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Fundamentals of
Geographic Information Systems
and Spatial Data
Laurie Schretlen & Leah Vanderjagt
Netspeed October 20, 2005
GIS & Spatial Data - Today
 Introduction to Geographic
Information Systems (GIS)
technology: basics, applications, and
directions
 Spatial data: information resources
for GIS research
 Spatial data access –
 in Canada and in Alberta
 GEODE
GIS Components
 Map data
 Information about location w/graphics
http://www.zoology.unimelb.edu.au/stats/Eworksheets/images/RandomCoordinates.jpg
GIS Components:
 Attribute
data
 Information
about what
can be
found at a
particular
location
http://www.extension.umn.edu/distribution/naturalresources/images/5740f02.gif
http://utca.eng.ua.edu/projects/final_reports/02403fnl_files/image004.jpg
GIS as database
Spatial data examples
 Road networks
 Vegetation inventories
 Soil inventories
 Census results
 Municipal boundaries
 Elevation values
 Climate readings
 Habitat ranges
 …
GIS Components
 Software
 A technology for storing and analyzing
location and attribute data
http://www.l.hsr.ch/skripte/gisscripts/media/softwarescreen1.jpg
GIS Components
 Hardware
 Systems to support rapid graphic
analysis and processing
http://www.gdf-hannover.de/pics/gisrechner.png
GIS Personnel
 People
 Project coordinators
 Data analysts
 Programmers
 Data and knowledge managers
Librarians
GIS Components
 Methods
 The analysis to be performed on the
data
http://www.wwf.org.co/colombia/images/a28_c.gif
GIS Methods and Analysis
 GIS is used to answer questions
and support decisions
 The quality of the answer depends
on:
 The METHODS chosen
 The DATA (more on that later)
Data Layers
Topography
Hydrography
Census
Highways
Places
 The ability to
‘stack’ layers
in a GIS
allows us to
ask questions
about the
relationship
between
different
objects of
study
Image courtesy of Charlene Nielsen, Department of Biology, University of Alberta
Overlay
 What two things occur at the same
location?
http://www.orthogate.com/guide/workshops/images/image002.gif
Overlay – GIS
 What residences lie beneath this toxic
plume of ammonia?
Overlay GIS
http://www.saultc.on.ca/GIS/images/RedPineTraill_sm.jpg
Buffering
 What lots are located near this road?
http://news.sina.com.cn/duihua/sars/LearnMoreAboutGIS/gis4.files/buffer.gif
Modeling
 GIS is used to ask ‘what if?’
 Testing scenarios and possible
outcomes
Modeling
Image created by Leah Vanderjagt, 2005: Data: NRCan CDED; City of Edmonton 2001 Digital Orthophotos
Modeling - Site Selection
 Combining best conditions from
multiple layers to come up with the
best location for a proposed facility
 Eg. Good slope drainage + enough
distance from streams + access to
roads = Best site
Modeling
GIS Applications
 GIS applications combine multiple
analytical processes to support
decision-making
 Some examples from non-profit and
government sectors:
Habitat tracking and analysis
maps.gov.bc.ca/imf406/imf.jsp?site=libc_habwiz
www.shim.bc.ca/atlases/shim/shim.htm
Health Care: Disease outbreak
monitoring and modeling
Dispersion of Avian Flu in Thailand
Affected and at-risk poultry farms
Avian Flu
http://www.gisdevelopment.net/application/health/links/ma04184pf.htm
SARS Mapping
Distribution map
Outbreak model – Buffalo, NY
Facilities Management for
Municipal Government
Route Optimization Modeling
Crime Analysis
Other uses
 Many groups still need to create
paper maps to support operations -
nearly always GIS-based
 GIS is also used for storage of
information – there is an archiving
function
Directions for GIS
 WEB APPLICATIONS
 Standards
 Unlocking the GIS black box -
distributed experimentation and
collaboration
 GIScience
GIS in Academic Institutions
 GIS is used extensively in
science/ecology disciplines:
 Renewable resources management
 Forestry
 Biology (ecology)
 Geography
 Earth and atmospheric sciences
 Geology
GIS in Academic Institutions
 Also used in:
 Civil engineering
 Business
 Economics
 History
 Psychology
 Health
 …
GIS and Libraries
 Community demographic analysis
GIS - Bibliography
Spatial data access
