Mea

sure

s fo

r th

e G

ener

aliz

atio

nM

easu

res

for

the

Gen

eral

izat

ion

of P

olyg

onal

Map

s w

ithof

Pol

ygon

al M

aps

with

Cat

egor

ical

Dat

aC

ateg

oric

al D

ata

Beat

Pet

erD

epar

tmen

t of G

eogr

aphy

Uni

vers

ity o

f Zur

ich

/ Sw

itzer

land

Emai

l: be

atp@

geo.

uniz

h.ch

Web

: ww

w.g

eo.u

nizh

.ch/

~be

atp

4th IC

A W

orks

hop

on P

rogr

ess

in A

utom

ated

Map

Gen

eral

izat

ion,

Bei

jing,

2-4

Aug

ust 2

001

Con

tent

sC

onte

nts

1.In

trod

uctio

n

2. M

easu

res

for

the

Gen

eral

izat

ion

of

Cat

egor

ical

Dat

a

3. A

pplic

atio

n of

Mea

sure

s in

the

Gen

eral

i-za

tion

Wor

kflo

w –

Sel

ecte

d Ex

ampl

es

4. C

oncl

usio

ns a

nd O

utlo

ok

1. In

trod

uctio

n1.

Intr

oduc

tion

Proj

ect A

ppro

ach

Proj

ect A

ppro

ach

•A

ppro

ach

from

the

mea

sure

s sid

e•

± G

ener

ic m

easu

res;

com

preh

ensiv

e de

scrip

tion

of th

ere

leva

nt a

spec

ts o

f pol

ygon

s an

d th

eir

cont

ext i

n a

map

•Re

quire

men

ts o

f gen

eral

izat

ion

oper

ator

s/al

gorit

hms

not

expl

icitl

y co

nsid

ered

at t

his

poin

t in

the

proj

ect

•So

me

mea

sure

s ar

e no

t exp

licitl

y co

nnec

ted

to s

peci

ficop

erat

ors/

algo

rithm

s (g

loba

l sta

tistic

al in

dica

tors

)•

App

roac

h re

flect

s th

e w

orkf

low

in th

e ge

nera

lizat

ion

proc

ess

•Bu

ilds

on th

e cl

assif

icat

ion

deve

lope

d in

pre

viou

s w

ork

Prop

ertie

s of

Cat

egor

ical

Dat

aPr

oper

ties

of C

ateg

oric

al D

ata

•Pl

ane

fillin

g po

lygo

n m

osai

cs (n

o ho

les

or u

nass

igne

dpo

lygo

ns)

•N

o de

dica

ted

back

grou

nd (≠

topo

grap

hic

map

s)•

At l

east

2 p

olyg

ons

are

invo

lved

in e

very

tran

sfor

mat

ion

oper

atio

n•

Freq

uent

rec

ompu

tatio

n of

mea

sure

s re

quire

d du

e to

perm

anen

t cha

nge

of in

dica

tors

•A

situ

atio

n or

a c

onfli

ct c

an b

e lo

oked

at f

rom

diff

eren

tpe

rspe

ctiv

es•

The

cha

ract

er o

f pol

ygon

s w

ith c

ateg

oric

al d

ata

is of

ten

fuzz

y �

influ

ence

on

gene

raliz

atio

n m

etho

ds

2. M

easu

res

for

the

Gen

eral

izat

ion

2. M

easu

res

for

the

Gen

eral

izat

ion

of C

ateg

oric

al D

ata

of C

ateg

oric

al D

ata

Cla

ssifi

catio

n of

Mea

sure

sC

lass

ifica

tion

of M

easu

res

•Sp

atia

l sco

pe•

Mic

ro/L

ocal

(pol

ygon

)•

Mes

o/Re

gion

al (g

roup

of a

djac

ent p

olyg

ons)

•M

acro

/Glo

bal (

cate

gory

, par

titio

n, e

ntire

map

)

•Fu

nctio

n/M

ain

char

acte

ristic

•Si

ze•

Den

sity

and

dist

ribut

ion

•D

istan

ce a

nd p

roxi

mity

• Pa

tter

n an

d al

ignm

ent

•Sh

ape

• Se

man

tic•

Top

olog

y

App

licat

ion

Scop

e of

Mea

sure

sA

pplic

atio

n Sc

ope

of M

easu

res

Thr

ee m

ain

appl

icat

ion

scop

es:

1)In

itial

dat

a ev

alua

tion

2)C

onfli

ct id

entif

icat

ion

and

tran

sfor

mat

ion

cont

rol

3)Ev

alua

tion

of r

esul

ts

1) In

itial

Dat

a Ev

alua

tion

1) In

itial

Dat

a Ev

alua

tion

•Re

cogn

ition

of t

he g

loba

l map

str

uctu

re (e

.g. t

otal

are

a of

cat

egor

ies,

cat

egor

y ar

ea r

elat

ions

, dist

ribut

ion

of o

bjec

ts)

•St

atist

ical

mea

sure

s on

the

glob

al le

vel (

not l

inke

d to

spec

ific

oper

ator

s or

alg

orith

ms)

