Geospatial Data Types

Data Types

• Two general views to organizing spatial data:

– Objects • Monitoring measurement points, rivers, structures• Have attributes or features attached to them• Point, line or area format• Values exist at entity locations• Commonly stored and rendered in raster format (grids)

– Fields • Continuous data such as temperature gradient fields and satellite imagery• Values exist over an area• Every location has a value• Commonly stored and rendered in raster format (grids)

Haining, 2003

Vector RepresentationX-AXIS

500

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600500400300200100

Y-AXIS

River

House

600

Trees

Trees

BB

B BB

BBB G

GBK

BBB

G

G

G GG

Raster Representation

1 2 3 4 5 6 7 8 9 1012345

67

8910

Real World

G G

Raster and Vector Data Models

adapted from Lembo, 2003

Vector – Advantages and Disadvantages

• Advantages– Good representation of reality– Relatively compact data structure– Accurate graphics

• Disadvantages– Complex data structures– Some spatial analysis is difficult or impossible to perform

• Advantages– Simple data structure– Uniform size and shape– Computationally cheaper to process

• Disadvantages– Large amount of data– Less visually pleasing (“blocky”)– May lose information due to generalization– Projection transformation is difficult– Different scales between grids can make comparison difficult

Raster – Advantages and Disadvantages

Objects and Fields

Objects and fields can be transformed to the other type

ObjectsVectors

FieldsRaster

adapted from Bolstad, 2002

Vector vs. Raster

Burroughs, 1996

Landcover Raster Grid

Legend

Mixed coniferDouglas fir

Oak savannahGrassland (1-5)

(6-10)

(11-15)

(16-20)

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Raster = Grid

columns

row

s

The bounding box defines the geographic extent of the grid in terms of its coordinates

[min_x, max_x, min_y, max_y]

Abbreviation for PICTURE

ELEMENT, which is the

smallest unit in an image.

In raster based GIS

systems, attribute

information can be

assigned to each pixel.

Pixel

Matrix of Equal-Area Cells

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Grid File Format (ASCII)

ncols 6 nrows 6 xllcorner 210yllcorner 370cellsize 20 nodata_value 0 5, 6, 7, 8, 10, 135, 7, 8, 10, 12, 134, 5, 8, 12, 15, 153, 4, 5, 13, 15, 163, 5, 11, 14, 15, 172, 4, 5, 16, 16, 17

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Table Format

X Y Value

220 380 2

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220 460 5

220 480 5

240 380 4

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240 440 5

240 460 7

240 480 6

Contoured Plots

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Also known as an Isopleth Plot

Map Scale

• Map scale is based on the representative fraction, the ratio of a distance on the map to the same distance on the ground.

• Most maps used in GIS fall between 1:1 million and 1:1000.

• A GIS is scaleless because maps can be enlarged and reduced and plotted at many scales other than that of the original data.

• To meaningfully compare maps in a GIS, both maps MUST be at the same scale

Scale of a baseball earth

• Baseball circumference = 226 mm• Earth circumference approx 40

million meters• Scale is 1:177 million

Scale Dependent Measurements

How long is Maine’s coastline?

length=340 km

length=355 km

length=415 km

From Longley et al., 2001

Resolution25 meter 5 meter

1 meterSame number of pixels (rows and columns)

Resolution

1 meter 5 meter

25 meterSame geographic area (m X m)

Spatial Dimensionality

0-dimensional, L0

points and nodes

1-dimensional, L1

lines

2-dimensional, L2 (x,y)areas, polygons

3-dimensional, L3 (x, y, z)volumes

4-dimensional, L4 (x, y, z, t)3-D plus time

Another way to classify spatial object types is by their dimensionality

2.5 Dimensions

Attributes

Attributes are the values and properties of an object or entity

Types of Attributes

• Nominal – Simply identifies or classifies an entity so that it can be distinguished from another. e.g. sensor ID, building name

– Cannot be manipulated using mathematical operations. However, frequency distributions are meaningful.

• Ordinal – Values based on an order or ranking, e.g. agricultural potential classes

– Cannot be manipulated using mathematical operations. However, frequency distributions are meaningful.

• Interval – Differences between entities are defined using fixed equal units, e.g. Celsius temperature

– Can be manipulated using addition and subtraction

• Ratio - Differences between entities can be defined using ratios, e.g. distance

– Can be manipulated using multiplication and division

• Cyclic - differences between entities depending on repeating sequence, e.g. wind direction

A common approach to classifying attributes is based on their level of measurement

Structured Query Language (SQL)

SELECT column name

SQL is a formal search language that allows you to work with, access and filter data stored in a relational database format

FROM data table name

WHERE data condition

The most common use for SQL is to retrieve subsets of data based on specified conditions

ArcGIS Select by Attribute

SELECT *FROM MO_STNWHERE O3 > 80 AND PM25 > 15

Defining Reclassification Categories

Classification Schemas

Natural breaks: classes are defined according to apparently natural groupings of data values. (GIS programs that automatically determine classes usually base them on relatively large jumps in data values.)

Quantile breaks: classes are defined by having an equal number of observations

Equal interval breaks: classes are defined by uniform intervals

Standard deviation breaks: classes are defined by differences from the mean value.

Color Brewer

http://www.personal.psu.edu/faculty/c/a/cab38/ColorBrewerBeta.html

Graphic Visualization Components

Summary

Two general data types: object & field

Generally, “handled” as either vector or raster

Data can have multiple attributes (properties) associated with features or grid cells

Levels of measurement helps formalize the arithmetic and statistics that are appropriate for a particular dataset

Date Topic Reading

Problem Set Tutorial

31-Aug GIS Overview Bolstad Chp 1Gorr, Chp1

7-Sep Geospatial Data Longley Chp 3Gorr Chp2-3

14-SepProjections and Coordinate Systems

Bolstad Chp 3

Problem Set 1 distributed

Gorr Chp4, Chp 5 (p. 172-180)

21-Sep Feature Analysis Bolstad Chp 9Gorr Chp 8 (p. 272-290), Chp 9

28-Sep Surface Analysis Bolstad Chp 10/11

PS1 due; PS2 distr.

Handout: Suitability Analysis

5-Oct Spatial Data Analysis Bolstad Chp 12

Handout: California Air Pollution

12-Oct Spatial Modeling / Web GIS Bolstad Chp 13

PS2 due Gorr Chp 8 (p. 291-299), Handout: Groundwater Modeling

19-Oct Exam / Project Presentations

Gistutorial\UnitedStatesStatesCountiesCitiesCapitalsUtahNevadaPennsylvania

Gistutorial\Layers

Tutorial3-1.mxdTutorial3-NativeAmericans.mxd