 ‘Map’ + ‘Attribute’ data is usually
referred to as spatial data
 Locating the right spatial data and
obtaining the rights to use it is a
major component of every GIS
project
Spatial data quality: Inconsistencies
Spatial data quality: Projections
http://www.colorado.edu/geography/gcraft/notes/mapproj/gif/twoproj.gif
Spatial data access
 Spatial data is expensive to create
and update
 Government agencies and large
corporations can afford it
 Data sharing is not necessarily a
part of the plan
Spatial data access
 If it’s shared, spatial data is either sold
by the producer or by a designated
value-added reseller
 Public consultations have resulted in
open sharing of more and more spatial
data sets at the federal level
 Some federal data is made available
through the Depository Services
Program
Canadian Geospatial Data Infrastructure
Spatial data access
 There is much more data available for
purchase
 Therefore, there is a spatial data
economy in Canada
 This economy is driven by cost-recovery
policies
 Government agencies charge other
agencies, corporations, and individuals for
data access
Different models of access
 United States – wide, very open
access to drive commercial
development
 Canada – stewardship model of cost-
recovery
 Provincial economy examples:
 Manitoba
 Alberta
Alberta Policy Environment
 Government agencies: cost-recovery
sales
 Third party vendors: data enhancers
and resellers for profit
 Data producers who do not sell or
distribute their data
Challenges to Access
 What is the result of Alberta’s policy
environment?
 Data creators don’t have sufficient
resources to respond to individual
researcher demand
 Data suppliers do not document or
support data products
 Data suppliers’ primary business is
not data supply, ie. creating happy
data customers
Post-secondary Response
 “Underground data economy” – have and
have-not departments at one institution
 Some data creators provide data in
exchange for research results
 Individuals or projects receive licenses for
data; cannot be shared with institution
 Academic libraries began to acquire data
through license (database model)
 Successful examples: NRCan, DMTI
GEODE
 To address issues of access to spatial
data in Alberta, the GEODE project
was launched in 1999
 Participating institutions:
 University of Alberta
 University of Calgary
 SAIT
 University of Lethbridge
 Miistakis Institute for the Rockies
GEODE
 Access to Alberta-based spatial data
 Digital elevation models
 Topographic data
 Alberta Vegetation Index
 Census boundaries
 Landsat 7 imagery
 Metadata development
 Data browser
 10,000+ files downloaded
Benefits to GIS Researchers
 Consortium-wide access to high quality
data
 Centralized price and acquisition
negotiations
 The opportunity to work with industry-
standard Alberta data
Benefits to suppliers
 One point of access for post-
secondary institutions
 Data support coordinated through
library and departments
 Institutional licensing
 Training of future employees with
industry standard data
GEODE’s Transformation
 GEODE was reconceived in late 2004
as a consortium – to facilitate and
promote access to spatial data for
post-secondary education in Alberta
 Objectives:
 Develop new funding strategies
 Enhance contents of collection
 Expand institutional membership
Benefits of institutional membership
 Access to GEODE collections
 Training and assistance with GEODE
service delivery
 Advocacy and liaison with vendors
 Cost-sharing
 Technology/infrastructure guidance
 Collaborative development of best
practices
GIS for Post-secondary Education
 For access to spatial data for GIS
research and teaching to continue
and thrive in Alberta, academic
libraries need to collaborate to:
 Develop spatial data collections
according to shared research priorities
 Lobby for access with producers and
vendors
 Share resources and expertise
Moving forward
 Long-range technology goal:
database-driven web service delivery
of spatial data files
 GEODE is seeking assistance with the
development of a province-wide
licensing model for spatial data use in
research and teaching
Questions? Discussion?
