Intro. To GIS Post Midterm Review March 25 th, 2013
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Vector vs. Raster CharacteristicVectorRaster Data
StructureUsually complexUsually simple Storage Requirements Small
for most datasets Large for most data Coordinate Conversion
SimpleMay be slow and require resampling Analysis Preferred for
network analysis Easy for continuous data, combining layers
Positional Precision Limited only by positional measurements
(scale) Floor set by cell size
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Vector Data Vector data represented by coordinates Points have
X and Y coordinate pairs Lines (arcs) connect two or more points
Polygons are a series of connected lines
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Raster Data Many cells make up a raster grid/image Size of
cells can vary Each cell has a value Think of a digital photograph
Pixels = cells
Datums Reference surfaces used for mapping Tied to a specific
ellipsoid Based on many precise measurements Both horizontal (e.g.
ellipsoid) and vertical (Geoid) datums Common US horizontal (2D)
datums: North American Datum (NAD) 1927 or 1983 World Geodetic
System of 1984 U.S. DOD (used worldwide)
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Earth Shape: Sphere and Ellipsoid
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Earth Models and Datums
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Horizontal Datums: Ellipsoids Bulge at the equator Flattened at
the poles A theoretical surface which fits the Earth best
(globally/regionally) Semi-major axis Semi-minor axis Flattening a
b
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Ellipsoid vs. Geoid Ellipsoids are idealized (mathematical)
models Geoids are more complex and representative (of the Earth
surface) Different ellipsoids work better in certain parts of the
world In North America, usually WGS 1984 or GRS 80
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Types of Projections Planar (Azimuthal) Cylindrical (Mercator)
Conical
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Review: Transverse Mercator (TM) Central Meridian Central
Meridian changes with the specific region for which the projection
is done
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Isopleth/Contour Map
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Question 14 Based on USGS standards, a 1:24,000 map scale has
24ft horizontal accuracy
Scale and Generalization Yellow generalization for smaller
scale maps
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03_19_Figure Spatial Resolution
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03_03_Figure Need at least 4 satellites to find X, Y, Z, and
error in receivers clock (Time) Need at least 4 satellites to find
X, Y, Z, and error in receivers clock (Time)
Sources of Errors When Positioning with GPS Standard
Positioning Service (SPS ): Civilian Users SourceAmount of Error
Satellite clocks:0.5 to 1 meter Orbital errors (ephemeris):< 1
meter Ionosphere:5.0 to 10.0 meters Troposphere:0.5 to 1 meter
Receiver noise:0.3 to 1.5 meters Multipath:0.6 to 1.0 meters
Selective Availability (SA)Does not exist any more User error:Up to
a kilometer or more Errors are cumulative and increased by DOP.
Note that the numbers are not current (absolute). However, you can
get a feel for which errors are more significant than the other
(relative).
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The satellites broadcast two types of data, Almanac and
Ephemeris. Almanac data is coarse orbital parameters for all SVs.
Each SV broadcasts Almanac data for ALL SVs (Satellite Vehicles).
This Almanac data is not very precise and is considered valid for
up to several months. Ephemeris data by comparison is very precise
orbital and clock correction for each SV and is necessary for
precise positioning. EACH SV broadcasts ONLY its own Ephemeris
data. This data is only considered valid for about 30 minutes. The
Ephemeris data is broadcast by each SV every 30 seconds. When the
GPS is initially turned on after being off for more than 30
minutes, it "looks" for SVs based on where it is based on the
almanac and current time. With this information, appropriate SVs
can be selected for initial search. When the GPS receiver initially
locks onto a SV, the Garmin display then shows "hollow" signal
strength bars. At this time, the Ephemeris data has yet to be
completely collected. Once the ephemeris data is collected from
EACH SV in turn, the associated signal strength bar will turn
"solid" black and then the data from that SV is considered valid
for navigation. If power is cycled on a GPS unit, and when turned
back on, the Ephemeris data is less than 30 minutes old, lock-on
will be very quick since the GPS does not have to collect new
Ephemeris data. Difference between Almanac and Ephemeris
Transformation types: Affine The affine transformation function
is: x = Ax + By + C y = Dx + Ey + F where x and y are coordinates
of the input layer and x and y are the transformed coordinates. The
C and F parameters control shift in origin (translation) A, B, D, E
control scale and rotation their values are determined by comparing
the location of source and destination control points. Scales,
skews, rotates, and translates 6 unknowns( A,B,C,D,E,F) so a
minimum of three displacement links required Little benefit from
more than 18-30 links The most common choice
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Vector Data and Topology Topology The arrangement for how
point, line, and polygon features share geometry Or knowledge about
relative spatial positioning Two types of vector models exist in a
GIS Geo-relational Vector Model Arc Coverage (has topology)
>>> format: binay Shape files (no topology)
>>>> format: *.shp, *.shx, *dbf, etc. Object-based
Vector Model Includes classes and geodatabases >>> format:
*.mdb
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Organizing Attribute Data Flat Files Hierarchical Relational
(databases) Object-oriented (database)
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Relational ( What is commonly used in GIS ) Various tables
(databases) are linked through unique identifiers Organizing
Attribute Data
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Non-spatial Data Or Attributes (for a vector dataset) Record
Field (Attribute)--- It could be either numeric or text) The Shape
Field/Object ID tells about the type of vector feature
(point/polygon/line) It is where the coordinates are also stored
(you do not see them here)
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add our one second error to the third receiver XX circle from
3rd satellite cannot intersect where other two do purple dots are
intersections of 2 satellites define area of solutions receivers
calculate best solution (add or subtract time from each satellite)
With Only Three Satellites Visible to the receiver
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position determined from multiple pseudo-range measurements 4
satellitesthree (X, Y, Z) dimensions and time when clock offsets
are determined, the receiver position is known Fourth
Satellite
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Q 33 and 34 Page 30 1 degree longitude: 111km * cos (phi)=81.2
km Page 31
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State Plane
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02_11_Figure UTM Coordinate System
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02_11_Figure Datum and UTM NAD83: (North American Datum)
produced in 1983 Q38 Page 38 Q39 Blocking of signal due to the
trees/branches, etc.
