Mitchell Chs. 2-4

Ch. 2

Maps can be used to describe more than just where things are.

 

Mapping locations of features allow researchers to find the patterns behind what causes these features, such as plant types with rainfall, erosion etc. -When looking at a map, there are two important questions one must ask;

 

What information do you need from the analysis? Depends on you are looking for.

 

How will you use the map? Having a very detailed map can be useful, but only information pertaining to what needs to be checked is useful.

 

Assigning Geographic Coordinates

Whether the map is new or old, having coordinates of different parts of the map is very important. Whether this is an address or long/lat values is specific to the map, but without coordinates the map is just a jumble of information.

 

Assigning Category Values

With maps with different types of features, these features needs to be distinguishable, and within that, have a different code for mapping.

 

Within many maps are major types divided into subtypes. An example could be how toxic water might be based on the color on the map.

 

Single Type Mapping

Single type mapping is using the same symbol every time.

 

These are simple patterns, but these maps could be all one needs to describe simple features.

 

The GIS of this uses coordinates to map out the patterns. Look at page 26 in Mitchell for a good example.

 

Subsets within single features can also show patterns. The book uses an example on crime where all crimes are shown and then certain crimes are taken away to show different patterns like burglaries.

 

Mapping by Category

Takes simple maps and adds different types of information to it.

 

The GIS behind the mapping stores different pieces of information in different sections.

 

 Mapping by category allows for mapping by type as well.

 

Categories/Grouping

When categories are mapped, the different types of subcategories must be grouped with the main one.

 

With these groups comes turning some categories on and off to show more important information in greater detail.

 

With the categories also comes how the viewer perceives the information. An uninhabited zone could be any number of things, but a forested area is a forested area.

 

Grouping the categories can be done in three different ways

Two codes: one for detailed and one for general

Creating a table to distinguish between detailed and general

Assigning the same symbol to the various categories that comprise each general category.

 

Colors and Symbols

When describing a map, using different colors allow the reader to easily distinguish between categories. Many maps use similar colors for each subsection.

 

Widths can also play an important role.

 

Using text can also help explain a map. If some areas could be misunderstood, adding text sometimes can erase the confusion.

 

Ch 3. 

Mapping the most and least allows you to cross-reference material and data to fit your needs, or discover patterns and trends among your info. 

 

Mapping the data based on quantities goes beyond just graphing data to a certain location, by adding the additional layers, you see what areas pertain to your question.

 

Features- knowing what features you are mapping is also very important. Graduated colors are used when there is a continuous phenomenon, or when the area is not simply defined.

 

To Broaden or to Generalize-  whether you are exploring the data, or presenting a map.

 

Counts and Amounts- counts and amounts show you the total numbers.

    A count is the actual number of features on the map.

    An amount is the total of a value associated with each

        feature.

 

Ratios- shows the relationship between two quantities, and are created by dividing one quantity by another.  The most common ratios are averages, proportions, and densities.

 

 Densities show where features are concentrated.

 

Ranks- used to sort the importance of something from highest to lowest, or vice versa.

 

Mapping Individual Data- helpful when first examining data because you get an accurate view without all the other distractions.

 

Classes/Breaks- using classes and breaks unifies a group of info into a universal set of numbers that can be graphed.

 

There are 4 types of classification schemes:

Natural Breaks- Classes are based on natural groupings of data values.  This system associates data where there are jumps in values, and pairs them in the same break value.

Quantile- each class contains an equal amount of features, but the values may be different.  Some values may be extremely high or lower than the norm, but could be placed in a class where the values are varied greatly due to the number of features.  Good for emphasizing the relative position of a feature among other features.

Equal Interval- the difference between the high and low values is the same for every class.  Class breaks are an even, set number for all.  Good for mapping continuous data,

Standard Deviation- This requires you to find the median of your information, as well as the standard deviation, and then break classes by adding or subtracting the standard deviation to the median.

 

Choosing a Classification Scheme- When choosing what scheme to choose, you must take into account many factors including, how your data is distributed across it’s range, as well as looking at outliers, and finding how to best fit them in your class.  Most of the time natural breaks are good for taken care of outliers, which could throw your whole scheme off balance.

 

Making a Map- Once you have decided how to classify your data, you must find the correct map projection for it.  The types of maps used are: Graduated symbols, Graduated Colors, Charts, Contours, and 3-D Perspective Views.

 

Graduated Symbols- used to map discrete locations or lines.  Graduated point symbols are drawn at the locations of individual features to show the magnitude of the data value. 

 

Ch. 4

Mapping the density of features lets you see the patterns of where things are concentrated

 

Helps you find areas that require action or meet your criteria, or monitor changing conditions

 

Why Map Density?

Mapping density shows the highest concentration of features

 

Useful for looking at features and mapping areas of different sizes

 

Simplifies the graphic portrayal of individual locations by deriving the number over a specified area

 

Mapping density is especially useful when mapping areas, such as census tracts or counties that vary greatly in size

 

Deciding what to map…

Know what kind of data you have

 

Density mapping of point and line features are mapped using a density surface

 

Can map data that has already been summarized by defined areas

 

Can either map the density of features, or of feature values

 

Can create a density map based on features summarized by defined area, or by creating a density surface

 

Mapping density for defined areas

Dot map, or calculate a density value for each area

 

Dot Map

Represents the density of individual locations summarized by defined areas

 

Each dot represents some number of phenomena

 

Random distribution of dots per area – they do not represent actual numbers for that one locality

 

The closer the dots, the higher the density

 

Density portrayed graphically, not numerically

 

Creating a density surface

Usually created as a raster layer

 

Each cell in the layer gets a density value based on the number of features within a radius of the cell

 

Provides the most detailed information, but requires more effor

 

Can create a density surface from individual locations, or linear features, such as roads or streams

 

Point data may be:

Locations of features, such as customers, crimes, or eagle nests

Sample points you’ve collected data for, such as water quality samples across a lake