How do you make a geospatial exchange a reality? You find great content providers to bring their wares to the market. Aerials Express (AEX) is one of those great content providers. With 420,000 square miles of high resolution aerial imagery over major metropolitan areas in the US (see map below), AEX brings base map content to “prime-the-pump” in the derivative product marketplace.

Christopher Warren and Bill Landis at AEX have been great. Their listings of AEX products address a big niche in our industry. High resolution imagery that can be physically acquired and manipulated with an explicit license to resell derivative works. Bill’s quote from the Press Release -

WeoGeo is an excellent opportunity for our company, said Bill Landis, President of Aerials Express. We are looking to WeoGeo’s advanced technology and unique distribution model to enhance the availability of our products into a wider range of GIS related markets.

It says a lot about the potential of an exchange-based market for our industry.

We will do our absolute best to make the market technology easy to use for search, discovery, and product acquisition. Its success will increase productivity and margins for all of its participants. Today, we mark its beginning.

I am writing this in Seattle as we prepare for the finals of the Amazon Start-Up Challenge. We are truly excited to be a part of this Challenge. It is an amazing opportunity to be recognized for our technology and business model.

I am in love with our technology and how easy it makes it for all players, large and small, to participate in a global mapping market based on the quality of their skills and geo-content. WeoGeo will make it easy for all of us in the geospatial field to do our jobs, while at the same time increase our operating margins and productivity.

A really exciting part of this Challenge is that our business model is also being recognized by an internet service company with a $39 billion market capitalization. Everyone in our field has seen the explosion of interest in geospatial over the last few years. One only has to look at the >200 million downloads of Google Earth, as well as the consolidation by Tele Atlas and NavTeq to know that our industry is moving mainstream. This is excellent new for all of us, for it will provide more resources and revenues for our field, which translates into better opportunities for us all.

Come see the videos of the finalists in this Challenge and vote for your favorite (preferably WeoGeo!). But make sure you see our video. I hope the passion for what we are trying to accomplish is evident. I also hope that you will find what we are attempting to accomplish as exciting as we do.

Big thanks to Adena Schutzberg at All Points Blog and James Fee at Spatially Adjusted for helping us rock the vote!

The only thing I can say is, “Wow!” Followed by the biggest grin you have ever seen on my face. As one of 7 finalists, Amazon expresses their confidence in our technology and business strategy. In all honesty, I am humbled and honored by the selection, and truly thank them for their selection of us as one of the 7 finalists.

I believe (passionately) in what we are trying to create. I believe that WeoGeo will change the paradigm in how we discover and access geo-content. I believe that we (the geospatial industry) as a community will more easily synthesize new mapping products that will help us create a better world. But these are my beliefs, and I tend to view everything we do through these rose colored glasses.

The selection as a finalist by Amazon Web Services (AWS) means that someone else out there sees the same potential for the mapping and geo-content industry as we do. It provides validation for the people who have worked so hard on this project beyond anything that I could offer, and for this I am eternally grateful.

In addition, Amazon will offer the winner of this contest a venture investment. I believe this says a lot about the geospatial industry, as well as WeoGeo. For WeoGeo to be among those considered a suitable investment opportunity by a $32 billion dollar company, we must have (1) a great business plan, (2) a great set of technology, and (3) be in an industry with high growth potential. Our industry, the geospatial industry, is now recognized by a leader in internet services industry as having high growth potential.

I’ve been grinning so much, my face hurts…

WeoGeo has created a scalable, fault-tolerant infrastructure to manage its use of Amazon Web Services Elastic Compute Cloud (EC2) operations. I’ve written about it a couple of times (see this link for a listing of the Amazon tagged blogs). The latest version of WeoCEO (Version 0.1.0) is ready for release and with it we are moving from private to public Beta.

This version includes the Assistant to back up WeoCEO (see this feature described in this Amazon Web Services StartUp Event Slide Show). WeoCEO Version 0.1.0 also provides enhancements to the stable IP addressing, failure detection, and automatic scaling and load balancing. These enhancements include automatic emailing to your site administrator during trouble events and detailed logging capabilities.

WeoCEO Version 0.1.0 (including the load-balancing and auto-scaling capabilities) will be free of charge at least until December 1, 2007. It will continue to be free if you only use the stable IP addressing and auto-recovery features for a single client instance.

