GIS For Dummies

Chapter 8: Gathering and Digitizing Geographic Data 131

A school needs a location near students. So, you need a map that shows where potential students live.

A school needs a location that’s not already built up. Okay, you need a map of available land for sale.

A school needs a location that’s accessible and legal. You want to position a school near streets (so, look for a street map), where it can access utilities (water, sewerage, electricity, gas maps) in an area that’s zoned for public buildings such as schools (a zoning map), and so on.

Cleaning up after digitizing

The result of digitizing maps — getting them into your computer — is to create a database for your GIS to use. But during the digitizing process, some inaccuracies may creep in. You need to look for two general types of errors when deciding whether your GIS database is ready for use: entity (graphical) and attribute (description) errors. Here’s a list of general rules that can help you decide whether your database is correct (keep in mind that many of these rules overlap):

All entities that you want to include are present.

Your database contains no unnecessary features.

All entities are in the correct location.

All entities are the correct size and shape.

All objects have the correct labels.

Each polygon has exactly one label.

All features are of the correct type.

To determine whether the database includes all the features you want or whether it contains unnecessary features, you often need a complete accounting of what you wanted to include in the first place. You prepare

maps prior to hand digitizing so that you know exactly what you need to digitize and what should be in your database when you are done. Because you can actually see the relationship between what you have completed digitizing and what you have not completed right on your computer monitor, heads-up digitizing has advantages over traditional digitizing methods.

Entity errors that relate to the accuracy of location and position, collectively called dangling nodes (dangles, for short), come in two types — undershoots and overshoots (see Figure 8-10). Overshoots and undershoots might cause your GIS to either over-report or under-report the number of polygons in your database, which can also make your labels inaccurate.

132 Part II: Geography Goes Digital

Dangling Nodes

Undershoot

Figure 8-10:

Dangling nodes, or

dangles.

Overshoot

In most GIS software, digitizing modules ask you to define the nature of the features while you input them by assigning specific codes that indicate, for example, the beginning and ending of a line or polygon. If a line coded as a polygon fails to connect to create that polygon — if the line is a dangle — the software typically displays a graphic symbol indicating there is a problem.

In my experience, you can more easily find and correct overshoots than undershoots. Unless you’re Ms. or Mr. Stable, and you are very certain about exactly where you are digitizing, draw those lines too big, rather than too small.

Building the metadata

Some inexperienced GIS practitioners might lead you to believe that if you have a clean, error-free database, you’re ready to store, use, and share your data. Nothing can be further from the truth. I can’t tell you how often I’ve received databases, created with meticulous care, that still don’t really

explain exactly what they contain, how accurate that data is, the timeliness of the information, what the categories mean, and so forth. I needed something that describes the database. What I needed, and what you need to make your GIS database really useful, is metadata.

Chapter 8: Gathering and Digitizing Geographic Data 133

Metadata is data about data. It’s a complete description of the major facets of quality, source, and accessibility of the data that make them useful not only to you, but to others who might use the data after you do. In my teaching, I’ve used the phrase “tracking down the wetlands fox” from a newspaper article I saw years ago. That article described the difficulty of sharing databases when some of the layers contained multiple definitions of something as seemingly obvious as a wetland. Because it has different official definitions for different agencies, a wetlands map no longer contains distinct identifiable categories. Comparisons of different wetlands maps become impossible.

You can find many other examples of classification discrepencies, including comparisons of old soil maps with new ones, trying to link land-use patterns and land-cover patterns when the terms used are nearly identical for substantially different classes, and more. But these examples constitute only one type of metadata. The Federal Geographic Data Committee, which is responsible for maintaining spatial data standards in the U.S. Government, has developed a list of seven basic entries for geospatial metadata:

Identification: Defines the database name, developer, area of coverage, categories, themes, collection methods, and data access

Data quality: How accurate and complete the data are, adaptability for application, positional accuracy, completeness, consistency, and sources for derived data

Spatial data organization: Data model (Vector/Raster), number of spatial objects, additional non-coordinate methods of location encoding

Spatial reference: Latitude and longitude coordinates included, projections used, datums, parameters used for coordinate transformations

