NRPI 377

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NRPI 377
Tues 9/13/2006
Week 4 Lecture 8
Today's Topic
Projected Coordinate Systems (State Plane)
Classification
Instructor Mike Gough E-mail GIS_at_mikegough.net

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Projected Coordinate Systems

• State Plane Coordinate System
• Only applicable in the U.S.
• Zones
• Defined by county, parish or other municipal
  boundaries.
• Different number of zones for each state.
• Sometimes identified by the Federal Information
  Processing System (FIPS) Codes.
• Two basic types of map projections
• The Lambert conformal Conic (for e w oriented
  states)
• Two standard parallels.
• Transverse Mercator (for n s oriented states).
• (Alaska also uses oblique Mercator).
• Units Feet (sometimes meters)
• Projection distortions are kept below 1 part in
  10,000

Minnesota
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Projected Coordinate Systems
Projections used for State Plane
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Projected Coordinate Systems
State Plane Zones By State
(Counties)
d
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Projected Coordinate Systems
State Plane Colorado North FIPS 0501
Establish a Zone Origin is usually established
2,000,000 ft to the west of the central meridian,
And at some distance to the south of the zone.
0,0
Distances from the origin are usually measured in
feet
2,164,606 feet E 392,285 feet N Col North
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Projected Coordinate Systems
State Plane California I FIPS 0401
Origin
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Eastings, Northings
,
,
,
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• Bolstad page 76
• Magnetic North and the geographic North Pole are
  in slightly different directions most places on
  Earth. This angular difference is called the
  magnetic declination and varies across the globe

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Classification

• Classification
• Process of grouping similar features together
  into classes or categories
• Use the same symbology to represent them.
• Classifications may be used to add to or modify
  the attribute data for each feature
• Example
• Polygons gt 1 square mile size value large
• Polygons from .1 to 1 square mile size value
  Mid
• Polygons lt .1 square mile size value small

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Classification

• Binary Classification
• Places features into two classes 0 or 1, true or
  false, etc.
• Example Parcel suitable for residential
  development or not?
• Is the parcel residentially zoned?
• Is the improvement value for the parcel 0
• Is the parcel within x meters of areas currently
  serviced by sewer and water?

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Classification

• Classifying data for display in ArcMap (symbology
  tab)

Categories For categorical (qualitative)
data Examples Nominal State name Ordinal size
(small, mid, large)
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Classification

• Classifying data for display in ArcMap (symbology
  tab)

Quantities For quantitative data Examples
(interval/ratio) Population Area Garbage
production
Quantitative data generally describes counts or
amounts, ratios, or ranked values. For example,
data representing precipitation, population, and
habitat suitability can all be mapped
quantitatively
Classes are distinguished by a numeric range.
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Classification

• Automatic Classification using a standard
  classification scheme or manual classification

Frequency Distribution and
Class Breaks
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Classification

• Standard Classification Schemes
• Natural breaks (Jenks) the default in ArcMap
• Equal interval
• Equal area
• Quantile
• Standard deviation
• Defined interval

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Classification Schemes

• Natural Breaks
• Classes are based on natural groupings inherent
  in the data.
• Group similar values maximize the differences
  between classes

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Classification Schemes

• Equal-interval
• The range is split into equal parts.
• Possible application to show that a store is
  part of the group of stores that made up the top
  one-third of all sales.

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Equal Interval Population by County
Outliers?
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Natural Breaks Population by County
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Classification Schemes

• Equal-area
• Class boundaries are set so that the total area
  of the polygons in each class is approximately
  the same
• Visually balanced map

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Classification Schemes

• Quantile
• Each class contains an equal number of features.
• Visually balanced map
• the resulting map can be misleading. Similar
  features can be placed in adjacent classes, or
  features with widely different values can be put
  in the same class.