There will be a charge for the load-balancing and auto-scaling features of WeoCEO, which support running multiple EC2 instances and optimizing your network. The charge for these features will be $0.05 per managed client instance per hour. The charge will be on the average usage over an hour, calculated at <15 minute intervals.

You can obtain a WeoCEO ISO with the setup and installation instructions, by visiting http://www.WeoCEO.com and clicking the “Signup” button, or by clicking the Signup button below. We are still in beta, so constructive comments on any of the components that make up this service will be met with exuberance and free goodies.

I have had a number of questions from our private beta Providers that basically ask, “What maps should I be making?” To be honest, I wish I knew. In reality, WeoGeo Market was established to answer this very question.

We set up WeoGeo to lower the risks of creating and selling mapping products (most importantly by reducing marketing and transaction costs). We believe that by lowering the risk of creating and selling geo-content, more products could be created at lower prices. By combining more products at lower prices with a greater ability to find and customize those products, Users of those products would be more apt to purchase more geo-content. The overall goal is to create a truly functioning marketplace for geo-content. The end result would be a collective intelligence expressed through the market that would help all of us focus on making the most valuable geospatial products.

Answering the question of what product to create is one of the hardest parts of running FERI’s operations. While FERI is a research and development organization, we still had to perform the basic sales and marketing efforts of finding paying customers to support our development of value-added mapping products. It is a very time consuming and difficult process, requiring a lot of telephone calls and a lot of travel to search out programs that would value our imaging and mapping efforts. Such is the nature of sales and marketing, and every good salesman would tell you that is just the way you have to generate business.

However, as a scientist I want to focus on the generation of new mapping products. While I could (and still do) focus on sales and marketing, my real interest is in generating new mapping products that could help people make decisions with their resources or help save lives. With the hyperspectral imagery, we could develop maps focused on a variety of topics. These maps could range from Harmful Algal Blooms (HABs or more commonly called red tides) to Submerged Aquatic Vegetation (SAV) to detecting probable locations of Improvised Explosive Devices (IEDs). Yet, finding sufficient demand for these products to overcome the high initial production cost of creating these products is difficult. (I have a whole other story on the IEDs and how the DoD does business with contractors and appropriation earmarks that I’ll save for another time.)

Over the years, we have watched with great interest how the internet has impacted other businesses. One of the most interesting impacts that we have seen is the rise of shared intelligence from the accumulation of individual choices. For example, search engines have used the individual linkages of web page creators to develop a collective intelligence estimate of the most likely desired result for a search term (and a new industry of search engine optimization). In particular, we were fascinated by eBay’s ability to enable millions of people to develop larger markets for their niche products.

By establishing a functioning marketplace for these niche goods, eBay created liquidity and demand for products that previously had limited marketability. In the process of creating a market whose niches could be efficiently filled, they also provided opportunities for entrepreneurs to develop new markets. In effect, eBay created a platform that enabled individuals to make choices, create products, and satisfy the needs of others, which in turn created a positive feedback mechanism for everyone who participated. This led to the creation of whole businesses that did not exist prior to eBay, and the rise of the valuation of goods that previously had limited market enetration, and thus, underdetermined recognized value.

The increased liquidity of products and the collective actions of many individuals led to a self-sustaining marketplace that enriches all of the participants. eBay is a lesson in economic theory, and gives truth to the concept that “a rising tide lifts all boats.”

So what does this have to do with answering the question from our Providers about which maps to produce? The answer to that question is that I am not sure, but I can make sure that the Provider’s risk is low enough for them to make some reasonable choices, and to give them the agility to respond to market demands. Through this process, I believe that our collective intelligence will point Providers in the most profitable direction.

This marketplace will give those with the skills and those with the content the ability to connect as never before possible. The new network of connections will lead to the creation of new geo-content that will enhance and enrich the lives of our community. And our community will profit from it because we will know which maps to make.

With the Open Geospatial Consortium (OGC) planning adoption of KML as a standard, we’ve focused our efforts in its support on varied platforms. KML’s previous proprietary nature was a cause for concern as Raj Singh aptly describes:

And one crucial point that I think a lot of people miss is the legal intellectual property aspect. Bringing KML into OGC isn’t just about what features end up in that XML format. It’s just as much about making sure the format is royalty-free to use forever.