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Q 42
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Radiometric Resolution
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03_21_Figure Radiometric Resolution
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03_21_Figure Jpeg Vs. Tiss Jpeg is a lossy format Jpeg does not
inherently carry geo-coordinates
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Spectral Resolution
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Q 48 Land cover: nominal Temperature: interval Building
numbers: ordinal/nominal Population: ratio Check your email for
further discription
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Query: Select by Attributes Or Structured Query Language (SQL)
Enter criteria for one or more fields Numeric values =,, Nominal
values = text Change criteria or narrow results based on additional
criteria
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REVIEW: Joins and Relates Many datasets are available in
tabular format Excel (.xls,.xlsx), comma-spaced values (.csv), text
Tables can be imported to ArcMap and linked points, lines, or
polygons using a common ID
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REVIEW: Joining Tables Tables downloaded as text or CSV may
need to be opened and saved as Excel files first First row of table
should contain short headers with no special characters (or spaces,
ideally) Table must have an ID that matches geography
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REVIEW: One-to-one A one-to-one relationship means that each
record in one table has only one matching record in another
table
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REVIEW: Many-to-one Many-to-one means multiple records in the
table match to one record in another table
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REVIEW: Joining Tables Right-click the spatial data which will
have the table joined to it, click Joins and Relates, then Join
Choose the table and the common ID fields
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REVIEW: Spatial Join Join can be performed using spatial
location to summarize/select data from another layer Join data from
another layer based on spatial location option in the Join dialog
box Choose another layer to join, then Summarize numeric attributes
OR Give the attributes of the closest feature
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REVIEW: Relating Tables Relates are used when tables have a
one-to- many or many-to-many relationship Attributes are not
appended to the table, but selecting a record in one table will
select all related records in another table Right-click layer,
choose Joins and Relates, then Relate
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Q 53-54 Page 73 Use the formula to find out the specification
(dpi) for the scanner? dpi: Dot per inch Q54: ???
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Topology Concepts Adjacency Enclosure Connectivity Terms to be
defined Node Arc Polygon
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Non-spatial Data Or Attributes (for a vector dataset) Record
Field (Attribute)--- It could be either numeric or text) The Shape
Field/Object ID tells about the type of vector feature
(point/polygon/line) It is where the coordinates are also stored
(you do not see them here)
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REVIEW: Trade-off between Spatial and Spectral Resolution In
order to maintain a reasonable level of energy (or signal) reaching
the camera (or imaging system), the relation between the pixel size
(or pixel area) and spectral bandpass (channel width) must be
considered: Pixel area Spectral bandpass Energy
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Example: Transformation Lets do a simple example We would like
to calculate new coordinates for point A(x=1, y=1), i.e., we want
to convert coordinate system (x,y) to (x,y). We assume a 1 st order
(affine) transformation works fine All the six coefficients (for
affine transformation) are given (a0=1, a1=1.1, a2=0.4 and
b0=0.2,b1=1.8,b2=0.8) x and y are the new coordinates for (x,y) in
the new coordinate system Continue on next Slide
>>>>
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Resampling coordinate 68 65 70 80 Pixel value x x 78 7378 74 69
y 1 1 2 3 2 3 1 2 3 1 2 3 y e.g., Average of 80 and 68 would be the
pixels new value
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Orthophoto Vs. Aerial photos (or Remotely sensed Imagery)
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Homework & Lab Read chapter 4 (Data quality) and answer the
question: HW: all questions except Q1 and Q2 Lab this week: Review
on ArcGIS