Guide to Mapping

Understanding your data

Geographic Dimension. The first step in map making is to determine which type of geographic features are involved. That is, does the phenomenon being mapped occur at points, along lines or over areas? Airports and oil wells are points features, while highways and railroads are line features. Counties and forest stands are areal features.

In some cases, the scale of the map determines whether a feature should be considered an area or a point. For example, on a map of Los Angeles County, the city of Los Angeles would appear as a large area; on a map of the United States, in contrast, LosAngeles would appear as a point.

Measurement Level. Another task is to determine how the data are measured. Generally speaking, data can be considered qualitative or quantitative. Qualitative data show differences in kind or type, with no numerical values attached. Quantitative data indicate differences in amount, and can be expressed as a number, although they don’t have to be.

Data can also be described by measurement level. Map makers are generally concerned with three levels: nominal, ordinal, and interval/ratio data. Nominal data differ in type, and cannot be ranked. Examples of nominal data are land use (residential, commercial, park) or tree species (maple, oak, fir). Ordinal data can be ranked, but have only relative values (low, medium, high). With ordinal data, it is possible to say that one thing is greater than another, but because there are no numerical values attached to items, it is not possible to measure the difference between them. Interval/ratio data, in contrast, do have numerical values attached to them. Thus, it is possible to measure the difference between things as well as rank them. Examples of interval/ratio data are elevation or population.

Data Processing. In addition to knowing the measurement level, it’s important to consider how the data have been manipulated. Some statistics are reported as raw values, such as total population. Others have been standardized by some other measure, such as population per square mile. For maps of areal features, it is often preferable to use standardized statistics. This is to compensate for the differences in size between data collection areas. If you are making a comparison between data items, they should be in comparable units. This may require converting one variable to a different unit of measure. For example, if you have elevation data from two different sources, one data set may need to be converted from feet to meters to match the other.

Map Types

There are two general types of maps. Maps that give general information about the location of features are reference maps. Maps in a road atlas are an example of reference maps, as are topographic maps. Those that show the distribution of a specific topic are thematic or statistical maps. A map showing population distribution by county is a thematic map.

What if I choose the wrong type of map to make given my data?

• Fairly common GIS error.

• Due to lack of knowledge about cartographic options.

• Can still have perfect symbolization.

• Possibility of misinformation

• Definite reduction in communication effectiveness

• 1. Map Types:  Point Data

     • Reference

     • Topographic

     • Dot

     • Picture Symbol

     • Graduated Symbol

  2. Map Types:  Line Data

     • Network

     • Flow

     • Isoline

     • Reference

  3. Map Types:  Area Data

     • Choropleth

     • Area qualitative

     • Stepped surface

     • Hypsometric

     • Dasymetric

     • Reference

  4. Map Types:  Volume Data

     • Isoline, Stepped Surface, Hypsometric

     • Gridded fishnet

     • Realistic perspective

     • Hill-shaded

     • Image map

  5. Map Types:  Time Data

     • Multiple views

     • Animation

       • Moving map

       • Fly thru

       • Fly by

Choosing Map Types

1. Check the data

   • Continuous vs. Discrete

   • Accuracy & Precision

   • Reliability

2. Dimension (Point, Line, Area, Volume)

3. Scale of Measurement (Nominal etc.)

4. GIS capability

5. May need to supplement GIS software

Map Generalization

Generalization is an umbrella term for several processes, all intended to remove unnecessary detail. Because maps cannot show everything, the mapmaker must select which features to show and which to omit. Features may need to be simplified to be legible at a smaller scale. In many cases, data need to be classified - divided into groups of similar values. Finally, symbols must be chosen to represent features on the map.

Selection and Simplification

Typically, selection and simplification activities occur during the compilation of a database, rather than during the map-making process. However, you may find that a data set has more features than you need, and that you want to map only a subset of the features. You could generalize the data base by selecting a set of features for your map (e.g., select only cities with a population greater than 500,000 or select only Interstate highways).

Simplification is a more complex process, and actually modifies the features stored in the database. Map makers have developed elaborate methods for simplification that are beyond the scope of both this document and most desktop GIS software. Although you might not be involved in map generalization directly, you should be aware that many data sets you use are generalizations of the original source data.

Classification

For most maps, it will be necessary to classify the data before mapping them. It is not usually practical to have a unique symbol for each data record. For example, on a map of population density by state, it would not be possible to distinguish fifty shades of grey. Instead, states with similar values should be grouped together and shown with the same symbol. Most people can distinguish about seven classes. Depending on the quality of your monitor or printer, however, five classes may be a more practical limit.

