all lecture material by austin troy (c) 2003 except where noted lecture 2: introduction to gis part...
TRANSCRIPT
All lecture material by Austin Troy (c) 2003 except where noted
Lecture 2:
Introduction to GIS
Part 1. Understanding Spatial Data Structures
Part 2. Legend editing, choropleth mapping and layouts
All lecture material by Austin Troy (c) 2003 except where noted
Introduction to GIS
Part 1. Understanding Spatial Data Structures
All lecture material by Austin Troy (c) 2003 except where noted
Perception, Semantics, and Space• How do we deal with representing semantic
constructions of spatial objects, like “mountain,” “river,” “street,” “city,”
• How about representing more conceptual semantic constructions like “temperature,” “migration pattern,” “traditional homeland,” “habitat,” “geographic range,” etc?
• Answer: we have various data models which use different abstractions of reality
Introduction to GIS
All lecture material by Austin Troy (c) 2003 except where noted
Entities and Fields• There are two general approaches for
representing things in space:– Entities/ Objects: precise location and
dimensions and discrete boundaries (remember, points are abstractions).
– Fields, or phenomena: a Cartesian coordinate system where values vary continuously and smoothly; these values exist everywhere but change over space
Introduction to GIS
All lecture material by Austin Troy (c) 2003 except where noted
Entities and Boundaries• There are two general types of boundaries, bona fide
and fiat (D. Mark, B. Smith, A. Varzi)
• Pure bona fide boundaries represent real discontinuities in the world, like roads, faults, coastlines, power lines, rivers, islands, etc.
• Pure Fiat boundaries are a human cognitive or legal construction, based on a categorization, such as administrative unit, nation state, hemisphere
• Some have elements of both, like soil type areas
Introduction to GIS
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Two major data models
• Entity approach roughly corresponds with the vector model
• Field approach roughly corresponds with raster model
• Any geographic phenomenon can be represented with both, but one approach is usually better for a particular circumstance
Introduction to GIS
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Raster
• Spatial features modeled with grids, or pixels• Cartesian grid whose cell size is constant• Grids identified by row and column number • Grid cells are usually square in shape • Area of each cell defines the resolution • Raster files store only one attribute, in the form of a
“z” value, or grid code. • Consider the contrary….
Introduction to GIS
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• Vector layers either represent:– Points (no dimensions)– Lines, or “arcs” (1 dimension) or– Areas, or “polygons” (2 or 3 dimensions)
• Points are used to define lines and lines are used to scribe polygons
• Each point line or polygon is a “feature,” with its own record and its own attributes
Introduction to GIS
Vector
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Raster and Vector representations of the same terrain
Introduction to GIS
Raster: great for surfaces Vector: limited with surfaces
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Introduction to GIS
Raster and Vector representations of the same
land use
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Introduction to GIS
Raster and Vector representations of the same
land use: closer in
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Vector vs. Raster: bounding
Introduction to GIS
Raster: bad with bounding Vector: boundary precision
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Introduction to GIS
Vector vs. Raster: Sample pointsCancer rates across space
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• In Arc View and Arc GIS, we can covert vector layers to grids, based on an attribute, or grids to vector layers
• The disadvantage of vector to raster is that boundaries can be imprecise because of cell shape• Each time you convert, you introduce more error too
Moving between vector and raster
Introduction to GIS
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WHEN TO USE RASTER OR VECTOR???
Introduction to GIS
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• where boundaries are not precise
• that occur everywhere within a frame and can be expressed as continuous numeric values
• where change is gradual across space
• where the attribute of a cell is a function of the attributes of surrounding cells
Raster data analysis is better for representing phenomena:
Introduction to GIS
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• Simple file structure
• Simple overlay operations
• Small, uniform unit of analysis
Raster technical advantages :
Introduction to GIS
Raster technical disadvantages :
• Big file size, especially for fine-grained data
• Difficult and error-prone reprojections
• Square pixels are unrealistic
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Vector analysis is better :• Where there are definable regions • Where the relative position of objects is important• Where precise boundary definition is needed• Where multiple attributes are being analyzed for a
given spatial object• For modeling of routes and networks• For modeling regions where multiple overlapping
attributes are involved• EG: units with man-made boundaries (cities, zip
codes, blocks), roads, rivers
Introduction to GIS
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• Smaller file size (in general)
• More graphically interpretable
• Allows for topology (see further on)
Vector technical advantages :
Introduction to GIS
Vector technical disadvantages :
• Complicated file structure
• Minimum mapping units are inconsistent between overlapping layers
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Specific Vector Usages
• All legal and administrative boundaries (zip codes, states, property lines, land ownership)
• Building footprints and 3-D models• Roads• Bedrock geology• Pipelines, power lines, sewer lines• Flight paths and transportation routes• Coastlines
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Specific Raster Usages• Terrain modeling where micro-locational variability is
present and matters• Groundwater modeling, where surface flow outside of
channels is important• Representation of slope and aspect• Representations of distance and proximity to features• Spatial representation of probabilities (logit)• Modeling phenomena in nature with continuous spatial
variability and numeric attributes, like soil moisture, depth to bedrock, percent canopy cover, vegetative greenness index, species richness index
Introduction to GIS
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• In many cases, though, the choice between raster and vector may not be so clear.
