With several friends competing at the Beijing games the office has been following the stories about pollution and its possible impact on the games very closely. The best analogy a friend of mine gave after a practice at the rowing venue was “it is like training at altitude”. We thought it might be useful to build a map showing the daily pollution levels in different parts of Beijing on a map that included the Olympic venues.

Raj found a Chinese government source for daily pollution levels in Beijing then geocoded it for us. Andrew used Mapufacture to turn the data into a dynamic geocoded feed, so we could put it on the map and have it updated in real time. Finally Bill used Finder to create a data set with all the Olympic venues. The whole thing came together in a day and we’ve embedded the map below. You can also go to Mapufacture and grab the embed for yourself or the KML and keep track of it in Google Earth or another compliant GeoBrowser.

The icons with the Olympic rings are Olympic venues and the orange squares with the Mandarin character for “atmosphere” are pollution sensors. When you click on the environmental data you’ll see totals for three different pollutants:

1) SO2 – Sulfur Dioxide
2) PM10 – Particulate Matter- that is 10 micrometers in diameter or less
3) NO2 – Nitrogen Dioxide

These three measurement compose the API – the air pollution index. The USA and Canada both use AQI, air quality index, which is similar to API but the indices are set according to different formulas based upon concentration. Therefore, one cannot compare API or AQI between countries without knowing what concentration is represented by the indices.

API Rating (Beijing)

0-50 Grade I (Excellent)

51-100 Grade II (Good)

101-200 Grade III (Lightly Polluted)

201-300 Grade IV (Moderately Polluted)

300+ Grade V (Seriously Polluted)

Interestingly Honk Kong uses the same API index but how they rank between “seriously polluted” and “excellent” is far different.

To keep things honest we used the Honk Kong scale for the map we created. If you would like to do some comparisons (knowing the formulas) of API in Beijing to AQI in other cities you can check out the EPA data set in Finder with AQI for major urban counties in the USA.

*Special thanks to Andrew’s wife Corrie for deciphering the enviro science for us. If you would like to get the PhD. version check out her blog on the topic here.

Popularity: 23% [?]

We are very excited to announce that Mapufacture is joining FortiusOne. What started off as a joke at the bar “we should just combine the companies together to make Geo-Voltron” has quickly turned into reality. We’ve always admired the work Andrew and Mikel have done in the community, and having the opportunity to work with them on a regular basis was one that we could not pass up.

In addition to working with great people we also saw great potential in blending our technologies. Mapufacture has done a phenomenal job pushing open standards on the GeoWeb and making dynamic data available on maps. In many ways they embodied the core of what many have defined as neogeography. At F1 we’ve had a mission of bridging the GeoWeb and GIS, and have invested lots of effort in bringing the vast world of GIS data to the GeoWeb and the public at large.

The long term vision has been to eventually fuse the personal and dynamic data of the GeoWeb (long tail) with the static and statistical data of GIS (short tail). Mapufacture presented us the opportunity to accelerate that vision and bring a broader vision of geospatial awareness to the public. The chance to bring dynamic and static data together in an intuitive way. The opportunity to combine quantitative data with qualitative user generated feedback.

Imagine a world where it is not only possible to look at toxic release locations by volume of discharge, but also have the citizenry comment with words, photo and video on the impact it is having on their community. What if an accident happened at a toxic release point? You can now bring in real time weather and see if wind dispersal could be a hazard for response. The examples are innumerable. It could be your sales data dynamically generating from Salesforce.com and combined with detailed demographic data to better coordinate your next marketing campaign.

There is obviously a lot of work to be done, but the Mapufacture and FortiusOne teams are both excited to bring the potential of what the GeoWeb can be to the market. We are excited and look forward to showing the first step in that vision later this month. In the mean time we’d love to get your thoughts on possible new logos for Geo-Voltron.

Candidate A

Candidate B

Popularity: 24% [?]

With the rise of post-partisan Obama on the national political scene, there have been sporadic stories in the print and on-line media , in Op-Eds, on the cable-news/YouTube and in the blogs; of how some influential Republicans have turned into Obama supporters, the so called Obamacans, reverse of Reagan-Democrats. Of course, not everybody is buying into the Obamacan story, considering it as a media creation or part of chaos theory. However, the recent claims by McClatchy newspapers’s that their “…. computer analysis, incomplete due to the difficulty matching data from various campaign finance reports, found that hundreds of people who gave at least $200 to Bush’s 2004 campaign have donated to Obama”, caught our eye at FortiusOne.

So, if there indeed are Bush donors who now have become Obamacans, the data-team wanted to find out where they are spatially speaking. Below are the maps of our efforts showing locations of possible Obamacans in New York City and Washington D.C. Why use the term possible? Because what is mapped are the results based on spatial join and attribute join, the later being a variation of spatial join. And the accuracy of the results of such joins is subject to the limitations imposed by the accuracy of the original data (donor addresses) as well as limitations of the geocoding operation. More on this towards the end of this post. So what is mapped are donor address matches and not individual donors.

