Attributes & Queries

Reading Assignment: Bolstad, Ch. 8 (p. 307-346)

Attributes

• To make decisions we need information about the spatial areas in Shapefiles:– Which parcels are big enough for my house?– Which areas have more poverty for development

funds?– Where environmental areas are threatened by

encroaching development?– How many endangered species are in each area?– How many fish are in each stream?– Who borders the streams we need to restore?– Which areas of the most fire fuels (dead wood)?

Attributes

• To answer questions we need information:– Counts of species– Counts of people, animals, houses, etc.– Height of trees, buildings, etc.– Size and perimeter of areas– Length of streams, roads– Ownership of parcels

• These are held in attributes

Census Scope

• An organization making census information available

• http://www.censusscope.org• Check out the variety of maps, charts, and tables

they have made available from US census data. • These are computed using attributes of the

census data at a county level (i.e. a polygon layer of counties).

Queries and Calculations

• We also need to select (query) certain types of information:– People over 60 years old– Parcels over 1 acre– Areas with 1 or more endangered species

• And compute new values:– Number of animals per meter– Density of trees– Board feet per acre– Fish per meter

Attributes, Queries, Calculations

• Attributes are associated with features – In the Attribute table

• Queries “Select” data – Available in “Select by Attribute”– Based on Structured Query Language (SQL)

• Calculations available in:– Geometry calculator– Field (column) calculator

Attributes

• Table attached to each layer• Each row tied to a feature

– Point– Polyline(s)– Polygon(s)

• Each column (field) represents a different attribute and has:– Name– Type– Other properties

Attribute Terminology

Attribute “Table”

Row or Record- One per feature

Column or Field

Feature, Object, or Record ID

Attribute Terminology

• Esri borrows from four disciplines for labels for attributes

Spatial Data Spreadsheet Database OOP

Attribute Table Spreadsheet Table -

An attribute Column Field Property

Feature ID? Row Number Record ID Object ID

Attributes for one feature

Row Record Object’s properties

Attribute value Cell Entry Property Value

Filter Selection Query -

Attributes

• Vector Attributes (very common)• Raster Attributes (when available)• Examples of attributes:

– Name– Population/Census numbers– Vegetation characteristics– Dates– Coordinates– Ownership– Park Type

Vector Attributes

• Used For:– Labels:

• Direct: Names of cities, states, etc.• Results of “expressions”: City with it’s population

– Symbology:• Size city by it’s population

– Selection• Select cities over a certain size

– Sub-setting• Create a new layer with cities over 1 million

Types of Attributes

• Qualitative– Nominal: No order, types

• Quantitative– Ordinal: Ordered set of classifications– Interval: Values along arbitrary scale– Ratio: Values along non-arbitrary scale– Cyclic: Values repeat

Types of Attributes (examples)

• Qualitative– Nominal: Land Cover Type

• Quantitative– Ordinal: Fire danger low, medium, high– Interval: Temperature– Ratio: Population Density (floating point)

• Number of People / Area– Cyclic: Directions (0 to 360 degrees)

Examples of Attributes

• Names• Taxonomic Identification:

– Scientific Names, common names, codes (NRCS codes)

• Organism characteristics• Population values• Distance, Area• Dates• Collector’s names• Coordinates

Structured Query Language (SQL)

• Comes from the database industry• “INSERT”, “DELETE”, and “SELECT” rows in

tables• Very rich syntax• Portions of “SELECT” grammar used heavily

in ArcGIS:– Selecting attributes– Raster calculator– Geodatabases

Select by Attributes

• SELECT * FROM TableName WHERE:– “WHERE Clause” or Filters

• Available from the Attribute Table

Attributes in ArcGIS

Filter Examples

• WHERE:– FID = 1– “Area” < 10000– “Area” <= 10000– “Name” = ‘Crater Lake’ (case dependent)– “Name” LIKE ‘Crater Lake’ (ignores case)

• Notice:– Fields have double quotes– String values have single quotes

SQL Comparisons

• Equals: =• Greater than: >• Less than: <• Greater than or equal: >=• Less than or equal: <=• Not equal: <>• Like: case independent string comparison with

wild cards (%)

Boolean Values

• True = T = 1 • False = F = 0

Boolean Operators

A B A AND B A OR B NOT A NOT B

T T T T F F

T F F T F T

F T F T T F

F F F F T T

More Complex Filter Examples

• WHERE:– “Name” LIKE ‘Hawaii’ AND Area < 10000– “Species” LIKE ‘Ponderosa’ AND DBH > 1

Select by Location

• Proximal• Topological

– Identical– Adjacent– Within– Share segment

Table Queries:The selection of a subset of features that meet some criteria.

“Area” > 20.0 “Landuse” = ‘Urban’ AND “Municip” = ‘City’

Expression: A sequence of operands and operators constructed according to the syntactic rules of a symbolic language (SQL)

Boolean Operators: Used to combine expressions

1) And

2) Or

3) Not

4) Xor

“AREA” > 10000 AND “IMPR” = 0

“RAINFALL” < 20 OR “SLOPE” > 35

NOT ("STATE_NAME" = ‘Colorado’)

[RAINFALL] > 20 XOR [SoilType] = ‘X’

Order matters:

(A AND B) OR C is not the same as

A AND (B OR C)

And – Must meet both criteriaOr – Can meet either criteria

Boolean Operators: Used to combine expressions

1) And

2) Or

3) Not

4) Xor

“AREA” > 10000 AND “IMPR” = 0

“RAINFALL” < 20 OR “SLOPE” > 35

NOT ("STATE_NAME" = ‘Colorado’)

[RAINFALL] > 20 XOR [SoilType] = ‘X’

Order matters:

(A AND B) OR C is not the same as

A AND (B OR C)

Operator Description

< less than

> greater than

<= less than or equal to

>= greater than or equal to

= Equal to

<> not equal to

Comparison Operators: Used to compare values

Two ways to combine tables:

JoinsUsed for 1-to-1 relationships, or many-to-1 relationships between attribute table and external table.

Relates Used for 1-to-many relationships, many-to-many relationships between attribute table and external table.

Table Join:Combines two tables based on the value of a field that can be found in both tables (a “common field”).

Parcel-ID Owner

2 John Smith

5 Bruce Martin

6 Anne Davis

1 Steve Arnold

8 Rick James

Parcel-ID Acres

2 2

5 1.5

6 6

1 3

8 1.6

Parcel-ID Acres Owner

2 2 John Smith

5 1.5 Bruce Martin

6 6 Anne Davis

1 3 Steve Arnold

8 1.6 Rick James

Table A Table B

Joins and Relates JoinJoins and Relates Join

A Join lets you join data from an external table to your attribute table based on the value of a field that can be found in both tables.

A Join lets you join data from an external table to your attribute table based on the value of a field that can be found in both tables.

+

Attribute tableExternal Tabular File (immigration)

Example of 1:1 relationship

Results of Join OperationResults of Join Operation

Example of Many-to-1 relationshipExample of Many-to-1 relationship

Join

Example of 1-to-many relationship

Relate

Joins and Relates RelateJoins and Relates Relate

Options Related TablesOptions Related Tables

Example of 1-to-many relationship

Relate

SummarizeCreates a new table containing one record for each unique value occurring in a selected field along with statistics summarizing the data in any of the other fields.

Group together All records that have the same State name.Get summary stats on the values in the rain field.

SummarizeSummarize

Find combined (total) area for each “covertype”

Summarize QuantitativeBy Qualitative!