by Ian Fichtenbaum, Near Earth LLC

On February 2nd, 2009, Google did something that made its users see red. This reaction was neither the embarrassed states of its many corporate rivals, nor the rage of information privacy advocates, but instead the result of a new release of one of Google’s most popular and acclaimed pieces of software, Google Earth. Tucked away in this shiny new version was a new feature sure to delight fans of planetary science and imagery ­­— at last, users had the option of viewing the planet Earth as well as the red planet, Mars. Through the imagery of NASA’s Mars exploration fleet and the prowess of Google’s image processing and geospatial capabilities, astronomical aficionados can explore the ridges and valleys of the red planet’s surface with as much ease as they can now spy on the layout of their own home town. Mountains of imagery that often languished in large NASA databases have now become more accessible to a much larger audience. Returning back to Earth, it bears mentioning that so much has happened in how we use public and commercial satellite imagery that we ought to take a step back and see how far we’ve come and how fast.

Only just a little more than a decade ago, not only did Google Earth not exist— nor did almost the entire commercial satellite imaging market. IKONOS, the first high-resolution commercial imaging satellite, would not be launched until late 1999 and other satellites years afterwards. Mountains of data from government-operated imaging satellites did indeed exist (as they still very much exist today) but, just like the Mars data, they existed in an obtuse format useful sometimes to experts but inaccessible to the vast majority of the public. Even when comprehensive imagery servers, such as the famed Microsoft TerraServer, came online in 1998, common users would still need considerable agility before they could even exclaim “I can see my house from here!”

Underlining this is a fundamental problem with satellite imaging and remote sensing. Human ingenuity has been exceedingly good at building machines that churn out petabytes for megabucks, but it has done a patch poor job of making the data actually useful to people when they need it — that is, channeling information from photons to electrons to neurons exactly when those very same neurons need it most. It is here that image collecting meets its match and more sophisticated analysis comes into play. Over the last couple of decades, a very healthy industry has arisen to fill this need for geospatial analysis by bringing to bear processing techniques and interpretation algorithms to weave a fabric of knowledge from the wool of information. To some, this industry is known as geomatics, the gathering, storing, processing, and delivery of geographic information, or spatially referenced information.

We can go farther — take geospatial imaging and add the wonders of GPS-based navigation, a telecommunications network, databases of transport networks, routing algorithms and some simple machine intelligence and now we have the fast growing multi-billion dollar industry of asset tracking and GPS navigation. This, too, has a name — many call it telematics.

Truth be told, both geomatics and telematics should not be thought of as two separate disciplines but rather as subsets of informatics — the analysis of information in general. Information about place, position, and time are just a few different kinds of information that can be brought together to bring forth greater understanding of the world. To these we can effortlessly add demographic, cultural, medical, conversational, culinary, legal, horticultural, ethical, mathematical, conceptual, and many, many more forms of information. Under the correct circumstance, all of these strands can be combined together into something that can tell us more than the sum of its parts.

All of which brings us all the way back to Google Earth and its cousin, Google Maps. The real trailblazing part of the software and the service was not merely the accessible presentation of geography, but the open software architecture which allowed anyone to cross-reference map data against any other readily available data. Hence, the phenomenon of the so-called mash-up: user-created real-estate maps drawn from classified listings, or charts of crime incidents drawn from police reports, or many other similar creations. Informatics in the modern world not only means that all the aforementioned information sources will end getting mashed together, but will do so as a direct consequence of user demand.

What will this mean for the business of information? First, as demand grows, expect to see raw data (i.e., raw images and unprocessed databases) becoming more commoditized and for margins to shrink. Conversely, players on the right hand side of the value chain, those who specialize in processing, mashing and interpreting data for geomatics, telematics, and informatics will boast heftier margins, but in a fragmented field. Commodity data providers will eventually find themselves either seeking greater scale along the horizontal (a satellite image company moving into other sources of images, such as aerial imagery) or expanding into informatics services themselves either through organic growth or by acquisition. Corporate strategists, however, should take note — if we’ve learned anything about the mash-ability of data, it’s that the sophisticated end-product of today will eventually become a commodity data-point for another mashable tomorrow. The value chain is always moving to the right and they must be ready to move with it.

Perhaps the greatest opportunities exist for those who can build platforms for information that become the most widely accepted. Google’s greatest success has been in becoming a de facto standard for serving up and organizing the world’s information. History shows that to have such a position is always an enviable one. As Jerry Seinfeld’s neighbor, the hapless mailman Newman, wisely put it “When you control the mail, you control … information”. If this is indeed the case, then one hopes that Google will use its dominant position in the marketplace more responsibly than Newman was often depicted. If not, its users will, no doubt, find more than a few reasons to see red.

About the author
Mr. Fichtenbaum is an Associate for Near Earth LLC. Hailing from Canada, he is a graduate of the Master of Management program at the University of British Columbia as well as a Bachelors of Engineering at McGill University. Since graduation, Ian has built a variety of business experience in both the satellite and financial worlds, having worked at the financial firm, Divine Capital Markets, and advised the Montreal-based small satellite startup, CANEUS NPS. He also worked at UBC’s Center for Operations Excellence, providing quantitative analysis and decision support tools to industry clients. He is fascinated about the intersection of business, finance and advanced telecom and aerospace technologies and the ties between these fields In addition to his undergraduate and graduate studies, Mr. Fichtenbaum is also a proud alumnus of the International Space University.