The lines between imagery, image processing and GIS continue to blur. Esri has been working on several technologies that take advantage of cloud computing, integrate image processing and automate much of the tedious work of the past. Earth Imaging Journal Editorial Director Matt Ball spoke with Jack Dangermond, founder and president of Esri, about the company's many recent and soon-to-be-released offerings. The conversation ranged from the uptake of Story Maps and a new type of geo-journalism, the meaning of smart maps, easing field data collection with apps and the explosion of imagery.
EIJ: The concept and proliferation of Story Maps has really caught on. Are you excited to see what users are doing, and how has the idea of a Story Map evolved?
Dangermond: It is exploding. Our users are creating thousands of them to tell their stories and communicate more effectively. In conversations with Jim Fallows, correspondent for The Atlantic Monthly, he believes this is a birthing of a new type of geo-journalism. It's really bringing maps and journalism together. The volume of this growth is enormous, with millions of maps being served or viewed each day. These are not just U.S.-centric; they're coming in from around the world.
Technically speaking, Story Maps require a strong platform with basemaps for publishing a series of templates (map journal, tours, etc.) that users can easily configure, and the creativity of our users. The templates are the work of Allen Carroll, who was formerly chief cartographer at National Geographic. Allen believes (as do I) that there are going to be orders of magnitude more stories and story maps in a year's time.
I'm very excited about this. It's all driven by the intellectual thinking and background of Allen Carroll. Clearly his vision is creating this new geo-journalism medium.
EIJ: The term smart mapping or smart map is emerging. What is a smart map, and how does that differ from digital maps or Story Maps?
Dangermond: Smart mapping is a new interactive experience for creating quantitative maps. It makes the creation of very high quality mapping easy and fun. It fundamentally takes a type of expert system approach for looking at your data and making suggestions for how best to represent it. Users can interact with the legend of an automatically generated map to explore the data and create multiple representations. It supports large volumes of data and supports the whole concept of spatial data exploration. Users can dynamically change the ranges of classes and see the map change in front of their eyes. They can also can move sliders around to change thresholds and tell stories or understand anomalies within their data. It's a whole new type of Web mapping.
If you go back in the history of GIS-based mapping, it went through several stages. First we used computers to create a map that could be printed or plotted out. Then with the creation of graphic terminals, we used computers and databases to display a map on a screen. As our tools improved, we were able to get better at creating high-quality maps such as Rand McNally Road Atlas or National Geographic basemaps.
The next stage was to put the map on the Web. In 1997, with ArcIMS, we were able to produce GIS-based Web maps, and while they were not very good quality, users could dynamically present data, interact with the maps, and pan and zoom around. The next generation was the multi-scaled tiled Web map that provided continuous so-called slippy maps that are now a standard in consumer and professional Web platforms, including ArcGIS.
Smart maps represent the next stage. This is a big jump and allows users to dynamically create and interact with data, visualizing and exploring data in real time.
The smart map will be the pattern that supports the next generation of GIS on the Web, integrating with big data and others. It promises to equip the user with tools that are not simply about making a map, but about dynamically analyzing and visualizing data geospatially. It supports the whole notion of data science.
EIJ: Mapping on the Web has come a long way. What underpins this latest evolution?
Dangermond: A couple years ago, Esri introduced the concept of a Web GIS, which is a whole new type of GIS. It isn't a client-server GIS, although a client-server GIS can plug into it. It's a different architecture. The Web GIS doesn't have a database at the center; it has a geo-information model, which is a set of Representational State Transfer (REST) endpoints that point at databases or real-time information. The geo-information model is three things: Web maps, Web scenes and Web layers. They don't really exist as data; they're just pointers back to databases, geodatabases, tabular data, imagery data and sensor networks. The data is represented dynamically on a map at the time it's requested.
Esri has figured out how to represent all types of geospatial data in the geo-information model with these three types. This underpinning is making GIS easy to use, because these Web maps are simple and easy to understand. I can e-mail a Web map. I can put one inside an app. People can do things such as spatial analysis by combining these objects. Web GIS dramatically simplifies GIS.
ArcGIS Online is a quintessential example of a Web GIS. However, our users can also implement a Web GIS on premise themselves, because last year, at ArcGIS 10.3, Esri released the Portal for ArcGIS with every Server. Portal can be thought of as all the technology necessary to implement ArcGIS Online on premise. It manages Web maps, Web scenes and Web layers, and comes with a library of apps that allows users to work within Web GIS.
EIJ: I've recently seen the Collector field data collection tool that greatly simplifies workflows and is available on any device. That feels like a parallel revolution in terms of populating these new types of maps.
Dangermond: Collector is an app, just like Story Maps are apps that work on top of Web GIS. A Web GIS has Web maps and apps. These apps are device apps or Web apps or desktop apps like ArcGIS Pro. Collector is one of these apps; another one is the Dashboard.
Collector is being used for many different field data collection projects such as collecting data about trees in Washington, D.C.; fire hydrants in Hong Kong; and for several different disease outbreaks. When you collect the data, it immediately sends the data to the Web GIS, such as ArcGIS Online or ArcGIS on premise with Portal. You can then view that data using the Dashboard, which is just another app.
