地理信息系統(tǒng)導(dǎo)論chap11

CHAPTER

11

VECTOR

DATA

ANALYSISBufferingVariations

in

BufferingBox

11.1

Riparian

Buffer

WidthApplications

of

BufferingBox

11.2

Buffer

Zones

as

Indicators

of

Positional

AccuracyOverlayFeature

Type

and

OverlayOverlayMethodsOverlay

and

Data

FormatSliversError

Propagation

in

OverlayBox

11.3

Error

Propagation

ModelsApplications

of

OverlayDistance

MeasurementBox

11.4

Distance

Measurement

for

Assessing

Positional

AccuracyPattern

AnalysisPoint

Pattern

AnalysisMoran’s

I

for

Measuring

Spatial

AutocorrelationG-Statistic

for

Measuring

High/Low

ClusteringApplications

of

Pattern

AnalysisBox

11.5

Detection

of

Drug

Hotspot211.5

Feature

ManipulationKey

Concepts

and

TermsReview

QuestionsApplications:

Vector

Data

AnalysisTask

1:

Perform

Buffering

and

OverlayTask

2:

Overlay

Multicomponent

PolygonsTask

3:

Measure

Distances

Between

Points

and

LinesTask

4:

Compute

General

and

Local

G-statisticsTask

5:

Perform

Select

and

ClipChallenge

TaskReferences3Vector

Data

AnalysisVector

data

analysis

uses

the

spatial

features

of

point,

line,and

polygon

as

inputs.The

accuracy

of

analysis

results

depends

on

the

accuracy

ofspatial

features

in

terms

of

location

and

shape.Topologycan

also

be

a

factor

for

some

vector

data

analysessuch

as

buffering

and

overlay.4BufferingBased

on

the

concept

of

proximity,

buffering

creates

twoareas:

one

area

that

is

within

a

specified

distance

of

selectfeatures

and

the

other

area

that

is

beyond.The

area

that

is

within

the

specified

distance

is

called

thebuffer

zone.Buffering

around

points

creates

circular

buffer

zones.Buffering

around

lines

creates

a

series

of

elongated

bufferzones

around

each

line

segment.

And

buffering

aroundpolygons

creates

buffer

zones

that

extend

outward

from

thepolygon

boundaries.Figure

11.1Buffering

around

points,lines,andpolygons.56Variations

in

BufferingThe

buffer

distance

can

vary

according

to

the

values

of

agiven

field.Buffering

around

line

features

can

be

on

either

the

left

sideor

the

right

side

of

the

line

feature.Buffer

zone

boundaries

may

remain

intact

so

that

eachbuffer

zone

is

a

separate

polygon.Figure

11.2Buffering

with

differentbuffer

distances.7Figure

11.3Buffering

with

four

rings.8Figure

11.4Buffer

zones

not

dissolved

(top)or

dissolved

(bottom).910OverlayAn

overlay

operation

combines

the

geometries

and

attributesof

two

or

more

feature

layers

to

create

the

output.The

geometry

of

the

output

represents

the

geometricintersection

of

features

from

the

input

layers.Each

feature

on

the

output

contains

a

combination

ofattributes

from

the

input

layers,

and

this

combination

differs

fromits

neighbors.Figure

11.5Overlay

combines

geometries

and

attributes

from

two

layers

into

asingle

layer.

The

dashed

lines

are

not

included

in

the

output.1112Feature

Type

and

OverlayOverlay

operations

can

be

classified

by

feature

type

intopoint-in-polygon,

line-in-polygon,

and

polygon-on-polygon.Figure

11.6Point-in-polygon

overlay.

The

input

is

a

point

layer

(thedashed

lines

are

for

illustration

onlyandare

not

part

of

thepoint

layer).

The

output

is

also

a

point

layer

but

has

attributedatafrom

the

polygon

layer.13Figure

11.7Line-in-polygon

overlay.

The

input

is

a

line

layer

(the

dashedlines

are

for

illustration

onlyandare

not

part

of

the

line

layer).The

output

is

also

a

line

layer.Butthe

output

differs

from

theinput

in

two

aspects:

the

line

is

broken

into

two

segments,

andthe

line

segments

have

attribute

datafrom

the

polygon

layer.14Figure

11.8Polygon-on-polygon

overlay.

In

the

illustration,

the

twolayers

for

overlay

have

the

same

area

extent.