Attribute Join
The attribute join is based on an identifier “XY” constructed from the concatenation of X and Y location coordinates of the Bush-Cheney and Obama donors, where the X and Y location coordinates are obtained by geocoding donor addresses. The attribute join resulted in 250 records across the lower 48 states, mostly concentrated in major cities of North-East and West-Coast. The results are shown below for New York city (lower Manhattan) and Wash D.C., where blue circles represent Obama donors (1,415 in D.C. and 1,825 in New York city); red circles represent Bush-Cheney donors (294 in D.C. and 419 in New York). The purple squares colocated with Bush-Cheney red circles are the XY “attribute matches.” There were 32 such locations in D.C and New York City had 85.

New York City: “XY” attribute join of Bush-Cheney donors with Obama donors

Washington D.C.: “XY” attribute join of Bush-Cheney donors with Obama donors

Spatial Join
Yet another way was to carry out a “spatial” join between location of each Bush-Cheney donor with all of the co-located Obama donors, resulting in more than 9,200 Bush-Cheney records colocated with more than 42,000 Obama records in the lower 48 states. The results are shown below for New York City (lower Manhattan) and Wash D.C., where again blue circles represent Obama donors, red circles represent Bush-Cheney donors, and the purple circles with varying sizes represent count of Obama donors that are colocated with each of the “spatially” joined Bush-Cheney donor. There were more than 1,500 Obama donors colocating with 248 Bush-Cheney donors in D.C. while the comparable figures for NY city are more than 2,030 Obama donors colocating with 303 Bush-Cheney donors.

Bush-Cheney donor locations spatially joined with Obama donors in NY City

Bush-Cheney donor locations spatially joined with Obama donors in Wash D.C.

Donor Data
You may find/download the mapped as well as other supporting datasets from the Finder! by using the key-word “Obamacans“. The supporting datasets also include spatial join of all Bush-Cheney donors for each of the Obama donors.

Read the rest of this entry »

Popularity: 15% [?]

One of the most anticipated and most hollow panels at GeoWeb conferences of late is “Something Something Business Model”. I think the reality was best captured by the Fake Steve Coast:

The default business model of Web 2.0 has been advertising. The problem is you are largely limited to placing advertisements around maps and you can’t leverage the local or geographic content on the map to target with. So, you have to generate a massive amount of traffic to make enough money with your ads around maps. Which is difficult, since most of the clicking is on the map and you don’t get loads of page views to push ads against.

The dirty secret – it is even tough for the big guys (Google, Yahoo, Microsoft) to generate big revenue with their mapping applications. The mapping applications are largely loss leaders. The scary bit is they are loss leaders and GYM control the ad inventory. Meaning they actually have a network of advertisers willing to pay to have their content shown in conjunction with their maps. This is no small feat and I would love to hear how folks like Lat 49 are fairing in their endeavors to build an ad network for maps.

Even if we do finally get advertisements on maps and a version of Adsense to go with it – are you likely or unlikely to be able to pay the bills with it? Not to say it is impossible.

Platial has stated in the past it is generating revenue (possibly even cash flow positive) and has the level of traffic (15MM unique users per month) to support an ad based business. Although where does it go (acquisition, IPO, Kleiner et al want their money back eventually)? How many other GeoWeb companies out there are able to support themselves on advertising?

What are the other alternatives? Maybe we can start with how folks pay for geo applications and content today:

GIS – I pay for licensed desktop software (sometimes a client server deployment)
Google Earth – I pay for the pro version that has extra functionality
API’s - I pay for geo type API’s when they are not used on the public web
Integrators – I’ll pay you to build a geo type mash up (sometime you have your own product to make this easier)
Data – I pay you for proprietary data that I can use in my geo application
Subscription – I pay to use your service on a recurring basis
Market places – I pay for third party content through your website and you get a cut
Buying devices – I pay for a GPS or other mapping enabled piece of hardware.

I’d argue that the majority of GeoWeb companies that are making money are doing so with one of the business models listed above. Further, I’d argue that of those most of them are doing so as integrators. Paying for licensed GIS software is the most real of the models generating over a billion in revenue, but it is not really GeoWeb outside of people paying to license Google Earth.

Selling geospatial data is another real business generating around $660 million. The companies selling this data are rarely GeoWeb companies unless you count NAVTEQ and TeleAtlas. In the data old guard the business model to sell their geospatial data is often a hot topic.

Selling API’s is a very GeoWeb method of doing business, but with the abundance of available free API’s how many people are actually paying for them? While subscription services have been big winners in other Web 2.0 spaces (Basecamp, Salesforce etc.) I can’t think of a successful geospatial subscription service (help me there must be one…).

For market places, WeoGeo has been successful in getting content providers to make their data available for sale through their service. It will be interesting to see how it scales and if a market develops, but it is one of the few GeoWeb areas where there has been business model innovation.

Interestingly, there are a myriad of business model options but nothing I’ve seen to date really pops out as a clear cut winner. Whether you are a start up or one of the big incumbents figuring out how to monetize the GeoWeb, it is going to continue to be a bur in the saddle (aka pain in the ass)…

Popularity: 11% [?]