The big revolution that's occurring is a whole family of these apps: navigator apps, analytic apps, viewing apps. ArcGIS Pro is a thick app released this winter, and that's a whole transformation of desktop GIS. ArcMap continues, but ArcGIS Pro is a new version of ArcMap. It doesn't do everything that ArcMap does yet, but it's not only a desktop app, it's a Web app. It lives on top of this ecosystem of Web maps, Web scenes and Web layers.
EIJ: Your investment in the cloud has been impressive. Not just your move toward this hosted environment, but also the provisioning you've done with investments in data. Is the cloud going to continue to be the means that people use your software?
Dangermond: Cloud infrastructure doesn't replace on-premise infrastructure in many cases. Organizations still want to have their own servers and desktops; that will continue for a long time.
What's starting to happen in our community now is that people are sometimes standing up their server in the cloud instead of on premise. Also, users are increasingly integrating their existing on-premise systems (desktop and server) into the ArcGIS Online cloud environment. A second trend is that people are using applications such as Collector and Dashboard on any device to access their data on the cloud. Desktops are also using these cloud services, such as with ArcGIS Pro that was engineered so you can have it run efficiently in what's called a Desktop as a Service (DAAS) in the cloud. Instead of a thick desktop computer, you can have your desktop GIS completely virtualized in the cloud and accessed through browsers.
The cloud offers very cheap map serving. If a user owns an ArcGIS desktop license, they are entitled to a subscription of ArcGIS Online as part of their maintenance. So if they make a beautiful map on their desktop, they can send it over to the ArcGIS Online cloud and create a map service. Instead of setting up their own server just for map serving, they can simply send maps over to ArcGIS Online, and it will serve it out without cost, and you can host an unlimited number of maps.
EIJ: One area I wanted to be certain to touch on is the explosion of imagery from new and different platforms such as smallsat constellations and unmanned aircraft systems (UASs). What does this new level of imagery data mean for GIS users?
Dangermond: During the last few years, we've been systematically incorporating image-management and image-processing capabilities into ArcGIS. At 10.3, it has as much or more image-processing functionality as any standalone image-processing desktop system. For the image community, that's really important. They can buy an ArcGIS desktop and get a full image-processing system that can do mosaics, color balance, classification, segmentation, visualization and turn out orthophotos as well as any other desktop image-processing system.
What is interesting, of course, is that all this image and remote-sensing power has integrated with all the rich GIS power. Traditionally, image processing and GIS were separate types of technology. With 10.3, we've merged these technology worlds into a single desktop and a single server. Users like that, because they don't have to learn two different types of tools or methods.
They can mix the data together in a common toolset (multispectral, raster and vector data) and do analysis that simply wasn't possible with an imagery-only focus. GIS vector data can enrich the remote-sensing and image-processing world; likewise, imagery and remote-sensing data can enrich a GIS.
Said a different way, a modern GIS has to have a full image-processing environment integrated in it. A modern image-processing environment has to have the rich power of a GIS inside it. We have accomplished that.
One of the biggest and most-exciting aspects of our field today, in terms of imagery, is drones. This fall, we are releasing the ability to connect to inexpensive drones and make the data they collect come alive with information integration such as full-motion video. We are developing capabilities to digitize off of full-motion video, do feature collects and directly update your GIS.
As drones get licensed to fly here in the United States, we imagine more local governments and police departments are all going to buy them. They will want to take their imagery feeds and will want to plug them into something where they can be valuable. Not just visualizing the data, but bringing it into the mission-critical GISs that people want to use.
EIJ: I've been absorbing our discussion, and some themes that keep coming back are simplification and automation. Is this going to continue to bring down the barriers and allow individuals to do more interesting things with maps?
Dangermond: Smart maps do a lot for you, and that's going to appeal to two communities. For those who don't know cartography at all, it starts them off with automatically generated maps. It basically looks at your data carefully and makes choices for how best to represent it. For more-advanced users, it starts them off with a high-quality map and lets them take over and add value with their own logic and design skills. It appeals to both of those communities. We're using more of the computer to do more of the thinking, so things will continue to be more automated.
We're announcing several new products at the Esri User Conference this summer. One of them is called the GeoAnalytics Server for dealing with very large datasets of three types. It will allow users to analyze tens of thousands of images very quickly in a Big Data environment, using scalable processor architecture (SPARC) and other technologies. It will also deal with very large collections of real-time data and the analysis of tens of thousands of observations per second”allowing users to analyze them, parse them, visualize them and store them for subsequent analysis. Finally, it will also handle very large amounts of point information, and perform spatial analytics to give greater insight. This server environment depends very much on automation and being able to parallelize data processing in the architecture.
The second new product, which will be announced at the GEOINT Conference, is ArcGIS Earth, which is similar in user experience and technical footprint to the Google Earth visualization tool. It will use ArcGIS Web maps and services as well as support dynamically being able to drag and drop KML files. This product is part of our work for supporting Google users in their migration into ArcGIS, but it will also be a whole new visualization environment for our users.
All of these innovations belong to a single integrated architecture. This is interesting, because each new capability is synergistic and enhances the whole platform. The GeoAnalytic Server, new imagery capability, the simplification of data by way of Web maps, Web scenes and Web layers; all of these new apps mean huge amplification of capabilities for our users. Instead of having to build everything yourself, the future is to allow users to configure their GIS and leverage automated technologies.
At the same time, it is important to say that Web GIS architecture isn't a replacement for what we have now, it's an addition that integrates traditional GIS and makes it available to a much larger audience.
