Intro. To GIS Midterm Review March 8 th , 2013

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Intro. To GIS Midterm Review March 8 th , 2013. Reminders. Lab on next Monday Try to catch up on homework assignments. Why Georeferencing?. Georeferencing. Georeferencing

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### Intro. To GISMidtermReviewMarch 8th, 2013

Reminders
• Lab on next Monday
• Try to catch up on homework assignments
Georeferencing
• Georeferencing
• The process of converting a map or an image (or scanned map) from one coordinate system to another by using a set of control points and a transformation equation.
• Two steps
• Coordinate transformation (scaling, rotating, skew)
• Resamping
Coordinate Transformation
• Methods
• First-order polynomial (Affine)
• 2nd Order polynomial
• 3rd order polynomial
• Spline

1st order

2nd order

>>Control points are used to estimate the coefficients (a0,b0,…)<<

Transformation types: Affine
• The affine transformation function is:
• x’ = Ax + By + Cy’ = 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
Example: Transformation
• Let’s 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 1st 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 >>>>

1

.5 , 8

Resampling
• Let’s continue on… After the transformation, the question is:
• What is the pixel value for .5 , 8???? (That’s what we call resampling)
• The new coordinate system is, in fact, a new raster dataset (right), which is slightly rotated, scaled, skewed, or distorted depending on the order of polynomial.
• We need to estimate pixel values from the original raster data (left/yellow dot), i.e., resampling, for the new dataset (right/green)

y’

y

2

3

3

1

2

1

73

78

78

2

70

74

80

1

3

68

69

65

coordinate

x

1

e.g., Average of 80 and 68 would be the pixel’s new value

Pixel value

2

x’

3

A bit of clarification on Optical RS

The end result is surface reflectance/temperature or a thematic map (classified map)

Midterm Overview
• Based primarily on lecture and homework/book
• Good knowledge of lab exercises helps!
• Closed notes, closed book, no computers
• Basic calculators
• Question types will include:
• Multiple choice
• True-False
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
Topology
• Concepts
• Enclosure
• Connectivity
• Terms to be defined
• Node
• Arc
• Polygon
Query
• A query is a “question” posed to a database (attribute data)
• Examples:
• Mouse click on a map symbol (e.g. road) may mean
• What is the name of road pointed to by mouse cursor ?
• Typing a keyword in a search engine (e.g. google, yahoo) means
• Which documents on web contain given keywords?
• SELECT ‘FROM Senator S’ WHERE S.gender = ‘F’ means
• Which senators are female?
Organizing Attribute Data
• Flat Files

Organizing Attribute Data

• Relational (What is commonly used in GIS)
• Various tables (databases) are “linked” through unique identifiers
Query: Making Selections
• Usually interested in some subset of the data
• Selections can be made in two primary ways:
• Select by Attribute – specify matching criteria
• Select by Location – based on spatial proximity
Select by Attribute Tips
• Be careful with case sensitivity and spaces
• Use parentheses to carefully construct a query
• Use “Boolean” Operators (AND, OR, NOT, LIKE)
• AND means both criteria, OR means either
• NOT allows you to exclude some criteria
• LIKE lets you be more flexible, use wildcard characters (_ for one character, % for many)
• Verify your expression to make sure it works
Selection Criteria (#8.8)

Per capita energy use > 4,000 AND population < 20,000,000

Selection Criteria (#8.8)

[Per capita energy use < 4,000 OR (population > 40,000,000)] AND (car theft <1)

Selection Criteria (#8.8)

Population < 20,000,000 OR car theft > 1.5