Card Set Information
GIS Test 2 Missed Questions
National Spatial Data Infrastructureshares data through clearinghouses
: update control points to real-world coordinates.
: use control points to run an affine xformation.
: create output by applying xformation equations to input features.
provides interactive functionality to establish the control points.
When control points have been established, the distance between the transformed point and real position for that point (RMS residual error) is calculated.
a process that fills each pixel of the new image derived from an image-to-map transformation with a value or a derived value from the original image.
Reduced resolution dataset (RRD files)
Technique commonly used for displaying large raster data sets.
Builds different pyramid levels to represent reduced or lower resolutions of a large raster.
When viewing entire raster, we view it at the highest pyramid level; as we zoom in, we view more detailed data at a finer resolution.
3 Main Causes of Location Errors
errors – hundreds of features need to be traced; it is reasonable that errors will be made
Scanning and Tracing
errors – duplicate lines, collapsed lines, misshapen lines
Errors in spatial location of control points
: Categorical, green, blue, male, female, elm, oak, Democrat, Republican, soil types
: ordered data - small, medium, large; first, second, third
: arbitrary 0; equal intervals between values; 10 degrees, 20 degrees
: definite 0 point; age, height, length time
Types of Database Design
Process of decomposition of flat files or data
Attribute data is broken down to small tables
Still maintains necessary linkages between them.
Ways to Classify Data
Variety of different classification methods:
Jenks Natural Breaks
Standard DeviationManual (set your own)
Same data may appear differently
Jenks Natural Breaks
Exploits natural gaps in data
Breaks that best group similar values and maximize the differences between classes.
Features are divided into classes with boundaries set where big jumps in the data values exit.
Good for unevenly distributed data.
Divides range of values into equal-sized subranges, (i.e. 0–100, 101–200, and 201–300).
Emphasizes amount of an attribute value relative to other values.
Best applied to familiar data ranges, such as percentages and temperature.
User chooses class size.
Specifies the interval value.
Data determines number of classes based on the interval.
Each class contains equal number of features.
Well suited to linearly distributed data.
Since features are grouped by number in each class, map can be misleading with unevenly spaced class ranges.
Similar features can be placed in adjacent classes, or features with widely different values can be put in the same class.
Minimize this distortion by increasing number of classes.
Shows how much a feature's attribute value varies from the mean.
ArcMap calculates the mean values and the standard deviations from the mean.
Class breaks are then created using these values.
A two-color ramp helps emphasize values above (shown in blue) and below (shown in red) the mean.
3 Labeling Options
placed automatically for an entire layer and behave as a group
Turn on/off for entire layers
Redrawn each time the map view changes
Uses Autoplacement to ensure no overlaps between labels
Unavoidable overlaps are discarded
Can specify classes with own symbols
Can specify placement priorities
May change between screen and printing
Placed by user individually using text boxes from the DRAW tool bar.
Created from dynamic labels
Stored permanently with feature class
Provides significant control over independent labels and their positions.
Can be stored three ways:
As text in the map document
As a feature class in a geodatabase
As feature-linked annotation in a geodatabase:
If the feature gets deleted, so does the label
Cannot go back to dynamic labels