Laurie Schretlen – lschretl @ ucalgary.ca
Leah Vanderjagt – leahv @ ualberta.ca
Web Citations
 Google Local: www.google.ca
 Google Earth: earth.google.com
 BC Habitat Wizard:
maps.gov.bc.ca/imf406/imf.jsp?site=lib
c_habwiz
 Sensitive Habitat Inventory and
Mapping:
www.shim.bc.ca/atlases/shim/shim.htm

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Netspeed-GIS (1).ppt

  • 1. Fundamentals of Geographic Information Systems and Spatial Data Laurie Schretlen & Leah Vanderjagt Netspeed October 20, 2005
  • 2. GIS & Spatial Data - Today  Introduction to Geographic Information Systems (GIS) technology: basics, applications, and directions  Spatial data: information resources for GIS research  Spatial data access –  in Canada and in Alberta  GEODE
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  • 9. GIS Components  Map data  Information about location w/graphics http://www.zoology.unimelb.edu.au/stats/Eworksheets/images/RandomCoordinates.jpg
  • 10. GIS Components:  Attribute data  Information about what can be found at a particular location http://www.extension.umn.edu/distribution/naturalresources/images/5740f02.gif
  • 12. Spatial data examples  Road networks  Vegetation inventories  Soil inventories  Census results  Municipal boundaries  Elevation values  Climate readings  Habitat ranges  …
  • 13. GIS Components  Software  A technology for storing and analyzing location and attribute data http://www.l.hsr.ch/skripte/gisscripts/media/softwarescreen1.jpg
  • 14. GIS Components  Hardware  Systems to support rapid graphic analysis and processing http://www.gdf-hannover.de/pics/gisrechner.png
  • 15. GIS Personnel  People  Project coordinators  Data analysts  Programmers  Data and knowledge managers Librarians
  • 16. GIS Components  Methods  The analysis to be performed on the data http://www.wwf.org.co/colombia/images/a28_c.gif
  • 17. GIS Methods and Analysis  GIS is used to answer questions and support decisions  The quality of the answer depends on:  The METHODS chosen  The DATA (more on that later)
  • 18. Data Layers Topography Hydrography Census Highways Places  The ability to ‘stack’ layers in a GIS allows us to ask questions about the relationship between different objects of study Image courtesy of Charlene Nielsen, Department of Biology, University of Alberta
  • 19. Overlay  What two things occur at the same location? http://www.orthogate.com/guide/workshops/images/image002.gif
  • 20. Overlay – GIS  What residences lie beneath this toxic plume of ammonia?
  • 22. Buffering  What lots are located near this road? http://news.sina.com.cn/duihua/sars/LearnMoreAboutGIS/gis4.files/buffer.gif
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  • 24. Modeling  GIS is used to ask ‘what if?’  Testing scenarios and possible outcomes
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  • 27. Image created by Leah Vanderjagt, 2005: Data: NRCan CDED; City of Edmonton 2001 Digital Orthophotos
  • 28. Modeling - Site Selection  Combining best conditions from multiple layers to come up with the best location for a proposed facility  Eg. Good slope drainage + enough distance from streams + access to roads = Best site
  • 30. GIS Applications  GIS applications combine multiple analytical processes to support decision-making  Some examples from non-profit and government sectors:
  • 31. Habitat tracking and analysis maps.gov.bc.ca/imf406/imf.jsp?site=libc_habwiz
  • 33. Health Care: Disease outbreak monitoring and modeling Dispersion of Avian Flu in Thailand Affected and at-risk poultry farms Avian Flu http://www.gisdevelopment.net/application/health/links/ma04184pf.htm
  • 34. SARS Mapping Distribution map Outbreak model – Buffalo, NY
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  • 39. Other uses  Many groups still need to create paper maps to support operations - nearly always GIS-based  GIS is also used for storage of information – there is an archiving function
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  • 41. Directions for GIS  WEB APPLICATIONS  Standards  Unlocking the GIS black box - distributed experimentation and collaboration  GIScience
  • 42. GIS in Academic Institutions  GIS is used extensively in science/ecology disciplines:  Renewable resources management  Forestry  Biology (ecology)  Geography  Earth and atmospheric sciences  Geology
  • 43. GIS in Academic Institutions  Also used in:  Civil engineering  Business  Economics  History  Psychology  Health  …
  • 44. GIS and Libraries  Community demographic analysis
