Introduction to GIS Lecture 2: Part 1. Understanding Spatial Data Structures Part 2. Legend editing...
Transcript of Introduction to GIS Lecture 2: Part 1. Understanding Spatial Data Structures Part 2. Legend editing...
Introduction to GIS
Lecture 2:Part 1. Understanding Spatial Data
Structures
Part 2. Legend editing & choropleth mapping
Part 3. Map layouts
Introduction to GIS
Part 2. Spatial Data Structures
By Austin Troy & Brian Voigt
Introduction to GIS
Spatial Data Model
• Features– cartographic object
• Entities– spatial location– non-spatial properties
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• Points (no dimensions)• Lines, or “arcs” (1 dimension) or• Areas, or “polygons” (2 or 3 dimensions)
Vector
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Point layerX,Y coordinates
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0 5
1
1 2 3 4
2
3
4
5 Point ID Location
1 4,3
2 2,2
3 1,4
4 4,1
1
2
3
4
Examples: Stream gauge / wave buoy, stoplight, survey location / respondent, residence / business, etc.
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Line (Arc) layer• Points define lines (arcs)
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Image source: ESRI Arc Info electronic help
Line segment
Vertex
Node
• Feature is the ARC, not the line segments• Arcs meet at the nodes
Arc
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Line (Arc) layer• Each point has a unique location
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Polygon layer• In a polygon layer, lines (arcs) define areas
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Lines (Arcs)
Points
• Boundaries: line segments
• Area of homogenous phenomena
• Closed region
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Raster
• Grids, or pixels• Cell size is constant• Area of each cell defines the resolution • Raster files store only one attribute, in the
form of a “z” value, or grid code.
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Raster and Vector representations of the same terrain
Raster: great for surfaces Vector: limited with surfaces
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Raster and Vector representations of the same
land use:
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Vector vs. Raster: bounding
Raster: bad with bounding Vector: boundary precision
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Vector vs. Raster: Sample pointsCancer rates across space
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Vector / Raster RepresentationPoints
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Vector / Raster RepresentationLines
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Vector / Raster RepresentationPolygons
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WHEN TO USE RASTER OR VECTOR???
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•Raster and Vector
• Analytic advantage and disadvantages• Technical advantages and disadvantages• Specific Usages• Tossups
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Part 2. Legend editing, choropleth mapping
By Austin Troy & Brian Voigt
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Mapping Attribute Data
Two basic approaches for visually displaying attribute data:
1. Quantities approach
2. Category approach
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Mapping Attribute Data
Quantity approach: applies to numeric >> ordinal
Category approach: text values; order is irrelevant
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Mapping Attribute Data
Quantity approach, example: population
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Mapping Attribute Data
Category approach, example: vegetation type
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Mapping Categories
Examples: vegetation types, land use, soil types, geology types, forest types, party voting maps, land management agency, recategorizations of numeric data (“bad, good, best” or “low, medium, high’). Can you think of any others?
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Mapping Categories
• Access layer properties: 1. right-click layer in the TOC
2. double-click layer in TOC
• Symbology tab >>> Categories >>> Unique values
• Set Value Field to desired attribute
• Click the Add All Values button
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Mapping Categories
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Mapping CategoriesOften categories must be aggregated and redefined: this land use
map had over 110 categories that were condensed to 12
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Grouping Categories
In this case 1262, 1263, 1264, 1265, etc. refers to different subcategories of commercial land use
Can then save symbology as .lyr or in .mxd
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Quantity Mapping
Also known as “choropleth mapping”• For points, lines and polygons: graduated color,
or color ramping• For lines and points can also do graduated
symbol
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Graduated Color
• Layer Properties >>> Symbology >>> Quantities >>> Graduated colors
• Set the Value field to desired attribute• In this case we choose median house
value• It automatically assigns
five classes for the data
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Graduated ColorThe map shows high value housing with dark
colors and low value housing with light colors
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Graduated ColorSame map, but this time with 3 classes
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Graduated Color…and with 15 classes
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Graduated Color Classification
interfaceThese are the class breaks (based on the distribution of the data)
largesmall
Classification method (default= Jenks)
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Graduated Color
• Classification Method: Equal Interval
• What kind of data does this work for?
