voxel is ideal — it can display very complex and imperfect data sets. Not only complex in size, shape, and location, but complex as temporal values and abstract probability distributions.

    This ability to display incomplete or imperfect data accurately in a 3D model is important to Lockheed’s clients. There are many video games or training simulators that provide photo-realistic environments; much of the imagery they use is simulated by cloning or modifying textures or images from real life. However, this technique is unacceptable for use by mission planners or first responders in combat or tactical situations. With lives at stake, they need to know exactly what they will face. The 3D model has to show true reality, and display unknown areas as “unknown” or “no data.” For example, in the 3D models that are created by Pictometry and PLW, if there is no satisfactory imagery available for part of a building, that part is shown as a plain, black surface. One can’t add in a fake window or door that has no counterpart in the real world. It’s much better to show the unknown as such.

    Voxels are especially well suited to show fuzziness or incomplete data not just as black, no-data representations, but as probability displays that can show fuzzy data as incomplete or semi-transparent voxels.

    The varying transparency of voxels can indicate the relative completeness of data.
    The varying transparency of voxels can indicate the relative completeness of data. Image courtesy of Lockheed Martin.

    Voxels are also ideally suited to create temporal models (which some prefer to call 4D models). Here again, the ability of voxels to display data as probability distributions is even more important for temporal data, which may be fuzzy in some locations and vary in fuzziness over time. Researchers are now looking at the possibility of populating voxel space with multiple images (ground stills, oblique aerial images, video, LIDAR, interior stills, CAD, GIS) in a kind of 3D statistical summary version of Microsoft PhotoSynth.

    We may eventually see a seamless environment, inside and out, with accurately represented data that was statistically assembled. This is not your father’s “points, lines, and polygons” GIS. Are you imagining the potential for the GIS community? I see this as yet another example of the CAD, GIS, imagery, and BIM worlds coming together for the benefit of first responders and the military.