Assignment 3

• Cartographic Modeling– Raw Spatial Data Map Product for Decision Making

• Steps– Define Goal– Define important social or biophysical factors– Select modeling method– Develop database– Process data to create new information if needed– Convert factor data to reflect relative Value to Goal – Combine environment factor valuations to create final

map.– Visualization

Process

• Goal: Create a habitat map for B. pondesii• Define Factors:

– Vegetation Type – likes hardwoods– Water – lives near ponds– Human Use – avoid human use areas

• Select Modeling Method: Binary Combination• Develop Database:

– Human Use: Roads, Town– Water: Water– Vegetation Type: Trees

Process• Process data if needed

– Reclassify Water create Ponds (1, Nodata)– Find Euclidean distance from ponds– Reclassify Town and Roads (1, Nodata)– Find Euclidean distance from both Town and Roads (using reclasses)– Combine Euclidean distance grids for Town and Roads using MIN

function to get the minimum distance from either (i.e. MinDist)• Convert factors to relative values (Binary: 1,0)

– Hydro = Con(Euc_pond == 0, 0, Con(Euc_pond <= 500, 1,0))– Hardwood = Con(Trees == 1, 1,0)– Human = Con(MinDist <= 150, 0,1)

• Combine factors using different local operators– Boolean: AND, OR– Arithmetic: + – Combinations

Euclidean Distance • Minimum distance from a source (Value <> NoData)• Input grid must have at least one source cell with the rest of

the grid being NoData.• Global Function

51520 y

Point 1

10, 15

Point 2

15,20

51015 x07.755 2222 yxD

Euclidean Distance

Source Cells have values. All other cells have NoData.

Output represents the minimum distance to any source cell.

Distance is in map units.

Boolean Logic

• All queries use Boolean Logic.

• Boolean logic involves True/False sets (Yes/No, 1/0) on which Boolean logical operators (or connectors) such as AND, OR, NOT and XOR can be applied.

• Going back to basic set theory, a group of individuals are either in a specific set or not.

• With Grids 0 = “not in set”, all other values indicate a cell is in the specified set. I always create a 1/0 Conditional Grid.

• NoData in a Grid will return NoData.

Boolean Operators

• AND, OR, XOR, NOT

AND

Decreasive

Controlled by Low Values

1 0

0 1

1 0

1 0AND1 0

0 0=

A B

A B

Boolean Operators

• AND, OR, XOR, NOT

OR

Increasive

Controlled by High Values

1 0

0 1

1 0

1 0 OR1 0

1 1=

A B

A B

Boolean Operators

• AND, OR, XOR, NOT

XOR

In A OR B, but not in

A AND B.

1 0

0 1

1 0

1 0XOR0 0

1 1=

A B

A B

Boolean Operators

• AND, OR, XOR, NOT

NOT

In A, but NOT B.

1 0

0 1

1 0

1 0NOT0 0

0 1=

A B

A B

Reclassification Methods

• Lookup – based on VAT attributes• Reclassify – new to 9.2• Con Function

Lookup• Creates a new raster by looking up values found in

another field in the table of the input raster. • Inputs: Input Raster, Field, Output Raster.• Field must be numeric; Integer or Floating Point. • Input must be integer, Output can be either.

Value Count Attr1

1 294 1

2 345 8

3 654 3

Input

Value Count

1 294

8 345

3 654

Output

Reclassify• Reclassifies or changes the values in a raster. • Inputs: Input Raster, Field, Reclassification Method,

Output raster.• The input can be any numerical type.• The output raster will always be of integer type.• Many reclassification methods available, including

Remap Tables created in the Reclassify tool.• You are putting all the input data into classes. The

reclassification scheme must be inclusive, else the algorithm will make classes using the remaining values through truncation.

Reclassify Algorithm

• You define thresholds from reclassification, the algorithm then applies a local conditional If/Else statement to the information.

• Basic If/Else formulation (to create 3 classes):

If (input value is):>= Minimum Value - <= Threshold 1 = Class 1

Else > Threshold 1 - <= Threshold 2 = Class 2

Else > Threshold 2 - <= Maximum Value = Class 3

Con

• Also Conditional approach.• Can be based on more than one input raster.• Local function.• Input and Output can be any numerical type.

– Con can be used to create a floating point output.

• Should also be inclusive, else undefined values will be converted to NoData.

CON Function• CONditional Expression • One of the most powerful local map algebra functions.• Apply in Single Output Map Algebra Function or Raster

Calculator • Basic Format:

– Output = CON (Condition, True_expression, False_expression)• Examples

– Output = con(input1 > 5, 10, 100)– Output = con(input1 > 5, 10) – Output = con(input1 < 5, 10, con(input1 < 15, 50, 100))– Ouput = con((input1 + input2) < = 5, sin(input1), cos(input2))

Examples of Con Function

• Outgrid = con(Ingrid > 5, 10, 100)

4 6

8 5

Ingrid

100 10

10 100

Outgrid

Examples of Con Function

• If no value or expression is specified for the false expressions:

– Outgrid = con(Ingrid > 5, 10)

the results will be the same as the above output except the cells that have a value of 5 or less Ingrid will be assigned NoData in Outgrid.

Examples of Con Function

• Multiple conditional statements can be used within the Con function, but each must have a value or expression that can be used to assign values to the output cells if the result of the evaluation of the condition is true.

– outgrid = con(Ingrid1 < 5, sin(Ingrid1), con(Ingrid1 < 20, cos(Ingrid1), con(Ingrid1 > 50, 100, 0)))

• The function is sequential, so the second condition will

acknowledge the first condition.• How would the outgrid cells be defined for Ingrid1 values

between 20 and 50?