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A friendly introduction to Geographic Information Systems

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The Mercator projection is often used for marine navigation as all straight lines on the map are lines of constant azimuth. – PowerPoint PPT presentation

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Title: A friendly introduction to Geographic Information Systems


1
What is GIS?
  • A friendly introduction to Geographic Information
    Systems
  • Marc Albrecht
  • University of Nebraska at Kearney
  • Department of Biology

2
Context Why GIS?
  • Many of the issues in our world have a critical
    spatial component!
  • Land management
  • Data on land values, taxation, assessment
  • Business site selection, advertising
  • Proximity of our land to other facilities
    (pollution, hunting, municipal, federal, state)
  • I dont know whats over that hill is a common
    problem. What is adjacent to the land we are
    using?

3
The Space on Earth
  • The Earth is finite!
  • If not now, within our lifetimes there may be no
    natural ecosystems.
  • Land managers, natural resource workers, and
    politicians are and will continue to make
    decisions about biological systems.
  • Good information and tools are needed to do this.

4
Enter GIS
  • A computer-based tool for holding, displaying,
    and manipulating huge amounts of spatial data.

5
Representing the World Projections
  • 3-D to 2-D (at first)
  • Projections change a round world into a flat one.

6
What is in a picture?
  • Example The Mercator projection has straight
    meridians parallels that intersect at right
    angles, as opposed to the Robinson projection.
  • Mercator preserves area only at the equator and
    at two standard parallels equidistant from the
    equator.
  • The Mercator projection is often used for marine
    navigation as all straight lines on the map are
    lines of constant azimuth.
  • Any one projection cannot simultaneously preserve
    all these qualities of the world shape, area,
    direction, and distance.

7
The Projection Problem
  • When working with GIS systems you have to know
    about projections in general and what projection
    the different data you are using are in.
  • It is possible to transform data from one
    projection to another, but is easier especially
    when starting out to have the different data
    layers in same projection when you obtain them!
    Agencies are generally helpful about doing this
    step for you if asked.
  • YOUR MAP LAYERS WILL NOT LAY ON TOP OF EACH
    OTHER, BUT RATHER BE SHIFTED INTO DIFFERENT
    AREAS!! This is embarrassing and frustrating.

8
This is what happens when projections mix!
  • Notice the boundary lines do not line up
  • Points that are placed on the wrong projection
    will be misaligned as well

9
How is all this done?
  • GIS stores data in a relational database
    structure (3-D spreadsheets)
  • e.g. employee names linked to store number, store
    number linked to shipment arrival
  • any data can be linked by a common attribute to
    any other data
  • Example shown here is a list of counties
    (geographic data) by income code (demographic
    data)

10
3-D Rendering Example
  • Elevation measurements can be easily converted
    into 3-D.
  • Such elevational data are collected regularly by
    federal and state agencies.
  • These data can be downloaded/ ordered at little
    or no cost.

USGS 7.5 Minute quad in 3-D
A 3-D rendering of the terrain
Beaty, NV
11
  • How many data points are contained in this image?
    Thousands? More?
  • Even without statistical measurement (which can
    be done) the pattern of pollution can be seen.
    Location and density of wells is also clear.
  • Line of sight analysis allows us to determine
    where to put a house or power plant where it
    could or could not be seen from major roads.
    Notice the roads actually track up the hills on
    the right side of the image.

12
1. Proximity Analysis
  • Two or more data layers are overlaid
  • GIS creates buffers around features on a
    particular layer
  • This allows analyses such as flood zone
    delineation and features near a route such as
    hotels along a bike route.

13
2. Query and Overlay Analyses
  • Query building is a data exploration operation
  • Example statement (acres gt 500 AND age gt
    55)
  • This would highlight all land parcels of greater
    than 500 acres owned by people older than 55
    years old in a data set loaded into the GIS.
  • Map algebra with raster data, in this type of
    operation mathematical operations are done on
    each pixel of multiple data layers. This results
    in a new data layer that is calculated from all
    the input layers.

14
The Global Positioning System
  • GPS

15
The Global Positioning System
  • A constellation of 24 high-altitude satellites
  • Cost over 12 billion US tax dollars

16
GPS Satellites
  • More than 24 up at all times.
  • Three atomic clocks per satellites.
  • Built to be resistant to blocking and jamming.

17
4 birds (as we say) for 3-D fix
18
GPS Uses
  • Natural Resource based
  • Animal/plant locations
  • Soil/water sampling locations
  • Human-based
  • Air and sea navigation
  • Emergency Services Locating
  • Airplane landing systems
  • Car-based direction services.

19
GeoSpatial Technology
20
Using Google Earth
Click here for a video tutorial of Google Earth
21
Using the CIA World Factbook
Click here for a video tutorial of the Cia World
Factbook
22
What can GIS do?
23
3. Spatial Analysis
  • Data can also be used to create surfaces
  • Other data uses
  • Density analysis
  • Proximity analysis
  • Least-cost paths
  • Line-of-sight
  • Hydrology analysis

24
Examples of GIS/GPS
  • Atlanta

25
Data Examples
  • Here is Atlanta
  • Highways
  • Roads
  • Census Tracts

26
  • Close up of downtown
  • Map contains data for each street
  • Each address in the city can be geocoded that
    is its location estimated in a systematic way
  • Length of each street segment - block
  • Streets can be sorted by length, name, income,
    home value, race, age - all provided by the
    Census Bureau (TIGER)

27
Atlanta Example
  • Hypothetical population of opossums.
  • Data can be sorted by attribute, such as sex,
    females are yellow in this example
  • Hmmm, why are males found closer to populated
    areas?
  • We do not know but how else would we discover
    the pattern?

28
Atlanta
  • Same population now reclassified by some other
    attribute.
  • a genetic marker?
  • age?, size?
  • Other operations
  • I can make a chart of any of the attributes.
  • I can compute density of points to see where the
    animals are most clustered
  • Measure distances between individual locations

29
The End!
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