63
Lecture 4 Geodatabases

Lecture 4 Geodatabases. Geodatabases Outline Data types Geodatabases Data table joins Spatial joins Field calculator Calculate geometry

Embed Size (px)

Citation preview

Lecture 4

Geodatabases

Geodatabases Outline Data types Geodatabases Data table joins Spatial joins Field calculator Calculate geometry ArcCatalog functions

2INF385T(28437) – Spring 2013 – Lecture 4

DATA TYPES Lecture 4

3INF385T(28437) – Spring 2013 – Lecture 4

Directly loadable data types

dBase (.dbf) Text with comma (.csv) or tab-

separated values (.txt)

Microsoft Access (.mdb)

Microsoft Excel (.xls)

4INF385T(28437) – Spring 2013 – Lecture 4

5

Data table formats First row must have attribute names

with self-documenting labels (e.g. Pop5To17, Area)

Usual naming convention first character is a letter remaining characters be any letters, digits,

or the underscore character All additional rows of a data table

contain attribute values None of the rows can be sums,

averages, or other statistics of raw data rows

INF385T(28437) – Spring 2013 – Lecture 4

GEODATABASESLecture 4

7INF385T(28437) – Spring 2013 – Lecture 4

8

Geodatabase typesManages features and tables inside a database management system

File geodatabase stores datasets in a folder of files each dataset file up to 1 TB in size can be used across platforms can be compressed and encrypted for

read-only, secure use

INF385T(28437) – Spring 2013 – Lecture 4

9

Geodatabase types Personal geodatabase

stores datasets in a Microsoft Access .mdb file

storage sizes between 250 and 500 MB limited to 2GB only supported on Windows

ArcSDE geodatabase stores datasets in a number of optional

DBMSs: IBM DB2, IBM Informix , Microsoft SQL

Server , Oracle, or PostgreSQL unlimited size and users

INF385T(28437) – Spring 2013 – Lecture 4

10

New file geodatabase

ArcCatalog

INF385T(28437) – Spring 2013 – Lecture 4

11

Import into geodatabase

INF385T(28437) – Spring 2013 – Lecture 4

Shapefile features

12

Import into geodatabase

Tables

INF385T(28437) – Spring 2013 – Lecture 4

13

Export from geodatabase

INF385T(28437) – Spring 2013 – Lecture 4

14

View geodatabases Cannot identify names in Windows

Explorer Must use ArcCatalog

INF385T(28437) – Spring 2013 – Lecture 4

15

Compact geodatabases

File and personal geodatabases Reduces size and improves performance Compact personal geodatabases > 250

MB. Geodatabases with frequent data entry,

deletion, or general editing Open geodatabases in ArcMap cannot be

compacted remove any layers with a source table or

feature class in that database from the TOC

INF385T(28437) – Spring 2013 – Lecture 4

16

Compress geodatabases File geodatabases

Once compressed, a feature class or table is read-only and cannot be edited

Compression is ideally suited to mature datasets that do not require further editing

Compressed dataset can be uncompressed to return it to its original, read-write format

INF385T(28437) – Spring 2013 – Lecture 4

DATA TABLE JOINSLecture 4

17INF385T(28437) – Spring 2013 – Lecture 4

18

Data table joins Putting two tables together to make

one table

Join two tables one-to-one by row

Must have the same values and data

types

INF385T(28437) – Spring 2013 – Lecture 4

19

Join example

Housing heating fuel study for U.S.

Counties

Source: U.S. Census Data table: Census SF3 table for heating

fuel by county

Map Features: County polygons

INF385T(28437) – Spring 2013 – Lecture 4

20

Data table

Heating fuel table (Excel spreadsheet)

INF385T(28437) – Spring 2013 – Lecture 4

21

Data table

Heating fuel table data dictionary H040001: Occupied housing units: House heating fuel; TOTAL Units H040002: Occupied housing units: House heating fuel; Utility gas H040003: Occupied housing units: House heating fuel; Bottled; tank;

or LP gas H040004: Occupied housing units: House heating fuel; Electricity

H040005: Occupied housing units: House heating fuel; Fuel oil; kerosene; etc.

H040006: Occupied housing units: House heating fuel; Coal or coke H040007: Occupied housing units: House heating fuel; Wood H040008: Occupied housing units: House heating fuel; Solar energy H040009: Occupied housing units: House heating fuel; Other fuel H040010: Occupied housing units: House heating fuel; No fuel used

INF385T(28437) – Spring 2013 – Lecture 4

22

Feature class

County polygons

INF385T(28437) – Spring 2013 – Lecture 4

23

Add data and features to map

INF385T(28437) – Spring 2013 – Lecture 4

24

Open attribute tables Find common attribute to join

INF385T(28437) – Spring 2013 – Lecture 4

25

Data problem FIPS has leading zero

and is a TEXT field.

GEO_ID2 is a NUMBER fieldwith no leading zeros.