We use KML as an additional means to help our Users (map consumers) and Providers (map sellers) use the Market. A reduced resolution KML is created for free whenever a dataset is listed by the Provider.

For Providers, a reduced resolution KML button on Panel 4 offers a link to their listing’s KML file. An example of this feature for FERI’s hyperspectral map listing can been seen in the red circle on Figure 1. The link in the red circle provides access to a KML file, which can be used by the Provider as another method to market their map listing through other mapping programs. These links (the one to the listing or the one to the listing’s KML) or the reduced KML itself can be used in any of the provider’s marketing material or blog posts.


Figure 1. WeoGeo Market listing for FERI’s St. Joseph Bay hyperspectral mapping product (click on the image to go the Market listing). The red circle in the bottom left hand corner links to this data product’s reduced resolution KML. The blue circle on the bottom right of Panel 5 is for high resolutions KML products, which are fully tiled and regionized products that the Provider may offer for sale (to be covered in a future post).

For the User, this feature helps them decide whether this map is appropriate for their needs. By viewing the KML in their favorite map viewer, the User can quickly see if this listing intersects with their area of interest or other mapping products. As an example of this feature, here is the KML from the listing in Figure 1 seen in ArcGIS Explorer, World Wind, Google Maps, and Google Earth.

Figure 2. KML listing of FERI’s St. Joseph Bay hyperspectral mapping product offering on WeoGeo Market as seen in ArcGIS Explore v 9.2, build 410. Currently, the KML needs to be saved as a file to your local machine from the link and imported into Explorer. In the balloon is a link directly back to the specific WeoGeo Market listing.

Figure 3. KML listing of FERI’s St. Joseph Bay hyperspectral mapping product offering on WeoGeo Market as seen in Google Maps. In the balloon is a link directly back to the specific WeoGeo Market listing.


Figure 4. KML listing of FERI’s St. Joseph Bay hyperspectral mapping product offering on WeoGeo Market as seen in Google Earth. In the balloon is a link directly back to the specific WeoGeo Market listing.

Figure 5. KML listing of FERI’s St. Joseph Bay hyperspectral mapping product offering on WeoGeo Market as seen in NASA World Wind v 1.4. The KML needs to be saved as a file to your local machine from the link and imported into World Wind.

Adena Schutzberg did a podcast with me last week on the business model for WeoGeo. It was my first podcast and I hope that I made sense to people (I welcome comments and/or critiques in the comments section here). I would like to thank Adena for giving us the opportunity to tell our story.

However, I am not sure I was as clear as I could have been about our history and the importance that history in the development of WeoGeo. I could not quite put my finger on what was missing until after the AWS StartUp Event - Boston (see here as well for my comments) when someone asked how many man-years of effort went into developing the site.

My first response was to take the number of years that FERI was in operation times the number of people involved at FERI. Kind of silly, I know. But when I think of why we built WeoGeo, this response seems relevant. Their response, of course, was, “no really, how much technical development time?” I understood the question; the person was trying to ascertain how difficult it would be to recreate what we are doing.

Our technical development on this project did start back around 2001 with a project called Hyperspectral Data Repository On-line (HyDRO). This was our first distribution system, developed to help alleviate the problems associated in delivering HSI data to our customers. This concept and technology eventually evolved into the WeoGeo Server (see post here as well). Between 2001 and 2005 we had 4 PhDs and masters-trained personal spending a portion of their time on HyDRO because it was a critical element of our research programs. In the last couple of years, we increased the number of people working on WeoGeo Market/Server, to >12 currently if you include outside contractors. For the most part, they are highly trained GIS and MIS/CIS/CS personnel.

The technology is hot, no question about it. I am amazed on a daily basis what our group of people has developed for mapping on both commodity computers and utility computing systems. Yet, here is the rub to this type of man-years calculation. I really believe that the reasons for WeoGeo, and its associated development time, stem from our history at FERI, which makes such calculations difficult. The “technical development time” is not just time spent coding; it includes the needs assessment and the development of the system architecture to address critical problems and/or pain. What we have developed at WeoGeo is a direct function of two critical needs of our operations as a research and imagery services organization.

