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Geospatial Attribute Data . We Lied!. Earlier this semester we claimed that data was either spatial, i.e. said where something was, or attribute, i.e. told you something about an object. In fact, on the exam, we accepted “non-spatial data” as part of the definition of attribute data. - PowerPoint PPT Presentation
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1CS 128/ES 228 - Lecture 8b
Geospatial Attribute Data
2CS 128/ES 228 - Lecture 8b
We Lied! Earlier this semester we claimed that data
was either spatial, i.e. said where something was, or attribute, i.e. told you something about an object.
In fact, on the exam, we accepted “non-spatial data” as part of the definition of attribute data.
BUT, it’s not that simple…
3CS 128/ES 228 - Lecture 8b
Some attribute data is tied to a location, not an object
Estimate of phytoplankton distribution in the surface ocean: global composite image of surface chlorophyll a concentration (mg m-3) estimated from SeaWiFS data (Source: NASA Goddard Space Flight
Center, Maryland, USA and ORBIMAGE, Virginia, USA).
Estimate of phytoplankton distribution in the surface ocean: global composite image of surface chlorophyll a concentration (mg m-3) estimated from SeaWiFS data (Source: NASA Goddard Space Flight
Center, Maryland, USA and ORBIMAGE, Virginia, USA).
4CS 128/ES 228 - Lecture 8b
Spatial Data – A Few Definitions Spatial data: Data that have some form of spatial or
geographical reference that enables them to be located in two or three-dimensional space. -- Heywood, Cornelius & Carver, p. 289
Spatial data: Data that relate to the geometry of spatial features. -- Chang, Introduction to Geographical Information Systems, p. 4
Spatial data: Any information about the location and shape of, and relationships among, geographic features. This includes remotely sensed data as well as map data. -- The GIS Dictionary, http://www.geo.ed.ac.uk/agidict/welcome.html, searched 3/27/2007 (as of 11/11/2008, “temporarily unavailable”)
5CS 128/ES 228 - Lecture 8b
A Compromise
Geospatial Attribute Data
Data about a non-spatial entity that is intrinsically tied to a given
location
6CS 128/ES 228 - Lecture 8b
Examples of Geospatial Attribute Data• Rainfall • Snow depth• Land use• Crime rates• Average income level• Population statistics
7CS 128/ES 228 - Lecture 8b
What is special about this data?
Data sets are generally very large
Turning such data into information (or knowledge) can be tricky (or worse!)
Dimensionality becomes an issue
8CS 128/ES 228 - Lecture 8b
Dimensionality Paper maps are
generally two-dimensional
While color can be used as a third dimension, it is more often used for attribute display
9CS 128/ES 228 - Lecture 8b
Sometimes 2-D works
Source: U.S. Census Bureau, 2005 American Community Survey (American FactFinder)
10CS 128/ES 228 - Lecture 8b
More fine-grained 2-D
Image from: http://www.csc.noaa.gov/products/nchaz/htm/lidtut.htm
11CS 128/ES 228 - Lecture 8b
What’s the Weather Like in Merry Old England? Source
12CS 128/ES 228 - Lecture 8b
When 2-D tends to work
“Planar” area being mapped
One piece of data for each position
Minimal problem locating data in “space”
No “time” dimension
13CS 128/ES 228 - Lecture 8b
What about Time?
Traditionally described as a “fourth” dimension, time adds a “third” dimension to GIS data.
This creates problems converting the data to information and knowledge.
2-D maps usually don’t cut it.
14CS 128/ES 228 - Lecture 8b
Solutions to the “Time Dilemma”:1. Graphs
Source: National Weather Servicehttp://newweb.erh.noaa.gov/ahps2/hydrograph.php?wfo=buf&gage=olnn6&view=1,1,1,1,1,1
15CS 128/ES 228 - Lecture 8b
More graphing
http://www.pmel.noaa.gov/tao/disdel/disdel.html
Tropical Ocean Array
• Buoys in Pacific Ocean• Monitor Conditions• Monitor El Niňo
16CS 128/ES 228 - Lecture 8b
Custom Graphs from TOA Monthly Wind
Speed data for the buoy I selected
1977-2007
17CS 128/ES 228 - Lecture 8b
Also available as… Downloadable data file
Formatting can be an issue But if you add it to your GIS, it’s yours!
Location: 8S 165E 16 Aug 1991 to 16 Mar 2007 ( 188 times, 2 blocks) Gen. Date Mar 28 2007 Units: Winds (M/S), W. Dir (DEG), -99.9 = missing, (1,1) is NE at sqrt(2) m/s Time: 1200 16 Aug 1991 to 1200 16 Aug 1996 (index 1 to 61, 61 times) Depth (M): -4 -4 -4 -4 QUALITY YYYYMMDD HHMM UWND VWND WSPD WDIR SD 19910816 1200 -5.0 0.7 5.6 278.1 22 19910916 1200 -2.9 -1.4 4.8 243.7 22 19911016 1200 -2.7 -0.1 3.4 268.2 22 19911116 1200 -0.2 2.1 4.3 354.3 22 19911216 1200 -0.5 1.7 3.3 344.0 22 19920116 1200 1.8 1.3 4.2 53.8 22 19920215 1200 4.4 0.3 5.3 86.2 22 19920316 1200 4.0 1.0 5.3 75.7 22
18CS 128/ES 228 - Lecture 8b
Solutions to the “Time Dilemma”:2. Multiple Images Really just a set of 2-D images shown side-by-
side or in sequence
Source:http://commons.wikimedia.org/wiki/Image:ElectoralCollegeYYYY-Large.png
19CS 128/ES 228 - Lecture 8b
Items of note • Each of the images here is a separate report (or is it “map”?), no longer directly connected to a GIS
• Each map actually contains summary information as well as traditional map elements
20CS 128/ES 228 - Lecture 8b
Solutions to the “Time Dilemma”:3. Animation
http://encarta.msn.com/encyclopedia_761567360_1/Animation.html
Animation: motion pictures created by recording a series of still images—drawings, objects, or people in various positions of incremental movement—that when played back no longer appear individually as static images but combine to produce the illusion of unbroken motion.
21CS 128/ES 228 - Lecture 8b
My Daily Habit – Doppler DataAnimation
22CS 128/ES 228 - Lecture 8b
More Weather From England
http://www.xcweather.co.uk/
23CS 128/ES 228 - Lecture 8b
Watch My Friends Ride Across The Country http://stats.raceacrossamerica.org/2006/animation/
A similar site, with elevation profiles, exists for the Tour de France, but it only animates during the race
24CS 128/ES 228 - Lecture 8b
Get Seasick?
http://www.pmel.noaa.gov/tao/jsdisplay/
25CS 128/ES 228 - Lecture 8b
What if there is a real third dimension?
Actual images (video) But these can only show “transparent” or
“discrete” attribute data Flyovers/fly-throughs help
Virtual reality But most users don’t have the equipment
to “view” this
26CS 128/ES 228 - Lecture 8b
And in the movies…
(Screen snapshot of) Animation of tornado-monitoring “buoys” from the Warner Brothers film Twister
Source: http://www.vfxhq.com/1996/twister.html
27CS 128/ES 228 - Lecture 8b
Conclusions about geospatial data
• It’s abundant• It’s important• Display is a challenge• Technologies only get better
28CS 128/ES 228 - Lecture 8b
Great Data Sets Abound
• Census bureau• USGS• Weather Service• Scientific labs
(esp. government funded)