INF385T(28437) – Spring 2013 – Lecture 4

FIPS

01001

01003

01005

01007

GEO_ID2

1001

1003

1005

1007

26

Data solution Make a new NUMBER field in Counties

attribute table and use field calculator to populate new field from old

INF385T(28437) – Spring 2013 – Lecture 4

27

Data solution New FIPS_NUM is same as GEO_ID2 and

ready to join

INF385T(28437) – Spring 2013 – Lecture 4

28

Join tables

INF385T(28437) – Spring 2013 – Lecture 4

29

Join result Heating fuel data is now listed for

every county in the USCounties feature attribute table

INF385T(28437) – Spring 2013 – Lecture 4

30

Permanent joins Joins are temporary and can be

removed Export data to make joins permanent

INF385T(28437) – Spring 2013 – Lecture 4

31

Choropleth map result

INF385T(28437) – Spring 2013 – Lecture 4

SPATIAL JOINSLecture 4

32INF385T(28437) – Spring 2013 – Lecture 4

33

Spatial join example You have census block group centroids

with housing fuel data

You want to know housing fuel data by neighborhoods

No attributes in common Spatial join needed

INF385T(28437) – Spring 2013 – Lecture 4

34

Spatial joins Points to polygons

Spatially joins points (block centroids) within polygons (neighborhoods)

Joins using “shape” (not attribute field)

INF385T(28437) – Spring 2013 – Lecture 4

35

Spatial joins Right click polygon layer

(neighborhoods)

INF385T(28437) – Spring 2013 – Lecture 4

36

Join result New polygon feature

INF385T(28437) – Spring 2013 – Lecture 4

37

Join result

Counts and sums

INF385T(28437) – Spring 2013 – Lecture 4

38

Count result Number of points in each polygon

INF385T(28437) – Spring 2013 – Lecture 4

39

Sum result Every block group centroid has associated

data (e.g. H040004, heating electricity shown in

labels)

INF385T(28437) – Spring 2013 – Lecture 4

40

Sum result

INF385T(28437) – Spring 2013 – Lecture 4

One neighborhood example Central business district

4 block groups Housing units with electricity fuel (80 + 299 + 128

+ 292 ) Sum = 799

41

Choropleth map result (sum)

INF385T(28437) – Spring 2013 – Lecture 4

42

Choropleth map result (sum)

INF385T(28437) – Spring 2013 – Lecture 4

43

Other spatial joins

Polygons to points Example: ATM robberies (points) need

neighborhood name

INF385T(28437) – Spring 2013 – Lecture 4

44

Polygon to point join result

Neighborhood name shows on each

point

INF385T(28437) – Spring 2013 – Lecture 4

45

Other spatial joins Points to points

Example: What is the distance of a burglary to the nearest commercial property?

INF385T(28437) – Spring 2013 – Lecture 4

46

Point to point join result Distance to nearest commercial

property shows on each burglary point

INF385T(28437) – Spring 2013 – Lecture 4

FIELD CALCULATORLecture 4

47INF385T(28437) – Spring 2013 – Lecture 4

(as in “Feature-Attribute” Calculator)

Sample functions

Performs numeric calculations

Populates field

Concatenates text data

48INF385T(28437) – Spring 2013 – Lecture 4

Field calculator functions

Calculate acres to square miles

49INF385T(28437) – Spring 2013 – Lecture 4

Field calculator functions

Populate field with county name

INF385T(28437) – Spring 2013 – Lecture 4 50

Field calculator functions Concatenate house number and street

fields

INF385T(28437) – Spring 2013 – Lecture 4 51

CALCULATE GEOMETRYLecture 4

52INF385T(28437) – Spring 2013 – Lecture 4

Polygon/point centroids Advanced calculations for finding a

polygon’s point centroid

53INF385T(28437) – Spring 2013 – Lecture 4

Calculate XY fields

Add new X and Y fields in the attribute

table

INF385T(28437) – Spring 2013 – Lecture 4 54

Calculate XY fields Calculate geometry for X field, repeat

for Y

INF385T(28437) – Spring 2013 – Lecture 4 55

56

XY field results Results are X and Y values based on

map properties (e.g. Long/Lat or XY feet)

INF385T(28437) – Spring 2013 – Lecture 4

Export as shapefile XY events should be exported as

permanent shapefile or feature class

59INF385T(28437) – Spring 2013 – Lecture 4

ARCCATALOG FUNCTIONSLecture 4

63INF385T(28437) – Spring 2013 – Lecture 4

Basic functions

Copy, paste, rename, etc.

64INF385T(28437) – Spring 2013 – Lecture 4

View and edit properties

Projections, fields, etc.

65INF385T(28437) – Spring 2013 – Lecture 4

View metadata

66INF385T(28437) – Spring 2013 – Lecture 4

Edit metadata

67INF385T(28437) – Spring 2013 – Lecture 4

Create new files

Geodatabases, tables, features,

etc.

68INF385T(28437) – Spring 2013 – Lecture 4

Summary Data types Geodatabases Data table joins Spatial joins Field calculator Calculate geometry ArcCatalog functions

69INF385T(28437) – Spring 2013 – Lecture 4