Terrorism, Lawns and the GeoWeb

Mow West, Young Man
Sayyid Qutb traveled from his home in Egypt to visit Greeley Colorado in the 1950’s. The things he saw in Greeley greatly influenced his ideas about society. One thing that really bothered him was the local’s lawn care rituals.

The mowing habits of his Greeley neighbors helped provoke Qutb to write a book sparking a fundamentalist movement that eventually led to the formation of al Qaeda.

While we may be tempted to slack off on lawn care, especially during a drought, we must remain vigilant. Communism wasn’t defeated through appeasement, and neither will terrrorism. This is not a conventional turf war: terrorists view an un-mowed lawn as an admission of defeat.

GRASS Won’t Cut It
Extreme times require extreme measures. What the GeoWeb needs is a service where users can develop lawn mowing mission plans. By bravely volunteering their geographic information not only would homeowners help out in the war on terror, but could also save a bit of leg work. A good plan can minimize wasted effort spent pushing a mower across areas already mowed. Think of it as situational awareness on the home front.

Someone should seek funding from the Department of Homeland Security to develop a Lawn Mowing Mission Planning Application. This app could leverage existing REST services, like those used to support the City of Greeley’s showcase web site.

For example, a home owner would fire up Sketchup and configure a Dynamic Component for the lawn to reference the url of the parcel, which returns coordinates. The user would then digitize their lawn using 3D tools to describe low hanging branches, then save it to the Google Maps Data API.

Once the lawn is in the datastore users could do things like request mowing plans, or bids for mowing services.

Mow Forth And Sin no More
Sketchup is not a thin client though. Silverlight could be leveraged to write one. Flex would work too, but it lacks multithreading. While ESRI will be providing a KML layer in the Silverlight API, there doesn’t seem to be much support for KML with XAML. Maybe the Microsoft Virtual Earth Silverlight control will address this. If Google would provide SWIG interface files for C#, it seems like we could start doing this. For a company whose unofficial motto is “don’t be evil”, a bit of C# support could buy a lot of absolution.

Spatial Disk Defragmentation, Google, and 64 Bit Cuil

Perfect Disk Eval

Spatial Data on a Disk
Either a virus or a bad VPN driver filled up my disk with garbage files. In the process of cleaning things up my disk became very badly fragmented.

After unsuccessfully trying to get enough contiguous free space for my page file with Diskeeper, I ended up using PerfectDisk 2008, which defragged enough free space at boot time.

From the geodatabase’s perspective though, the file may still be fragmented. When I zoom in close on a large featureclass, the features that fall within the extent might be scattered in many different places on the disk, even though the file containing them is not fragmented.

How much would performance improve if features that are geographically near each other were placed on the same disk clusters?

Spatial Data in Memory
Still, it would be better to avoid disk access altogether. I have MSDN library loaded on my hard drive, however I find it faster to use Google to search msdn online. I suppose Google is faster since most info I’m looking for is already loaded into memory somewhere. Getting data from memory in Googles’ computers thousands of miles away is still faster than getting data from my local disk. As far as I know the Google Platform uses 32 bit computers – constraining them to 4 GB memory. Perhaps Google is faced with an Innovators Dilemma in deciding when to make the jump from 32 bit to 64 bit? If Cuil can educate Wall Street on the 64 bit advantage maybe they can compete with Google.

Stephen Arnold traces much of Cuil’s advances — and the advances of other search engines — to simple hardware designs that were carried out years ago by Alta Vista, the pioneering search engine build around the Alpha 64-bit processor at Digital Equipment Corporation. – Information Week

Cloud Geography and EGS

Geothermal Map - from SMU

I read somewhere that electricity costs will soon overtake hardware costs for computing. As the gap between electricity and hardware grows, electricity becomes even more important when siting a data center.

Perhaps the folks behind Google’s philanthropic interest in Enhanced Geothermal Systems (EGS) realize this. Notice how geothermal resources seem to be inversely correlated with population density, and positively correlated with mountains.

When your business plan is electric generation, expensive transmission lines are a necessity. But if your business plan is selling cloud based computing, it seems like building a data center next to the generator makes more sense. Granted, fiber optic construction would be needed, but I suspect this is several orders of magnitude cheaper than transmission lines. Perhaps we can expect to see more geothermally powered data centers cropping up in remote places. Since a large part of the electricity in a data center is used for cooling, locating in a cooler high altitude might also be attractive. I wonder whatever happened to NORAD. I wonder if Google is wondering this too.