attribute data and map types
DESCRIPTION
Attribute Data and Map Types. What kinds of data are in a GIS?. Spatial data Non-spatial data (also known as attribute data) “A GIS with no attribute data is a mapmaking system, not a GIS!”. What is Attribute Data?. - PowerPoint PPT PresentationTRANSCRIPT
CS 128/ES 228 - Lecture 2b 1
Attribute Data and Map Types
CS 128/ES 228 - Lecture 2b 2
What kinds of data are in a GIS?
Spatial data
Non-spatial data (also known as attribute data)
“A GIS with no attribute data is a mapmaking system, not a GIS!”
CS 128/ES 228 - Lecture 2b 3
What is Attribute Data?
Attribute data is data about objects stored in a GIS that refers to non-spatial properties of the object.
CS 128/ES 228 - Lecture 2b 4
Examples of Attribute Data Date of construction of a building Purpose of a building Name of a stream Population of a city Breed of dog that lives at a house Photo of a fire hydrant
CS 128/ES 228 - Lecture 2b 5
How is Attribute Data kept in a GIS?
Attribute data is generally stored in database tables.
CampusID Name Type Floors Footprint
6 Murphy Academic 2 2001
9 Hopkins Support 2 946
12 Maintenance Support 1 1848
15 Hickey Support 2 2367
17 Shay-Loughlen Dorm 3 1298
CS 128/ES 228 - Lecture 2b 6
How is Attribute Data extracted from a GIS?
GIS’s have two main types of output Reports Maps
As always, these can be combined
CS 128/ES 228 - Lecture 2b 7
Reports A Geographic Information System is,
at its core, a database.
Good database software always has a report generator. (We have something called Crystal Reports.)
Ergo, one can produce reports from a GIS.
CS 128/ES 228 - Lecture 2b 8
Maps A picture is
worth 1000 words
What attribute data is being shown?
CS 128/ES 228 - Lecture 2b 9
How is the Data Shown? Symbolization
Issues:
Realistic vs. abstract symbols
Size, texture, and density
Use of color
CS 128/ES 228 - Lecture 2b 10
Visual Display of Attribute Data
Easy for discrete features
There are many ways to represent continuous features on a map
Beware of the boundaries between classifications – they’re not usually very meaningful
CS 128/ES 228 - Lecture 2b 11
How do we distinguish among our data values?Dichotomous scale
(i.e. two classes)
Each class quite heterogeneous
Placement of boundaries is extremely sensitive to data density & quality
CS 128/ES 228 - Lecture 2b 12
How many classes to use?Multiple classes:
Classes more homogeneous
Large number of classes hard to interpret
Note: density of symbols should match the quantitative order of the classes, i.e. greater density => greater value
CS 128/ES 228 - Lecture 2b 13
How shall we determine the class limits?1. Intervals of constant size
CS 128/ES 228 - Lecture 2b 14
How to set class limits?2. Intervals that have equal numbers of cells
(equal class size)
CS 128/ES 228 - Lecture 2b 15
How to set class limits?3. Natural breaks in distribution
CS 128/ES 228 - Lecture 2b 16
A GIS Riddle Q: When is a map not a map?
A: When we call is something else.
Q: Why would we do this?
A: Because we do…
CS 128/ES 228 - Lecture 2b 17
Thinking about the data in a mapHow “processed” is the data?
Not at all Some Lots
Image Maps Line Maps Cartograms (Choropleths)
CS 128/ES 228 - Lecture 2b 18
Image maps (unprocessed data)
Composed of images of the area under study (usually aerial photos)
Often pieced together to make “mosaics”
CS 128/ES 228 - Lecture 2b 19
Advantages of image maps
What you see is what is there (assuming the photo is current)
CS 128/ES 228 - Lecture 2b 20
Problems with Image Maps Interpretation
Details can be tricky – perspective is unusual (see math at right)
Distortion Especially near
edges and seams No annotation
CS 128/ES 228 - Lecture 2b 21
Line Maps (Somewhat processed data?) Reality is replaced
by “reality-based” renderings
“Raw” data is replaced by a representation of that data
CS 128/ES 228 - Lecture 2b 22
Advantages of Line Maps Can concentrate
on information “of interest”
“Easy” to understand
CS 128/ES 228 - Lecture 2b 23
Disadvantages of Line Maps Data is not as
accurate due to: Incompleteness Representation
(especially scaling) Deliberate
“editorial” changes (see Exaggeration from previous lecture)
CS 128/ES 228 - Lecture 2b 24
Cartograms (Choropleths)
Similar to line maps, but geographic data is deliberately distorted to make some other point
CS 128/ES 228 - Lecture 2b 25
Utility of Cartograms Strengths
Highlight exactly what is desired
Strong visual imagery
Weaknesses
Not useful outside initially intended domain
Relatively difficult to produce Lots of information is lost
CS 128/ES 228 - Lecture 2b 26
Question???
Is a cartogram a map?
CS 128/ES 228 - Lecture 2b 27
Other types It is not uncommon to combine
some of these types
Cartographically Enhanced Image Maps are particularly common For example, the map we use in lab
CS 128/ES 228 - Lecture 2b 28
Map Forms
Historically, maps have been static, e.g. on sheets of paper
Computer technology has rendered maps dynamic and/or interactive
CS 128/ES 228 - Lecture 2b 29
Two “dynamic” maps
CS 128/ES 228 - Lecture 2b 30
One last issue
When do we compute using the attribute data?
CS 128/ES 228 - Lecture 2b 31
Early Processing… Compute your answers early and
then reveal them when asked. Commonly done for systems such as
search engines
CS 128/ES 228 - Lecture 2b 32
Late Processing… Store only your data; compute
answers as needed
MapQuest does this, as requests can’t be known in advance
CS 128/ES 228 - Lecture 2b 33
Hybrid Do some processing early, do some late
It is usually hard to detect that this is happening
“Caching” is one (not so good) example of this approach.• (Not so good because caching isn’t really
processing, per se)
CS 128/ES 228 - Lecture 2b 34
Conclusions A map is interesting, but a map that
highlights attribute data is useful
There are tradeoffs between completeness of information and ease of user processing
Caveat user!