Transcript Geographic Information Systems What is a Geographic Information System (GIS)? • A GIS is a particular form of Information System applied to geographical.

Geographic Information Systems
What is a Geographic Information
System (GIS)?
• A GIS is a particular form of Information
System applied to geographical data.
• An Information System is a set of
processes, executed on raw data to
produce information which will be useful
when making decisions.
• A system is a group of connected entities
and activities which interact for a common
purpose.
This discussion is derived from a seminar by Dr. David Waits
What is a Geographic Information
System (GIS)?
• An information system has a full range of
functions to:
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process observations
process measurements
provide descriptions
explain data
make forecasts
make decisions
What is a Geographic Information
System (GIS)?
• In a geographic information system,
information is characterized spatially.
• In a GIS the common purpose is decision
making to manage:
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land
resources
transportation
retailing
OR any other spatially distributed activity
What is a Geographic Information
System (GIS)?
• A GIS is an organized collection of
computer hardware, software, geographic
data, and personnel to efficiently capture,
store, update, manipulate, analyze, and
display all forms of geographically
referenced information.
• A GIS integrates spatial and other kinds of
information within a single system to
provide a consistent framework for
analyzing geographic (spatial) data.
What is a Geographic Information
System (GIS)?
• A GIS makes connections between
activities based on geographic proximity.
• The digital data structure can be
conceptualized as a set of “floating
electronic maps” with a common
registration allowing the used to “look”
down (drill down) and across the stack of
maps.
• The spatial relationships can be
summarized (data base inquiries)
What is a Geographic Information
System (GIS)?
• The spatial relationships can be
summarized (data base inquiries) or
manipulated (analytical processing).
• Another definition of GIS - An internally
referenced, automated, spatial information
system for data mapping, management,
and analysis
GIS Process
Capture
Data
Register
Map Base
Interpret
Data
Store Data
in Computer
Convert Data
to Digital
Process
Data
Format
Display
Results
Images
Image
Processing
System
Statistical
Reports
Maps
Map
Digitizing
System
Statistical
Analysis
System
Spatial Attribute
Data
Data
Base
Base
Database
Management
System
Geographic
Analysis
System
GIS
System
Cartographic
Display System
Maps
Statistics
Tabular Data
GIS - Map Stacking
NDVI From Aerial
Image
Nitrogen Availability
Estimate from
Aerial Photo
pH Layer
Geographic
Information
System
Courtesy of PPI
“Drilling Down” Through The Data Layers
Courtesy of PPI
GIS Data Formats
• There are two formats used by GIS
systems to store and retrieve
geographical data:
– Raster
– Vector
Raster Format
• Data are divided into cell, pixels, or
elements
• Cells are organized in arrays
• Each cell has a single value
• Row and Column Numbers are used to
identify the location of the cell within the
array.
• Perhaps the most common example of
raster data is a digital image.
Vector Format
• Data are associated with points, lines, or
boundaries enclosing areas
• Points are located by coordinates
• Lines are described by a series of
connecting vectors (line segments
described by the coordinates of the start
of the vector, its direction, and magnitude
or length).
• Areas or polygons are described by a
series of vectors enclosing the area.
Vector Format
• Any number of factors or attributes can be
associated with a point line or polygon.
• Data are stored in two files:
– a file containing location information
– a file containing information on the attributes
• A third file contains information needed to
link positional data with their attributes.
Vector and Raster Representation
of Point Map Features
Map Feature
GIS Vector
Format
(X,Y)
Coordinate in space
GIS Raster
Format
Cell Located
in an Array
Vector and Raster Representation
of Line Map Features
Map Feature
GIS Vector
Format
GIS Raster
Format
Vector and Raster Representation
of Area Map Features
Map Feature
GIS Vector
Format
GIS Raster
Format
Vector and Raster Formats
• Most GIS software can display both vector and
raster data.
• Raster formats are efficient when comparing
information among arrays with the same cell size.
• Raster files are generally very large because each
cell occupies a separate line of data.
• Vector formats are efficient when comparing
information whose geographical dimensions are
different.
Comparison of Raster and Vector
Formats
Raster
• Raster formats are efficient
when comparing
information among arrays
with the same cell size.