• Often it depends on the application
• The following are some examples where you could go either way:
Tossups
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• Vector-based models used for terrain, including contours and TIN– Problem: creates distinct terrain entities that
distort reality: terraces and triangular facets
• Raster based grids are more commonly used– They are optimal for showing spatial micro-
variation in elevation although still have the problem of being like miniature “steps”
– Lattices deal with this through interpolation
Terrain
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Soil
• Soil type: Vector – Soil types are meant to represent discrete and
homogeneous areas and are qualitative. There is no “slight gradation” between soil types like with pH
• Soil pH: raster– pH is numeric, not categorical, and that number may vary
slightly within a single soil type polygon
– If pH were turned into categories, like High, Medium and Low, vector might be better
Introduction to GIS
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Weather
• Weather station data: Vector, coded with points• Average precipitation surface: Raster
interpolation of points• Average precipitation contours: vector lines• Both are interpolations, but one may be more
accurate in a given situation• Downside of contours: terrace effect, fewer
intervals, more categorical
Introduction to GIS
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Rivers• Most people think of a river as a discretely bounded
entity, hence vector • What about where the river size fluctuates
seasonally, e.g. desert rivers?• Or where the location of the river bed changes
slowly and gradually over the years• Or where the river becomes delta, and the distinction
between “river” and “swamp” becomes fuzzy? • Or where the river has a certain probability of
flowing or being dry at any given location and time
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• Depends on the type of analysis being done• With vector can do network modeling of stream and
river system, but only in the arcs– Vector stream model can take advantage of topologically
enabled analysis tools
• With raster, can do surface flow modeling– More realistic, because when it rains water flows
everywhere, not just in channels, shows accumulation
– Think of every piece of land as mini stream channel
Rivers
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• No official administrative boundary for this• Where does one metro area begin and another
end? Look at the New York New Jersey area.• For a precise bounding, say for administrative
purposes, use vector• Can also include “fuzzy boundaries”• To represent a gradual change from one urban
area to another, use raster
Metropolitan Areas
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• Vector works well for modeling vegetation stand type where categories are broad, e.g. mixed conifer, deciduous hardwood
• Raster works better where there is micro-locational heterogeneity in species distribution
• Raster also works better for representing ecotones, or edges between two stands
• The more specific and variable the classification, the more likely the raster approach will be needed
Vegetation Mapping
Introduction to GIS
All lecture material by Austin Troy (c) 2003 except where noted
Introduction to GIS
Part 2. Legend editing, choropleth mapping, and layouts
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Visual Analysis• The most intuitive form of vector analysis is
visual analysis, where we code features with colors or symbols to deliver information
• Frequently, we code features by an attribute value and let the color or symbol express the attribute value
• Understanding legend editing and map classification is critical to making maps that effectively deliver information
Introduction to GIS
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Mapping of Attribute Data
In GIS, each feature can have a number of attributes attached to it (e.g. land parcel>> property ID, assessed value, square footage)
We can map out these attribute values by their corresponding geography
Two basic approaches for classifying the data:
1. Quantities approach
2. Category approach
Introduction to GIS
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Mapping of Attribute Data
Quantity approach: applies to numeric attributes that are ordinal (have order to them); this means one values is greater than or less than another; good for continuous data.
Category approach: applies to categorical data, where the categories can have, but don’t need to have, order. If they do have order, the category approach ignore that order
The same layer can have some quantitative and some categorical attributes
Introduction to GIS
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Mapping of Attribute Data
Category approach, example: vegetation type
Introduction to GIS
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Mapping of Attribute Data
Quantity approach, example: population
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Mapping Categories
This is the simplest type of mapping: we are simply assigning a different color or symbol to each feature with a given category value
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?
