Unit 3 Flashcards
Advantages of Choropleth maps
Very common, easy to understand & interpret. Easy to make (especially in ArcGIS)
Disadvantages of Choropleth maps
Easy to misinterpret due to their ease in creation, even if it is not appropriate for the data
What is a Choropleth ideal for?
Things that are smooth or evenly distributed throughout the enumeration unit. Also units that are similar in size & shape
Should data be standardized or raw/count data for Choropleth Maps
Data should be standardized (ratios, percentages, densities)
How many classes are ideal for Choropleth maps
5-9 classes
2 important considerations for choropleth maps
classification method & number of classes
5 common data classification methods for choropleth maps
Equal intervals (all class intervals are the same), natural breaks (class intervals determined by big breaks in data), quantiles (same # of enumeration units in each class), mean/standard deviation, nested means)
3 common color schemes for choropleth maps
Sequential, part-spetral, & diverging
Map where symbols are scaled in proportion to some data that occur at point locations
Proportional or Graduate Symbol Maps
What kind of data is ideal for proportional or graduate symbol maps?
True point data where data is actually measured at a point. Also, conceptual point data (data collected for an area, but can be conceived to occur at point [ex: population of McLean County]. Data are typically raw/count data
Maps that are ideal for displaying variation within an enumeration unit
Dot maps
What type of data is common for dot maps
Raw Count data (Ex: total population, number of acres of corn harvested, etc.)
Used to restrict where dots are placed (ex: no dots in urban areas or water bodies for corn harvested)
Limiting attributes
Used to construct where dots are placed (ex: all dots for corn harvest to be placed in areas of cropland)
Related attributes
Automated mapping & GIS software such as ArcGIS will randomly placed dots within enumeration units
Ancillary Data