• Raster files are generally
very large because each
cell occupies a separate
line of data, only one
attribute can be assigned
to each cell, and cell sizes
are relatively small.
Vector
• Vector formats are efficient
when comparing
information whose
geographical shapes and
sizes are different.
• Vector files are much
smaller because a
relatively small number of
vectors can precisely
describe large areas and a
many attributes can be
ascribed to these areas.
Comparison of Raster and Vector
Formats
Raster
• Raster representations are
relatively coarse and
imprecise
Vector
• Vector representations of
shapes can be very
precise.
Most GIS software can display both raster and
vector data. Only a limited number of programs
can analyze both types of data or make raster type
analyses in vector formats.
Coordinate Systems
• Spatial data are generally recorded as
latitude and longitude, frequently as
decimal degrees.
• Other systems commonly used are the
Universal Transverse Mercatur - UTM and
State Plane Coordinates. These systems
are projections of the curved surface of
the globe on to a plane surface.
Coordinate Systems
• UTM, the preferred system, distance unit
is the meter.
• The unit of the state plane system is the
foot.
• There is generally a different coordinate
system for each state in the state plane
system.
• In the UTM system projections are made in
zones of approximately 6 degrees of
longitude.
Coordinate Systems
• There are two datums (reference planes)
commonly used to make projections:
North American Datum of 1927 (NAD27)
and the World Geographic Reference
System of 1984 (WGS84). The WGS84
datum can be used world wide. The
default datum of many GPS receivers is
the WGS84 datum.
UTM Zones
Longitude
Range
78-84
84-90
90-96
96-102
102-108
108-114
114-120
Zone
17 N
16 N
15 N
14 N
13 N
12 N
11 N
Tulsa
Stillwater
UTM Specifications
• UTM position is specified by:
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Number of the Zone
North (or South) of the equator
East of the western boundary of the zone
Distances are in meters
• Coordinates are referred to as “Northings”
and “Eastings”
– N xxxxxx, E yyyyyy
Interpolation to Predict Missing
Data
• Frequently, data are collect at discrete
points located a significant distance apart
or some of the data are missing.
• Interpolation is used to predict the values
of the missing data.
• There a number of interpolation
algorithms available in SST Toolbox and
other software.
Interpolation Algorithms
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Nearest neighbor
Local Averaging
Inverse distance to a power
Radial bias functions
Shepard’s Method
Kriging
AND
• Simple Contouring
What is the effect of the interpolation
algorithm on the estimate of missing data?
Efaw 1x1 Phosphorus
Selected Missing Data
60-70
ppm
50-60
Distance, ft
66
61
56
51
46
41
36
31
26
21
16
11
6
1
6
1
40-50
30-40
20-30
10-20
0-10
Nearest Neighbor
Missing Data
• Value of the nearest
measurement to the
missing data.
• In the case of values
at the same distance,
the average of those
values
Nearest
Neighbor
Local Average
Missing Data
• Average of all values
within a predetermined
distance.
Averaged
Values
Inverse (Weighted) Distance
Search Radius < 3 ft
• Values are weighted
by the inverse of
their distance from
the missing value.
The weights can be
raised to a power.
The interpolated
value is equal to the
sum of the weighted
values divided by
the sum of the
weights.
Missing Data
Inverse (Weighted) Distance
Missing Data
W=1
W = 0.707
W = 0.5
W = 0.447
W = 0.354
Missing Values and Predicted Values
Phosphorus at Efaw
Missing Value
Phophorus, ppm
60
Nearest Neighbor
Average
Inverse Dist.
50
40
30
20
10
0
5
10
15
20
25
30
35
40
45
50
Missing Element Location, ft
55
60
65
Absolute Error, %
Error In Predicting Missing Data
100
80
Nearest Neighbor
60
Average
Inverse Distance
40
20
0
5
10 15 20 25 30 35 40 45 50 55 60 65
Element Location
Comparison on Interpolation Algorithms
Nearest
Neighbor
Average of
Adjacent
Elements
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17.3
Inverse
Distance
Radius<3ft
% Error ____________________________
23.1
19.5
Phosphorus, ppm
Prediction by Linear interpolation Between
Every Fifth Data Point
Efaw 1 by Experiment
70
60
50
40
30
20
10
0
Trans 4
Fifth Data Point
0
20
40
Distance, ft
60
80