Looks like no one added any tags here yet for you.
Nominal Data
Data that can be labeled or categorized but there is no inherent order between categories.
Ordinal Data
Data that can be categorized and ranked, where you can’t measure the interval between rankings.
Interval Data
Data that can be categorized or ranked, and the degree of difference between intervals can be measured, but there is no true zero.
Ratio Data
Data that can be categorized or ranked, and there is a true zero.
Entity
A real-world object or phenomenon.
Feature
A single record or row in a table that represents an entity.
Attribute
A characteristic or measurement about a feature.
Vector Pros
Good for discrete data, can represent complex shapes, more precise, efficient for data storage.
Raster Cons
Lose precision when the cell size is large, can take up lots of room on a computer.
Shapefile Required Files
.shp, .shx, .dbf.
.shp File
The main file that stores the geometry.
.shx File
The index file that stores the index of the feature geometry.
.dbf File
The database that stores the attribute information of features.
Measures of Central Tendency
Mean, median, and mode.
Euclidean Distance
Measures distance on a flat map surface.
Geodesic Distance
Accounts for the shape of the earth, distances are calculated on the curved surface.
Buffering
A specified distance around a point, line, or polygon.
Union
All features and attributes are written to the output feature class.
Intersection
Portions of features that overlap in all layers will be written to the output feature class.
Clipping
Uses one vector dataset to cut out a piece of another vector dataset.
Pattern Analysis
Using techniques to assess the proximity and density of features in space.
Spatial Interpolation
Analysis where we use points with known values to estimate values at unknown points.
Choropleth Maps
Polygon-based maps that divide geographic areas into colours or patterns depending on one of the data attributes.
MAUP
A problem in spatial analysis where the results depend on the shape or size of zones used for analysis.
Nulls vs Zeros
Zero may indicate an absence of something, while null means data wasn’t collected or is missing.
Placeholder Number
An obvious number that stands out in your dataset when a number is required.
How do you create centroids from polygons?
Takes a polygon layer, finds the centre, and creates a new point feature
When would it be useful to make centroids from polygons?
Running analyses that need points as the shape, if you are interested in spatial relationships from the centre of polygons, or for visual displays
How does the find closest analysis work?
Takes 2 input layers, the one you are moving away from and the one you are moving towards
Can get routes in straight lines or following roadways
Uses ESRI’s datasets for roadways
What are travel areas?
Input is a point layer, output is a polygon layer
Creates a layer that shows the area that can be reached within a certain time or distance of either walking or driving
Combining multiple travel areas can give you an indication of what areas are being affected/serviced by the feature
What is summarize within?
Input to summarize can be points, lines, or polygons
Summary areas can be another input polygon layer, or a grid or a “sketch” on the map
Calculates statistics of the number of features within another polygon layer
count/number of features
mean, median, mode, standard deviation
What is calculate density?
Input is points or lines, input is a polygon feature
Many different ways to visualize
Shows the density or spread of features
How do you generalize data?
Group individual results by a larger area, exact locations aren’t shared but a polygon with aggregated data is, need to aggregate or group to a meaningful size
What is geographic masking?
Publicly providing the exact location can cause harms, often knowing the exact location isn’t needed for the purpose of publication/data sharing, geographic masking allows us to shift the locations in a GIS to protect exact locations
When is creating a buffer useful?
When looking at the proximity of features, or between feature classes, or if you need to convert a point or line feature to a polygon and you know the area or size you need
What do histograms show?
The frequency of observations plotted against the range of observations for a single attribute
When do you have more filtering options?
Depending on the level of measurement in your dataset
What is a natural breaks classification?
Classes are based on natural groupings inherent in the data, and created in a way that best groups similar values together and maximizes the differences between classes
What is a quantile classification?
Each class contains an equal number of features, this is well suited to linearly distributed data
What is equal interval classification?
Divides the range of attributes into equal-sized subranges
What is defined interval classification?
Specifies an interval size to define a series of classes with the same value range
What is manual interval classification?
You can define your own classes, manually add class breaks, and set ranges that are appropriate for the data
What is geometrical interval classification?
Creates class breaks based on class intervals that have a geometric series, designed to accommodate continuous data
What is standard deviation classification?
Shows you how much a feature’s attribute value varies from the mean, mean and standard deviation are calculated automatically
What is a heat map?
Draws point features as a dynamic, representative surface of relative density. Works best when there is a large number of point features, especially if their symbols overlap
What are some examples of sources of error?
Nulls or zeros where they don’t belong, missing data, typos and formatting, differences between data source providers.