These two critical needs were (and still are):
1) Delivery of our survey grade, high volume mapping content;
2) Finding and acquiring other survey grade mapping content to fuse with ours to create value-added geocontent for our clients.

WeoGeo was built to solve these two critical problems (there are others, but not nearly as critical to our organization as these). If you have never been faced with these problems, then you might not appreciate the depth of the solutions we have built to service these needs (and its potential). But if you have, then you have felt our pain - and I hope value our solution.

The worldwide spatial information management industry has been estimated at ~$50 billion. While large, the industry is dominated by specialization and niche practices that have reduced the flow of spatial information between location-aware enterprises. This reduction in information flow decreases efficiency and productivity within enterprises, and between industries.

Let us examine the different vertical markets that make up the spatial information industry, including urban planning, emergency response, real estate, natural resource management, environmental protection, agriculture, asset management, construction, advertising, etc. They all use slightly different tactics to acquire their spatial awareness or geospatial intelligence (Figure 1; this figure and the next are from a 2007 Where 2.0 presentation. If you are interested in the full presentation let me know.). However, all of these industries have very similar needs in that they require high quality maps to make fundamental (insert your favorite term here, e.g. business, asset, resource, targeting, etc.) decisions.

Figure 1. Vertical silos in the spatial information business keep the markets small and separated.

If we can break down these vertical silos, such that the maps in one niche were used as raw material into the next niche, we can re-order our geospatial markets to look like Figure 2. Here, the silos become building blocks for higher valued information products, which in turn are used as base products for higher valued geo-enabled processes. These building blocks now increase business process efficiency and productivity for the spatially-aware enterprise. As any process manager will tell you, increasing efficiency and productivity is good, really good, because it means you can do more for less.

Figure 2. Silos are changed into building blocks for higher valued industries, increasing efficiency of productivity and resource management.

A recent article from Geoff Zeiss (who was building upon a 2004 article by Paul Teicholz) used the construction industry as an example of the impact of information silos. He first points out the size of the construction industry, worldwide = $2.3 trillion, US = $1.2 trillion. That’s trillion with a T.

Paul’s article examines a decline in construction productivity, during a period when all other industries were looking at increases in productivity (Figure 3). Paul points to a lack of IT integration and R&D by the building industry as a reason for this real fall in productivity, while all other non-farm industries appear to have used IT to become more productive. Geoff goes farther (and I tend to agree with him) that part of the problem relates to the ‘Islands of Information’ that are created, and not shared, by the various disciplines involved with the construction industry:

Disciplines such as architecture, structural engineering, construction, civil engineering, and GIS are classic information silos. Each maintains its own information island comprised of design applications and data. This has created a nightmare for operations and maintenance, emergency planners and responders, urban planners, and others who require seamless access to urban terrain including building interiors and exteriors, roads and highways, and above ground and underground utilities. The biggest challenge is not typically data, because the data that would help these folks already exists because much of (sic) it is created when buildings and infrastructure were designed. The biggest challenge is that islands of information and technology make it difficult to integrate existing data in a seamless view.

Figure 3. Labor productivity declines 1964-2003. (from ACEbytes Viewpoint #4)

WeoGeo was started to specifically address the creating, sharing, and marketing of geospatial content that will help increase the productivity of spatially-aware industries. We have built an easy to use interface and system to rapidly list, host, discover, customize, and deliver value added geo-intelligence in a way that generates revenue for content providers, which will be affordable for content users. We are using a classic exchange mechanism to create a neomarket to “remake” the silos into “connections” between the islands of geospatial information (I know I am mixing metaphors, but I couldn’t help it. Sorry.)

Does it matter? Are there enough inefficiencies to be found that will translate into dollars to make a difference? Here is another quote from Geoff’s piece:

Several years ago the National Institute of Standards and Technology (NIST) commissioned a study on Interoperability to attempt to quantify the efficiency losses in the U.S. capital facilities industry… NIST estimated that in 2002 poor interoperability cost the US capital facilities industry $15.8 billion.

That leaves some room for improvement in efficiency. And this is just one spatially-aware industry. An increase in productivity in these industries will create a more efficient use of (natural) resources, which over time creates a positive feedback into the quality of operations (and life) for all those using planetary resources.

