Quantum GIS: the Open-Source Geographic Information System
If you've ever zoomed around the globe with Google Earth, you know how much fun it can be to work with geospatial data. When I need a diversion, I often fire up Google Earth and float above the skyscrapers of Manhattan or revisit former stomping grounds.
For a deeper level of control with geospatial information—where you're the chef who concocts the whole stew—dive into a geographic information system, or GIS. A GIS lets you control all the elements that go into the geophysical world you want to explore. Stripping GIS down to its essentials, you could call it computer-based mapmaking. However, because a GIS is powered by a database, the opportunities for advanced analysis are light-years beyond anything you could do with a paper-based map. A GIS not only will make you feel like you have the world in your hands—look out for that “I'm playing God” feeling—but you also probably will do something extremely useful with it for your work or private life.
This article introduces a sample project with Quantum GIS (QGIS), one of the most advanced and powerful open-source GIS packages for the desktop. Although QGIS has some excellent documentation, new users might find the terminology a bit stilted and missing some information. The authors of the documentation assume you already are familiar with GIS and that you're coming to QGIS from a proprietary alternative, such as the popular ArcGIS from ESRI. I, on the other hand, assume you've never used a GIS before.
To illustrate some basic functions of a desktop GIS, I use QGIS to make preparations for a fantasy of mine, which is to create an ecologically friendly real-estate development. In this exercise, I locate a parcel of agricultural land in Washtenaw County, Michigan, near Ann Arbor, where I can restore a former wetland and build a cluster of homes nearby. I chose Ann Arbor due to its proximity to drained wetlands in rural areas, as well as local demand for homes in areas with lots of wildlife.
To accomplish this task, I explore how to load QGIS on your system; find the geospatial data for the task; load that data into QGIS; and view, set up and analyze that data to do the job at hand. Along the way, I introduce key concepts and important terms.
QGIS has a useful, comprehensive Web site with plenty of resources to get you started. Beyond the free application download, you'll find a wiki, help forums and loads of documentation. QGIS has versions for Mac OS X, Windows and several variants for Linux users: source, Debian, Ubuntu Gutsy and OpenSUSE. Given that repositories are provided, installation should be easy and straightforward. All you need to do is add the requisite repository to your favorite package manager. If you must install from source, there are plenty of on-line guides explaining the process. See Figure 1 for a look at QGIS's GUI.
GIS is a complex application requiring knowledge about data formats, how a GIS functions and general cartography. Let's rip through a quick, need-to-know primer on GIS.
As mentioned previously, using a GIS is essentially mapping on a computer. To do this mapping, you need to find data related to geography, typically called geospatial data. This geospatial data that we will introduce into QGIS consists of two elements, namely spatial features and attribute data. Examples of spatial features might include streets, rivers or land cover—any feature you might find on a map. Meanwhile, attribute data describes the characteristics of the spatial features and is stored in a database within the GIS. For example, most of those streets have names and lengths; the land-cover types have names and areas associated with them. In the case of land cover, a GIS might store attribute-related categories, such as high-density urban, low-density urban, cropland, forest and so on, which you then could query easily.
Your paper road map would think you were completely mad if you commanded it to “just show me the rivers and mountains, please” or “flip the county boundaries on and off”. On the other hand, because a GIS portrays data in similar groupings of geographic elements, called layers, your computer will execute your command and not label you loopy. Some examples of layers are countries, cities, rivers and oceans. A GIS allows you to control which layers are displayed on your screen at any time.
Layers can consist of two types, namely features and surfaces. In our above list, the layers with countries, cities, rivers and specific buildings are feature-based; oceans are one single, continuous expanse and, thus, are a surface.
James Gray is Products Editor for Linux Journal.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
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