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Graduated ColorHere’s what the same
distribution looks like with only 5 equal intervals.
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Graduated Color
• Data representing # of vacant structures
• Potential problem(s) with this method of classification
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Graduated Color
This map of vacant properties tells us almost nothing, because almost all the records fall into the first class
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Graduated Color• Natural Breaks: Notice
how there are now more classes on the left side, where most of the data are.
• Minimize each class’s average deviation from the class mean, while maximizing each class’s deviation from the means of the other groups
• Reduce the within class variance and maximize the between class variance
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Graduated Color
This map of vacant properties, made with Natural Breaks, is more intelligible
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Graduated Color
Quantile method: sets the class boundaries so as to maximize the perceived variation in the map; equal number of data points in each class
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Graduated Color
Map of vacant properties using the Quantile classification method
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Graduated ColorGraduated color can also be applied to points.
Here are houses display by sales price
Natural breaks Equal interval
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Graduated SymbolIn this case housing price is expressed by symbol size
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Graduated SymbolThe same thing can
also be done with lines—for instance, traffic volumes
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Symbol StylesWe can also choose to “match to symbols in a palette” and then
apply the “transportation.style” palette to the FCC, or roadcategory, attribute inour roads layer
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Results in this map
Must click here to match
Choose your style palette here
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Symbol Styles
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Symbol StylesOne could also manually create symbol styles for each street type.
Clicking on each symbol in either the TOC or properties windows brings up a manual symbol selector. You can assign a separate one to each category.
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Includes many classes of industry standard symbols
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Symbol StylesThere are also a huge variety of industry-specific point symbols
that can be either assigned through matching symbols to a predefined style or manually assigning those symbols
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Displaying ChartsAttributes for point, line or polygon features can also be
displayed as charts on the map
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NormalizationShow an attribute normalized by another attribute or
expressed as a percentage of total. Here we have number of vacancies per tract as a percentage of total households.
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numerator
denominator
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Layer Files
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• Save symbology and setting
• Primarily for saving legend setting
• Opening a layer file will open the data layer with all the preferences saved
• With an extension .lyr
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Layer Files
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• Use layer files when you have lots of non-numeric categories
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Layer Files
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• Create a layer file in ArcCatalog
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Layer Files
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• Create a layer file in ArcMap
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Layer Files
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• Import a layer file’s symbology in properties
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Part 3. Map Layouts
By Brian Voigt and Austin Troy
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Map Layout• You can create a map for layout in Arc GIS
by selecting View >>> Layout view.• Layouts are designed to be cartographically
acceptable, which means they must have the key elements of a printed map, such as scale bars, north arrows, legends and titles
• These can be added from the Insert menu
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Map Compilation
Map?X
What’s missing?
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Title
Legend
Neatline
North arrow
Scale bar
Notes
Data frame
Map Compilation
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Map Compilation• Geographic features
• Other map elements– Legend– Title– North arrow– Scale bar– Author– Neatline– Source of data– Other objects…
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Map Layout: Data frame• Create a new view or “Data Frame” in
ArcMap
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ArcMap: Data Frame• More than one frame can be shown in layout view
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Frame 1
Frame 2
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Data Frames: Context
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Data Frames: Inset maps
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Layouts: Data frame• Access and edit data frame properties
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Map Layout: Map Legend
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Map Layout: Map Legend
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• Legends editing: Items
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Insert Legend Title
Map Layout: Map Legend
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Map Layout: Map LegendEditing legend item type
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Map Layout: Map Legend
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• Legends editing: Size and position
Size&Position
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Map Layout: North Arrows
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Map Layout: Scale Bar
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MXD Files
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• Project files– Save your layout
– All other preferences
– Data is not included
– With an extension .mxd
• File >>> Save (As)