I posted last week about bandwidth issues associated with geospatial data and our AWS S3 solution. The deciding factor for us to use Amazon’s offerings was not necessarily the edge distribution capabilities of S3, but the synergy from combining S3 data storage and distribution with virtual computing capabilities of EC2. There are multiple issues in image processing that require a ton of memory space and CPU horsepower. In both Market and Server, we offer the following basic map distribution options to our map providers -

Geo Clipping (6 zoom levels, allowing for ~125 million possible selections per data set)
Spatial Resampling (4 levels)
Layer Resampling (depends on data)
Output File types (5 - JPEG, GeoTIFF, ENVI, ESRI BIL, ERDAS IMG)
Projections (5 - UTM, Transverse Mercator, Lambert Conic, Albers Equal, Geographic)
Datums (3 - WGS84, NAD 83, NAD 27)

These options result in millions of possible map variants, which preclude the storage of each variant for distribution. So processing power for conversion is critical; and this processing power needs to be connected to a large, web-addressable, temporary data storage array to house the unique variant that a map user has selected. Now for a true mapping marketplace, this infrastructure needs to support 100s to possibly 1000s of simultaneous map requests from the same base map like the 40 GB image in Figure 1. Doing our NeoMapping Market correctly requires the creation of enormous processing, storage, and bandwidth infrastructure.

Figure 1. 40 GB, 156 layer HyperSpectral Imagery (HSI) map listed on WeoGeo Market. (Click on image to go to the listing in the Market).

However, who could afford that infrastructure upfront? Our original estimates for acquiring base computation needs and placing them into a co-location facility were around $500K. While not a lot of money in the scale of today’s internet operations, it was big for us. In addition, we were trying to develop the software architecture to support the Market and Server, and these expenses were large in it of themselves. AWS provided a unique and simultaneous answer to many of our immediate storage, processing, and distribution needs.

Developing our infrastructure on the scalable AWS solution allows us to say we can support the 1000s of map requests required for a functioning digital marketplace. The user experience is vital to the service’s credibility and therefore our success. However, there is a true (and in a number of cases unexpectedly high) cost in this decision. We traded high capital expenditures for high operating expenditures. In an upcoming post, I’ll talk about the Total Cost of Operations (TCO) on AWS, and some of the ways we are moving to reduce these high operating expenses through stability and scaling solutions. Some of these solutions we have turned into products that we provide to others (e.g WeoCEO)..

I would be interested in hearing about the actual experience of others on AWS and whether S3 and EC2 could or could not meet their needs.

An obvious question that drops out of yesterday’s post on the right file format to use to distribute large raster files is, “How do you distribute a 40 GB file?” The distribution of a single 40 GB file would overwhelm the bandwidth of many small businesses. That was one of the reasons we originally developed the WeoGeo Server.

Figure 1. WeoGeo Server (click on the image to see more information)

The Server allows the mapping organization to distribute customer-defined customized products that would reduce the required file size, and thus bandwidth, to satisfy their customers’ demand. However, there is still the use case where the customer wants the whole file.

Since FERI is a small business, we couldn’t have our daily research activities impacted by an imagery request. So the first (obvious) step was to develop a customization and distribution system that processes a data request in an asynchronous manner, i.e. the order is taken during business hours, but it is processed and delivered after business hours. This allowed us to optimize our bandwidth in our labs and still reasonably satisfy customer demands (assuming they did not need instantaneous data delivery). We also tweaked the system to allow some small files and all of our own requests to be processed immediately, while larger ones for external users were processed in the evenings.

The asynchronous data delivery is also a fundamental difference between our technology and online GIS servers. We optimized for discovery, customization, and ordering in a way that allows the customer to receive near-instant gratification on the discovery and ordering, while (possibly) delaying gratification on the delivery.

While the customization of product selection and the asynchronous processing and delivery bought us some additional help in terms of distributing large geospatial content files, it still did not help us with the problem of what to do with multiple requests for 40 GB image files. This is where some of my earlier posts, where I described our use of Amazon Web Services, begin to make some sense (and maybe why Jinesh digs what we are doing).

However, I am late for dinner, so I’ll pick up this theme on a later post…