Month: October 2012
Many online news outlets are posting real-time or interactive maps of the impact of Hurricane Sandy. It is nice to see that many of them are including meta-data on the source of their information. It is something that is often missing from online news maps, which is strange because of the normally strict rules about citing sources in news articles. The Guardian UK has posted interactive Google Map of every verified event along with a downloadable Google Fusion Table of citations. Mashable U.S. & World has provided an article on How to Follow Hurricane Sandy On-line including webcams, interactive maps, and apps. Many news sources such as the New York Times are using information from the National Weather Service or Google’s Hurricane Crisis Map. Being able to verify the source of information is important, but especially during a disaster event.
Occasionally there is a national news item that bubbles up to take headlines and starts a dialogue about a formerly fringe-ish topic. This week, there were two. In order of occurrence, the first is that an Italian judge has declared six scientists criminally negligent in predicting an earthquake and has sentenced them to six years in jail for manslaughter. The second is a US Presidential candidate thinks Iran is connected to Syria and that connection is what gives Iran a link to water (and thus shipping). Those two might not look connected, but they are. Let me take them in reverse order.
Let’s not get all political here about the relative merits of one party over another in US politics. We at VerySpatial don’t profess to know the intricacies of political policy, economics, foreign policy, and all the other issues surrounding US Presidential Politics. But we do profess to know at least thing or two about Geography, which apparently one candidate forgot. Mitt Romney said, “Syria is Iran’s only ally in the Arab world. It’s their route to the sea.” This is false as Iran has miles and miles of coastline, not to mention it isn’t even connected to Syria. You have to go through Iraq to get there, and its not like Iran and Iraq have a history of being buddy buddy. Obviously this is a major gaffe from a Presidential candidate, but the real issue here is that a surprising large number of journalist and general public do not even recognize it as such a gaffe. An error, sure, but do they think it is a big error? Not nearly as much. I think this speaks more to the lack of geographic literacy in the US as much as anything. More deeply, I think it speaks to the apathy of facts prevalent in US public discourse today. We need to remember that facts are the bedrock under which decisions are made. If we can’t get our facts accurate, how can we expect to make decent decisions or analysis?
This leads to the second news item, which is that Italy has convicted six scientists of manslaughter for failing to predict an earthquake. The punch line to the story is that these six scientists were unable to predict an earthquake and, in the eyes of the court, they failed to adequately predict the degree of danger and are therefore legally culpable. The obvious problem here is that earthquake prediction is a tricky endeavor at best. There are so many variables to contend with in earthquake prediction – time, location, magnitude – and each of those has so many sub-variables true earthquake prediction basically is a bit dodgy (editor – as the Itialians should say, impossibile). Further complicating this process is the fact that it is almost as bad to falsely predict an earthquake is going to happen as it is to fail to predict an earthquake is going to happen. Call it the ‘Boy Who Cried Wolf’ effect, if you will. The reality of earthquake prediction today is that we are simply ill equipped to adequately predict the future, only measure that which has already happened. Facts are important in this case, but we also have to know the limitation of facts. We have to have a good idea of what a fact is capable of telling us and what it isn’t. In my opinion, the Italian judge in charge of this case has made a grievous error in assuming facts that simply aren’t there, or at least aren’t predictable from known facts. How can we make decent decisions or analysis if we can’t understand the limits of what we know?
We’ve been following this news item for some time, and I have to say I, for one, never dreamed these scientists would be convicted. An Italian judge has decided six scientists and one government official are criminally negligent for failing to predict the L’Aquila earthquake. They face up to 6 years in jail for their actions. The judge was quick to point out the verdict isn’t based so much on the lack of prediction as their failure to adequate phrase their warnings in a sufficiently alarming way. It isn’t too much of a stretch to say this is going to have a drastically chilling impact on scientific reporting, particularly in Italy. I’d like to say something hopeful out of this, but frankly it is all quit too depressing.
Anyone who spends more than an hour around me knows I like clever word manipulations. Yep, I find them punny. Christoph Niemann has just taken this to a whole new level with Clever Google Maps Manipulations. Some of them are funny (like My Way or the Highway) and some of them are pretty nifty visual illusions. I personally like the one above best as I’ve gotten HORRIBLY lost on Mail-In Rebate Way on more than one occasion. Either way, they’re a good reminder that maps can be as much art as information.
There’s so much going on with this article in Jalopnik that I love. Let me break it down for you in rough order. First…. cars and geography and we all know how I feel about those. Second, the point of the article, which is to show we use a lot of gas in the US. But those are just the superficial, kinda uninteresting bits, especially to geographers.
The really cool part for me rests in a two things. This is an excellent example of how to lie with maps, or at least deceive. We know the US uses a lot of gas, but where and why is a bit of a mystery. One theory is the ‘fly over’ states tend to have older and less efficient cars and most importantly trucks. Furthermore, they tend to drive greater distances because they’re more spread out than an urban area like NY or LA. If you use the swipe bar in the middle (more on that in a second), you can flip between two views of the data. The left map shows annual gallons of gas used per capita and it clearly shows the middle of the country is the worst offenders. Again, the efficiency plus distances would make sense for the average person to use more gas than someone in an urban or suburban environment. However, the picture changes dramatically when you look at the map on the right. Here we see not per capita use, but total use, and it’s the more urban areas that tend to be the worst offenders. As Jalopnik points out in the text, the math is pretty clear – it’s because there’s more people. Even if a large number of people only drive a short distance in highly efficient cars they can still use a lot more gas per year than a small number driving large distances with inefficient cars. So how do you lower gas use? Thus far the focus has been upon fuel efficiency standards, but it looks like that might not be the only approach to take to tackle the problem. I just love the idea you can look at the same data totally differently and get a completely different compelling argument. It’s kinda awesome, I think.
And to round it out, the final really cool thing about this post is the great use of a swipe for displaying two maps. We use it a lot in our professional work as GISers, but I’d love to see more use like this ‘in the wild’ so to speak. It’s such a compelling way to present counter arguments just like this.