Introduction to GIS
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Mapping Categories
To map categories in ArcGIS, we simply double click on the layer in the TOC and, in “layer properties,” click on the “symbology” tab
Generally,we will choose “Categories>> Unique values”
Introduction to GIS
The we choose our values field that contains the attribute and then click the “Add all values” button
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Mapping Categories
The symbology in the last slide gives us conservation lands, categorized by type of ownership
Introduction to GIS
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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
Introduction to GIS
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Mapping CategoriesDo do this, we must group the “group values” function in the
symbology properties window
Introduction to GIS
We can then give that grouping a label
In this case 1262, 1263, 1264, 1265, etc. refers to different subcategories of commercial land use
This classification is saved when I save my ArcMap Document
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Quantity Mapping
This is more complex, because there are so many ways to map out quantities
Mapping options depends on the feature type:• For points, lines and polygons, we can darken or
lighten the color to express magnitude: this is called graduated color, or color ramping
• For lines and points we can increase symbol size to express greater magnitude: this is called graduated symbol; we can do this because points and lines have fewer than 2 dimensions
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Choropleth Mappinga thematic mapping technique that displays a quantitative attribute using ordinal classes applied as uniform symbolism
over a whole areal feature. Sometimes extended to include any thematic map based on symbolism applied to areal objects.-Nick Chrisman
A map that shows numerical data (but not simply "counts") for a group of regions by (i) classifying the data into classes and (ii) shading each class on the map. -Keith Clarke
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Graduated Color
In Arc GIS layer properties>>symbology, we choose Quantities>>graduated color
We then choose a value to representIn this case we choose
median house value
It automatically choosesfive classes for the data
Introduction to GIS
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Graduated Color
The resulting map shows high housing value areas with dark colors and low with light
Introduction to GIS
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Graduated ColorIn that case we used 5 classes. Changing the number of
classes changes the information delivered; more classes: more info, but harder to see differences
Introduction to GIS
3 classes for median value
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Graduated ColorIn that case we used 5 classes. Changing the number of
classes changes the information delivered; more classes: more info, but harder to see differences
Introduction to GIS
15 classes for median value
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Graduated ColorThe Classification
Method also affects how the mapped attributes will look. Arc GIS normally defaults to the Jenks, or natural breaks, method
Introduction to GIS
These are the breaks it makes, based on the distribution of the data
largesmall
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Graduated ColorNow, here’s an
equal interval approach. Notice how all the breaks are evenly spaced. With a fairly normal distribution of data, this is usually OK
Introduction to GIS
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Graduated ColorHere’s what the same
distribution looks like with only 5 equal intervals.
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Graduated Color
However, when the distribution is skewed, or there are significant outliers, then equal interval is problematic because most intervals have no data in them. Here’s an example, with number of vacant houses per tract—most have near none, but a very few have a lot
Introduction to GIS
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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
Introduction to GIS
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Graduated Color
Notice how with natural breaks there are now more classes on the left side, where most of the data are
Introduction to GIS
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Graduated Color
Introduction to GIS
This map, made with Natural Breaks, is more intelligible
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Graduated Color
There is a similar approach to Natural Breaks called Quantile. This method sets class boundaries so each class has equal numbers of observations in it
Introduction to GIS
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Graduated Color
This essentially sets the class boundaries so as to maximize the perceived variation in the map, as we see here
Natural Breaks is similar, but does not necessarily result in an equal number of data points in each class; rather it uses Jenks' Goodness of Variance Fit (GVF) statistic
Introduction to GIS
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Graduated ColorGraduated color can also be applied to points.
Here are houses display by sales price
Introduction to GIS
Natural breaks Equal interval
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Graduated SymbolSince points and lines are not dimensionally realistic, the symbols representing
them can also be graduated. Here the size of the dot represents the house price
Introduction to GIS
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Graduated SymbolThe same thing can also be done with lines—for instance, the width of a line feature showing rivers
can be made to represent the flow of that river segment. For many line features, like streets, ArcGIS comes preloaded with symbol palettes that recognize the attribute codes and put the appropriate symbol
Introduction to GIS
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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 CFCC, or roadcategory, attribute in our roads layer
Introduction to GIS
Results in this map
Must click here to match
Choose your style palette here
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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.
Introduction to GIS
Includes many more classes of symbols that are industry standar
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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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Charts displayed geographicallyAttributes for point, line or polygon features can also be
displayed as charts on the map
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NormalizationWith graduated color or symbol, we can also show 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. Otherwise we’re only tracking total number.
Introduction to GIS
numerator
denominator
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Layouts• You can very simply create a map for layout
in Arc GIS by simply clicking View>>Layout view.
• Layouts are designed to 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
Introduction to GIS
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Layouts• Example
layout (from lab 6)
Introduction to GIS
legend
North arrow
Scale bar
title
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Layouts• Legends are edited in the Legends property window,
which can be accessed by double clicking the legends. Best way to learn about it is try it out
Introduction to GIS
Legends can show layer name as well as intervals for quantitative data and category names for categorical data
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Layouts• You can change names of the layers for the sake of
your layout legend (since most layers have pretty unintuitive names) in the layer properties window
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Layouts• In layouts you can have detailed and highly formatted
labeling and annotation. You can use an attribute field to label; this is specified in layer properties
Introduction to GIS
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MXD Files • You can save your layout, along with all other
preferences and settings by saving an Arc Map Document (MXD) file. However, this is not saving your data, only the settings, including the layout. If you move the MXD, you must move the layers with it. This is one reason why a geodatabase is easier than multiple shapefiles
• To save, just go to File>>save as
Introduction to GIS
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Layer Files • Layer (.lyr) files save all your settings and
preferences for one single file. It is primarily for saving legend settings. So, for instance, if I a layer with 300 land use categories, and I create a legend classification that regroups them into 30 categories, each with a special color or hatching, I can save that as a layer file.
• Once created, opening a layer file will open the data layer with all the preferences saved. You can move the data around without moving the layer file as long as both are on the same system.
Introduction to GIS
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Layer Files • This is done in Arc Catalog, by right clicking and
clicking “create layer.” Then I can create the legend preferences in Arc Catalog
Introduction to GIS
Then, double clicking in Arc Catalog will give me the layer properties, which can be changed