•Id

entif

y po

tent

ial p

robl

ems

impo

sed

by m

ap c

ontr

ols

befo

rege

omet

ric tr

ansf

orm

atio

ns ta

ke p

lace

(e.g

. too

man

yca

tego

ries

for

the

targ

et s

cale

� re

clas

sific

atio

n)•

Stra

tegy

bui

ldin

g (e

.g. d

elet

e po

lygo

ns o

f cat

egor

y x

with

an

area

sm

alle

r th

an 8

0% o

f the

min

imum

are

a)•

Ass

ess

the

befo

re s

tate

of t

he d

atab

ase

•T

hese

mea

sure

s ar

e lin

ked

to s

peci

fic g

ener

aliz

atio

nop

erat

ors

(and

alg

orith

ms)

•Id

entif

icat

ion

of (g

eom

etric

) con

flict

s•

Gui

de/S

uppo

rt o

pera

tor

sele

ctio

n pr

oces

s (e

.g. d

o no

tde

lete

this

poly

gon)

•G

uide

/Sup

port

alg

orith

m s

elec

tion

proc

ess

(e.g

. disp

lace

non-

unifo

rmly

bec

ause

of l

ack

of s

pace

)•

Gui

de/S

uppo

rt p

aram

eter

sel

ectio

n pr

oces

s fo

r al

gorit

hms

•Re

solv

e lo

cal c

onfli

cts

whi

le r

espe

ctin

g th

eir

influ

ence

on th

e en

tire

map

(glo

bal i

ndic

ator

s)

2)2)C

onfli

ct Id

entif

icat

ion

and

Con

flict

Iden

tific

atio

n an

d T

rans

for

Tra

nsfo

r --m

atio

nm

atio

n C

ontr

ol C

ontr

ol

3) E

valu

atio

n of

Res

ults

3) E

valu

atio

n of

Res

ults

•C

ompu

tatio

n of

the

afte

r sta

te �

com

pare

with

bef

ore

stat

e•

Che

ck fo

r in

cons

isten

cies

(e.g

. top

olog

ical

err

or)

•Pr

oble

m: v

isual

impr

essio

n �

num

eric

al v

alue

s•

Acc

ept o

r re

ject

a s

olut

ion

(com

plet

ely

or p

artly

)•

Mod

ify s

trat

egy

or e

xit

•Id

eally

, pro

blem

s or

pot

entia

l pro

blem

s ar

e id

entif

ied

atru

n tim

e or

dur

ing

initi

al d

ata

eval

uatio

n (a

ppro

pria

tem

easu

res!

)

3. A

pplic

atio

n of

Mea

sure

s in

the

3. A

pplic

atio

n of

Mea

sure

s in

the

Gen

eral

izat

ion

Wor

kflo

w

Gen

eral

izat

ion

Wor

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cted

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mpl

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logi

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es: G

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eral

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from

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ener

aliz

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om 1

:100

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Min

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2.

3.

4.

5.

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Sele

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Dist

ance

Con

flict

Dist

ance

Con

flict

1.

2.

3.4.

5.6.

4. C

oncl

usio

ns a

nd O

utlo

ok4.

Con

clus

ions

and

Out

look

Con

clus

ions

Con

clus

ions

•W

ork

in p

rogr

ess;

muc

h is

still

unc

lear

(e.g

. com

plex

situa

tions

)•

Mea

sure

s ar

e a

key

elem

ent i

n th

e ge

nera

lizat

ion

proc

ess;

aho

listic

app

roac

h al

low

s be

tter

con

trol

ling

tran

sfor

mat

ions

•Se

man

tic in

form

atio

n an

d ex

pert

kno

wle

dge

is ve

ryim

port

ant

•A

cqui

sitio

n of

gen

eric

kno

wle

dge

for

diffe

rent

type

s of

cate

goric

al d

ata

can

be a

pro

blem

•Ev

ery

data

set h

as it

s in

divi

dual

pro

pert

ies

•In

terp

reta

tion

of v

alue

s (c

hang

es o

f val

ues)

may

be

apr

oble

m (e

.g. s

hape

and

glo

bal/m

acro

indi

cato

rs)

Out

look

O

utlo

ok ––

Nex

t Ste

ps N

ext S

teps

•H

arm

oniz

atio

n w

ith r

equi

rem

ents

of o

pera

tors

and

algo

rithm

s (M

. Gal

anda

)•

Step

by

step

impl

emen

tatio

n fr

om s

impl

e to

com

plex

on

the

Lase

r-Sc

an/L

amps

2 pl

atfo

rm•

Find

app

ropr

iate

met

hods

for

the

impl

emen

tatio

n of

com

plex

mea

sure

s•

Find

way

s fo

r in

tegr

atin

g se

man

tic in

form

atio

n•

Exte

nsiv

e em

piric

al te

stin

g•

Mod

ifica

tion

of m

easu

res,

intr

oduc

e ne

w o

nes,

dro

pot

hers