  • 46. Spatial data access  ‘Map’ + ‘Attribute’ data is usually referred to as spatial data  Locating the right spatial data and obtaining the rights to use it is a major component of every GIS project
  • 47. Spatial data quality: Inconsistencies
  • 48. Spatial data quality: Projections http://www.colorado.edu/geography/gcraft/notes/mapproj/gif/twoproj.gif
  • 49. Spatial data access  Spatial data is expensive to create and update  Government agencies and large corporations can afford it  Data sharing is not necessarily a part of the plan
  • 50. Spatial data access  If it’s shared, spatial data is either sold by the producer or by a designated value-added reseller  Public consultations have resulted in open sharing of more and more spatial data sets at the federal level  Some federal data is made available through the Depository Services Program
  • 51. Canadian Geospatial Data Infrastructure
  • 52. Spatial data access  There is much more data available for purchase  Therefore, there is a spatial data economy in Canada  This economy is driven by cost-recovery policies  Government agencies charge other agencies, corporations, and individuals for data access
  • 53. Different models of access  United States – wide, very open access to drive commercial development  Canada – stewardship model of cost- recovery  Provincial economy examples:  Manitoba  Alberta
  • 54. Alberta Policy Environment  Government agencies: cost-recovery sales  Third party vendors: data enhancers and resellers for profit  Data producers who do not sell or distribute their data
  • 55. Challenges to Access  What is the result of Alberta’s policy environment?  Data creators don’t have sufficient resources to respond to individual researcher demand  Data suppliers do not document or support data products  Data suppliers’ primary business is not data supply, ie. creating happy data customers
  • 56. Post-secondary Response  “Underground data economy” – have and have-not departments at one institution  Some data creators provide data in exchange for research results  Individuals or projects receive licenses for data; cannot be shared with institution  Academic libraries began to acquire data through license (database model)  Successful examples: NRCan, DMTI
  • 57. GEODE  To address issues of access to spatial data in Alberta, the GEODE project was launched in 1999  Participating institutions:  University of Alberta  University of Calgary  SAIT  University of Lethbridge  Miistakis Institute for the Rockies
  • 58. GEODE  Access to Alberta-based spatial data  Digital elevation models  Topographic data  Alberta Vegetation Index  Census boundaries  Landsat 7 imagery  Metadata development  Data browser  10,000+ files downloaded
  • 59. Benefits to GIS Researchers  Consortium-wide access to high quality data  Centralized price and acquisition negotiations  The opportunity to work with industry- standard Alberta data
  • 60. Benefits to suppliers  One point of access for post- secondary institutions  Data support coordinated through library and departments  Institutional licensing  Training of future employees with industry standard data
  • 61. GEODE’s Transformation  GEODE was reconceived in late 2004 as a consortium – to facilitate and promote access to spatial data for post-secondary education in Alberta  Objectives:  Develop new funding strategies  Enhance contents of collection  Expand institutional membership
  • 62. Benefits of institutional membership  Access to GEODE collections  Training and assistance with GEODE service delivery  Advocacy and liaison with vendors  Cost-sharing  Technology/infrastructure guidance  Collaborative development of best practices
  • 63. GIS for Post-secondary Education  For access to spatial data for GIS research and teaching to continue and thrive in Alberta, academic libraries need to collaborate to:  Develop spatial data collections according to shared research priorities  Lobby for access with producers and vendors  Share resources and expertise
  • 64. Moving forward  Long-range technology goal: database-driven web service delivery of spatial data files  GEODE is seeking assistance with the development of a province-wide licensing model for spatial data use in research and teaching
  • 65. Questions? Discussion? Laurie Schretlen – lschretl @ ucalgary.ca Leah Vanderjagt – leahv @ ualberta.ca
  • 66. Web Citations  Google Local: www.google.ca  Google Earth: earth.google.com  BC Habitat Wizard: maps.gov.bc.ca/imf406/imf.jsp?site=lib c_habwiz  Sensitive Habitat Inventory and Mapping: www.shim.bc.ca/atlases/shim/shim.htm