The

outputcombines

the

geometry

andattribute

data

fromthe

twolayers

into

a

single

polygon

layer.1516Overlay

MethodsAll

overlay

methods

are

based

on

the

Booleanconnectors

of

AND,

OR,

and

XOR.An

overlay

operation

is

called

Intersect

if

it

uses

the

ANDconnector.An

overlay

operation

is

called

Union

if

it

uses

the

ORconnector.An

overlay

operation

that

uses

the

XOR

connector

iscalled

Symmetrical

Difference

or

Difference.An

overlay

operation

is

called

Identity

or

Minus

if

it

usesthe

following

expression:

[(input

layer)

AND

(identity

layer)]OR

(input

layer).Figure

11.9The

Union

method

keepsall

areas

of

the

two

input

layersin

the

output.17Figure

11.10The

Intersect

method

preserves

only

the

area

common

to

the

twoinput

layers

in

the

output.18Figure

11.11The

Symmetric

Difference

method

preserves

only

the

areacommon

to

only

one

of

the

input

layers

in

the

output.19Figure

11.12The

Identity

method

produces

an

output

that

has

the

same

extent

asthe

input

layer.But

the

output

includes

the

geometry

andattributedata

fromthe

identity

layer.2021SliversA

common

error

from

overlaying

polygon

layers

isslivers,

very

small

polygons

along

correlated

or

sharedboundary

lines

of

the

input

layers.To

remove

slivers,

ArcGIS

uses

the

cluster

tolerance,which

forces

points

and

lines

tobesnapped

together

ifthey

fall

within

the

specified

distance.Figure

11.13The

top

boundary

has

a

series

of

slivers

(shaded

areas).These

slivers

areformedbetween

the

coastlines

from

the

inputlayers

in

overlay.22Figure

11.14A

cluster

tolerance

can

removemany

slivers

along

the

topboundary

(A)

but

can

also

snaplines

that

are

not

slivers

(B).2324Error

Propagation

in

OverlayError

propagation

results

from

inaccuracies

of

the

inputlayers.Slivers

are

examples

of

errors

in

the

inputs

thatcanpropagate

to

the

analysis

output.25Areal

InterpolationOne

common

application

of

overlay

is

to

help

solve

the

arealinterpolation

problem.

Areal

interpolation

involves

transferringknown

datafromone

set

of

polygons

(source

polygons)

toanother

(target

polygons).Figure

11.15An

example

of

areal

interpolation.

Thick

lines

represent

census

tracts

andthin

lines

school

districts.

Census

tract

A

has

a

known

population

of

4000and

B

has

2000.

The

overlay

result

shows

that

the

areal

proportion

ofcensus

tract

A

in

school

district

1

is

1/8andthe

areal

proportion

of

censustract

B,

1/2.

Therefore,

the

population

in

school

district

1

can

be

estimatebe

1500,

or

[(4000

x

1/8)

+

(2000

x

1/2)].2627Distance

MeasurementDistance

measurement

refers

to

measuring

straight-line(Euclidean)

distances

between

features.

Measurements

canbe

madefrompoints

in

a

layer

to

points

in

another

layer,

orfrom

each

point

in

a

layer

to

its

nearest

point

or

line

inanother

layer.28Pattern

AnalysisPattern

analysis

is

the

study

of

the

spatial

arrangement

ofpoint

features

in

two-dimensional

space.At

the

general

level,

a

pattern

analysis

can

reveal

if

adistribution

pattern

is

random,

dispersed,

or

clustered.At

the

local

level,

a

pattern

analysis

can

detect

if

adistribution

pattern

contains

local

clusters

of

high

or

lowvalues.Pattern

analysis

includes

point

pattern

analysis,

Moran’s

Ifor

measuring

spatial

autocorrelation,

and

G-statistic

formeasuring

high/low

clustering.29Point

Pattern

AnalysisNearest

neighbor

analysis

uses

the

distance

betweeneachpointand

its

closest

neighboring

point

in

a

layer

to

determineif

the

point

pattern

is

random,

regular,

or

clustered.Ripley’s

K-Function

can

identify

clustering

or

dispersionover

a

range

of

distances,

thus

setting

it

apart

from

nearestneighbor

analysis.Figure

11.16A

point

pattern

showingdeer

locations.30Figure

11.17The

computed

L(d)and

the

lowerand

upper

simulationenvelopes.3132Figure

11.18A

point

pattern

showingdeer

locations

and

thenumber

of

sightings

ateach

location.33Figure

11.19Percent

Latino

populationby

block

group

in

AdaCounty,

Idaho.

Boise

islocated

in

the

upper

centerof

the

map

with

smallsized

block

groups.34Figure

11.20Z

scores

for

the

LocalIndicators

of

SpatialAssociation

(LISA)

byblock

group

in

AdaCounty,

Idaho.35Figure

11.2136Z

scores

for

the

local

G-statistics

by

block

groupin

Ada

County,

Idaho.37Feature

ManipulationTools

are

available

in

a

GIS

package

for

manipulatingand

managing

features

in

one

or

more

feature

layers.Thesetools

include

Dissolve,

Clip,

Append,

Select,Eliminate,

Update,

Erase,

and

Split.Figure

11.22Dissolve

removes

boundaries

of

polygons

that

have

thesame

attribute

value

in

(a)

and

creates

a

simplified

layer

(b).38Figure

11.23Clip

creates

an

output

that

contains

only

those

features

of

the

inputlayer

that

fall

within

the

a