Entity and attribute information: Specific attributes, what information is encoded, codes, and code definitions

Distribution: Where and from whom to obtain the spatial data (you can often access and read the metadata before you actually obtain it), available formats, media type(s), online availability, and cost

Metadata reference: Compilation date and compiler

There are many excellent examples of metadata. Here is a URL for a typical set from the USGS vegetation database for a portion of South Florida:

http://sofia.usgs.gov/metadata/sflwww/vegmap.html

People (often, government agencies) have created numerous online tools for developing metadata. You can find information about some of these tools at http://sco.wisc.edu/wisclinc/metatool. Today, most com- mercial-grade GIS software includes such tools for you, so you don’t need

Part III

Retrieving,

Counting, and

Characterizing

Geography

In this part . . .

The data you put into your GIS isn’t much use to you if you can’t search out specific data, compile that data,

and then analyze and interpret to make sense of it. This part shows you how to retrieve just the right data and then turn that data into the information that meets your needs. In this part, you find out how you can describe the geographic data you find both numerically and by type. You also see how you can order geographic features by their sizes and shapes, as well as by their locations — both in absolute and in relative terms. Searching out and characterizing geographic data are powerful skills that serve you well when you work with GIS.

Chapter 9

Finding Information

in Raster Systems

In This Chapter

Creating a map search plan

Performing a search with your GIS

Making sense of your search results

Grid-based maps indicate where geographic features are located on a geographic grid, how much space they occupy, and their locations

relative to other features on the map. So, grid-based maps give you an extremely easy to understand way of storing spatial information.

With paper maps, you get the information you need by reading and interpreting the printed map. Paper maps are limited because you can layer only so many geographic features onto one map before that map becomes unreadable. For example, even though each kind of feature relates to transportation information, you can’t effectively show highways, waterways, railways, and ATC flight patterns all on one paper map. That would be one confusing map! You’d probably divide this kind of information onto separate maps. To work with more than one or two types of information, you need to gather information from separate maps — and who wants to go through that effort?

In GIS, you can comfortably map many types of information to a geographic grid because all the information can be coded into a computer and selectively retrieved for whatever subset of data you want. You use computer search and retrieval techniques to get just the information you need. The GIS may contain geographic information about all crops grown in the United States. You can retrieve just the geographic information about soybeans

in part of Kansas, if that’s what you need. First, though, you need software programs that allow you to locate the features you need to find. This chapter gives you the rundown on the easiest, most hassle-free ways to get the information you need from your GIS.

Chapter 9: Finding Information in Raster Systems 139

class, or data level you seek. The software finds objects by the codes you use to identify them when you create the data. After you decide on a specific search object, you can follow these general steps to find the object and verify the results in most raster GIS:

1.Select the map layer that contains your search object.

To locate all public school buildings, for example, you first select the map layer that corresponds to the object schools. You wouldn’t look in a map layer called hydrology, soils, or elevation to find the location of the schools. But a map layer called public buildings probably contains grid cells categorized as courthouse, library, civic center, and many others — including schools.

2.Specify the names, codes, measurements, and so on that identify your search object.

Look in the data that you or someone else produced to find out the code used for each object when the grid layer was created. In this example, you would determine the code used for schools and tell the computer to search for that in the grid layer called public buildings.

3.Review the retrieved information and make sure you got what you searched for.

The final map contains a subset of the data in the public buildings layer and will highlight only the cells containing the code for school buildings.

4.Name your new map.

You get the honor of providing a new name for the map. In this case, you’d likely call the map schools.

Folks run searches for all sorts of reasons, and the most simple (but not necessarily most common) is curiosity. You might want to know how the schools are distributed throughout the city. Or maybe you just want to simplify the map so that you can easily see individual schools without having to deal with all that annoying background. Most often, though, when you search for objects, you have a more complex question in mind. You may want to search for schools because you want to know where they’re located relative to other features, such as housing, so that you can buy a home near a public school.

People almost always have features or distributions other than simple location in mind when they perform a search in GIS. For example, you might look on a map for the location of your home, but you really want to find out whether you live within the same school district as a particular elementary school you want your children to attend.