Quantum GIS: the Open-Source Geographic Information System
Loading shapefiles into QGIS is done by clicking the toolbar icon labeled Add vector layer, which looks like a plus sign hovering over a map; it opens a standard open file dialog. By preselecting ESRI shapefile (suffix .shp) from Files of Type, I can be sure I'm opening the right file, which is useful, because a shapefile is actually a bundle of files. As I load each shapefile, it shows up under its original name on the left under the Legend window, which acts as a sort of table of contents.
After unpacking the datasets, I load these five shapefiles in this order: allroads_161v7b.shp (roads), hydro_161v7b.shp (rivers), hydropoly_161v7b.shp (lakes), Washtenaw_Potential_Restoration_Area.shp (the name says it all) and Washtenaw_nlcd_1992.shp (land use).
Unfortunately, upon loading the shapefiles, the sum total map that's displayed on the right in the Map View window looks like a big rectangle covered with random black and green blobs and no lines. Where are the roads, lakes and rivers I loaded? One reason for the odd display and missing elements is that the layers I added first are buried under the county-wide land-use layer, which sits on top of everything else. I can begin to solve this problem by dragging the land-use layer down to the bottom of the Legend and tinkering with the other layers so they all are visible.
The other reason for the strange-looking map is that QGIS defaults to display one color for every characteristic in the shapefile. For the road layer, defaulting to one color is fine, because it is simply a collection of lines. However, layers with thousands of polygons are more complicated. All of the many land-use types default to the same color, thus creating no differentiation among them. I must give each land-use type its own unique color manually. To do so, I first right-click on the land-use entry in the legend and select Properties from the menu. On the Symbology tab, I change the drop-down menu next to Legend type from the default value of Single Symbol to Unique Value. Using the drop-down menu in Classification Field, I can select which field in the database to classify. In my case, I classify a field called GRIDCODE, which contains the code that designates the land-use code for each polygon in the layer.
How do I know which database field I should classify, as well as the meaning of each classification? To find out, I sometimes need to leave the Layer Properties menu and examine the attribute table, a display of the database containing the attribute data for the layer. For example, I can examine the attribute table of the land-use layer by right-clicking on the title in the Legend (on the main GUI) and selecting the command Open attribute table. An example of an attribute table is shown in Figure 2. The land-use attribute layer contains a field ID to designate each polygon, as well as the field GRIDCODE to classify each one. Oftentimes the attribute table also contains a field with the label for each classification. Although such a field is missing from the land-use attribute table, a separate file with classifications is found in a text file included in the downloaded dataset.

Figure 2. The attribute table displays the data contained in a particular layer, for example, a shapefile.
After consulting the attribute table and the file containing classifications, I am ready to continue with the classification of the field GRIDCODE back in the Layer Properties menu. Pressing the Classify button populates the window below with the unique classification codes found in the layer. I can label each classification as I wish using the "Label" field, and I can give each classification its own color with the Fill color option.
After finishing the classification, I also want to do some more housekeeping to make the Legend and Map View more useful, such as making the colors of the other layers more intuitive (for example, blue lakes) and thickening the lines designating the roads and rivers. I can carry these out also with the Layer Properties dialog (right-click on layer name→Properties). A right-click on the layer name also gives me the option to change the layer name displayed in the Legend.
Post-housekeeping, the Map View in QGIS finally takes shape. I finally can recognize features such as roads and rivers, and now that the land-use types are differentiated, I easily can tell which areas are urban, agricultural, forested and so on. Figure 3 shows the end result.

Figure 3. After modifying the properties of each layer and changing the layer names in the Legend, the Map View is readable and ready for analysis.
To simplify visual analysis on my map, I also applied the same color to similar land-use categories. For instance, I applied the same color to two different agricultural categories as well as three different forest-related ones. For this application, I am interested to know only whether the land use is agricultural or forested, not the specific type of each. Fewer colors makes my map less busy.
James Gray is Products Editor for Linux Journal
Today’s modular x86 servers are compute-centric, designed as a least common denominator to support a wide range of IT workloads. Those generic, virtualized IT workloads have much different resource optimization requirements than hyperscale and cloud applications. They have resulted in a “one size fits all” enterprise IT architecture that is not optimized for a specific set of IT workloads, and especially not emerging hyperscale workloads, such as web applications, big data, and object storage. In this report, you will learn how shifting the focus from traditional compute-centric IT architectures to an innovative disaggregated fabric-based architecture can optimize and scale your data center.
Sponsored by AMD
Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6
Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.
Learn more about catching the bad guy in this free white paper.
Sponsored by DLT Solutions
| Using Salt Stack and Vagrant for Drupal Development | May 20, 2013 |
| Making Linux and Android Get Along (It's Not as Hard as It Sounds) | May 16, 2013 |
| Drupal Is a Framework: Why Everyone Needs to Understand This | May 15, 2013 |
| Home, My Backup Data Center | May 13, 2013 |
| Non-Linux FOSS: Seashore | May 10, 2013 |
| Trying to Tame the Tablet | May 08, 2013 |
- Using Salt Stack and Vagrant for Drupal Development
- Making Linux and Android Get Along (It's Not as Hard as It Sounds)
- New Products
- Validate an E-Mail Address with PHP, the Right Way
- Drupal Is a Framework: Why Everyone Needs to Understand This
- A Topic for Discussion - Open Source Feature-Richness?
- New Products
- Home, My Backup Data Center
- The Pari Package On Linux
- Developer Poll
Enter to Win an Adafruit Prototyping Pi Plate Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Prototyping Pi Plate Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- Next winner announced on 5-21-13!
Free Webinar: Linux Backup and Recovery
Most companies incorporate backup procedures for critical data, which can be restored quickly if a loss occurs. However, fewer companies are prepared for catastrophic system failures, in which they lose all data, the entire operating system, applications, settings, patches and more, reducing their system(s) to “bare metal.” After all, before data can be restored to a system, there must be a system to restore it to.
In this one hour webinar, learn how to enhance your existing backup strategies for better disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible bare-metal recovery solution for UNIX and Linux systems.




5 hours 22 min ago
11 hours 1 min ago
17 hours 59 sec ago
17 hours 23 min ago
17 hours 33 min ago
17 hours 37 min ago
18 hours 7 min ago
20 hours 59 min ago
21 hours 34 min ago
21 hours 35 min ago