You should be sure that your classification adequately describes the phenomenon youare mapping. Classes should be exhaustive (describe all possible values) and shouldnot overlap (no value can fall into two classes). For example, suppose you aremapping land use using the following categories:residential, industrial, park, andinstitutional. As you are assigning parcels to these classes, you find a parcel that isfarmland. It does not fit into any of these classes; how do you classify it? Your choices are to create a new class for farmland or to expand the definition of one of theexisting classes to include farmland.There are several approaches to classifying data, and the characteristics of your data setand the purpose of your map will determine which is best. An understanding of basic statistical concepts, such as mean, standard deviation, and data distribution, is invaluable for understanding data classification. 

Below is a description of some common classification schemes:

Equal range. Equal distance between class breaks. Useful when diagram of data distribution is rectangular, and enumeration areas are of equal size.

Quantiles. Equal number of observations in each class. Class intervals can be dramatically different in size.

Standard deviation. Class breaks based on distance of standard deviation from the mean. Useful if diagram of data distribution is a normal curve. Good for showing deviation from the mean.

Natural breaks. Class breaks conform to gaps in data distribution. George Jenks developed a classification similar to this that mathematically minimizes variation within classes, and maximizes variation between classes.

Map Composition

To communicate its message effectively, your map needs context: a title, a legend, a scale bar. Thus, the map is really just one element in the page layout (or map composition). Your layout can be designed for many types of display: a paper printout, a computer monitor, or a wall-sized poster. You should have some idea of how the map composition will be displayed before you begin designing the final layout, because that will influence some of the choices you will make. For example, if you are making a wall-sized map, you will need to make your text very large so it can be read from far away.

Let’s begin by looking at some of the basic elements of design: balance, hierarchy, figure-ground relationships, and complexity. 

Making a Map

People are visual learners and seem to be instinctively attracted to maps. Maps help us instantly perceive patterns, relationships, and situations. They not only organize and present the rich content of our world, they offer a unique contextual framework for understanding, predicting, and designing the future.

Maps and data form the underpinnings of GIS, which then organizes information into separate layers that can be visualized, analyzed, and combined to uncover meaning in data. This combination has resulted in a powerful analytic technology that is science-based, trusted, and easily communicated using maps and other forms of geographic visualization.

Map Evaluation Guidelines - see below & blog entry describing it

Cartographic Compilation and Design

• figure-ground organization

• visual hierarchy

• visual emphasis

• colors, symbols, labels

• font & font size

• context (geographic and thematic)

• map projection (equal area, conformal, etc.)

Map Elements and Page Layout

• balance

• map elements aligned to page and each other

• appropriate borders

• orientation indicator - grid/graticule appropriately aligned, labeled

• scale indicator - map scale appropriate & units logical

• legend - symbols, colors, size, position, logical

• titles & subtitles - relevant, descriptive, position, size

• production notes

Other Considerations

• Making a Meaningful Map

• Rachel's Cartography Checklist

• 33 Map Elements to Include in Cartographic Design

• Cartographic Considerations

• Intro to Map Design

• Presentation on Map Design

Advent of Digital Mapping

Make no mistake, traditional printed maps are not going away. They continue to be important because they help you quickly grasp the broader context of a problem or situation. The best printed maps are true works of art that can stir your emotions and imagination. There’s no comparable large-format document that communicates and organizes such large amounts of information so effectively and so beautifully. Cartographers using GIS will continue their craft of making astounding printed maps that teach and amaze.

And this will always be the case. Large-format printed maps and their digital cousins (such as PDFs) will continue to significantly occupy the good work of many mapping professionals. The difference now is that GIS tools have come of age for spectacularly high levels of professional cartography

Meanwhile, a major online mapping revolution is under way, and the implications of this are far-reaching. We all know that consumer maps are ubiquitous on smartphones and the web. Map-based applications regularly rank among the most used programs on smartphones and mobile devices. Online maps have familiarized millions of people with how to work with maps, and this massive worldwide audience is ready to apply maps to their work in ever more imaginative ways using Web GIS.

Web Map Properties

Continuous and multiscale:  Web maps work across multiple scales. Zoom in to see additional details and gain insight. Online maps provide continuous pan and zoom. They literally have no edges—you can pan anywhere and zoom in for greater detail. Even if you don’t have operational data for a particular area, the basemap will still provide reference.

Pop-ups:  Web maps are windows into a wealth of information. Click on a map location to “pop up” a report and explore the information behind it. Pop-ups help reach into the map for more detailed information that emerges on demand. A single window into a map can become a window into a world of related information, including charts, images, multimedia files, and analytics. The ability to link such a wide variety of content to the map has transformed how we think about maps. They’ve evolved from static containers of data to dynamic information vessels.

Real-time feeds:  Your online maps are no longer static. They can be readily and immediately updated because your layers online can contain the latest, most accurate information. When your data changes, the maps that reference that layer are also updated.

Mashup culture - Participatory GIS:  Your maps can combine more than your own data. You can mash up your rich GIS data with information from other users—in fact, whatever is useful and relevant to your objectives from the entire world of GIS users.