Post on 22-Apr-2020
Stra
tegi
es fo
r dea
ling
with
risk
, the
13t
hof
Jan
uary
, 200
6, W
agen
inge
n
Spat
ial D
ata
Qua
lity
Issu
es
in F
inla
nd
Kirs
i Virr
anta
usH
elsi
nki U
nive
rsity
of
Tech
nolo
gyU
nive
rsity
of
Wag
enin
gen
13.1
.200
6
2/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
The
curr
ent
stat
us in
SD
Q in
Fin
land
•Th
e N
atio
nal G
I st
rate
gy h
as b
een
publ
ishe
d in
200
4–
Nat
iona
l Spa
tial D
ata
Infr
astr
uctu
re is
bei
ng im
plem
ente
d–
In o
rder
to
impl
emen
t IN
SPIR
E di
rect
ives
–N
SI o
ffer
s, a
mon
g ot
hers
, met
adat
a de
scrip
tions
and
ser
vice
s of
th
e co
re g
eogr
aphi
cal d
ata
sets
•N
atio
nal R
ecom
men
datio
ns f
or P
ublic
Adm
inis
trat
ion
are
curr
ently
dev
elop
ed–
The
core
info
rmat
ion
of s
tand
ards
tra
nsla
ted
into
Fi
nnis
h/Sw
edis
h–
Conc
ept
defin
ition
s, P
roce
dure
s, M
easu
res
–Q
ualit
y m
anag
emen
t pr
oces
s•
Spat
ial d
ata
qual
ity is
one
of
the
mai
n is
sues
in r
esea
rch
–Th
e us
er-o
rient
ed w
ay o
f de
scrib
ing
qual
ity a
nd it
s im
plic
atio
ns
to d
ecis
ion
mak
ing
in d
iffer
ent
appl
icat
ions
3/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Mai
n ac
tors
in S
DQ
in F
inla
nd
Nat
iona
lLa
nd S
urve
y
The
Min
istry
of
Agr
icul
ture
and
Fore
stry
Priv
ate
com
pani
es
Uni
vers
ities
and
Res
earc
hin
stitu
tes
Nat
iona
lC
ounc
il fo
r GI
NC
GI
Oth
er
publ
icor
gani
zatio
ns
GI s
trate
gy
Fund
ing
for r
esea
rch
Met
adat
a se
rvic
es
Qua
lity
mod
els
Met
adat
a
Var
ious
rese
arch
to
pics
Dev
elop
men
t of
the
reco
mm
enda
tions
Qua
lity
mod
els
4/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
The
cont
ents
of
my
pres
enta
tion
•1)
Nat
iona
l Spa
tial D
ata
Infr
astr
uctu
re in
Fin
land
•2)
Nat
iona
l Rec
omm
enda
tions
on
Geo
grap
hic
Dat
a–
Met
adat
a on
geo
grap
hic
info
rmat
ion
–Sp
atia
l dat
a qu
ality
•3)
Som
e im
plem
enta
tions
–Th
e qu
ality
mod
el a
t N
LS–
The
qual
ity m
odel
at
FDF
•4)
Res
earc
h/de
velo
pmen
t to
pics
at
univ
ersi
ties
–At
Hel
sink
i Uni
vers
ity o
f Te
chno
logy
, Dep
t. o
f Su
rvey
ing
–At
Hel
sink
i Uni
vers
ity, F
acul
ty o
f Fo
rest
ry
•5)
Con
clus
ions
5/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
1) N
atio
nal S
DI
•D
evel
oped
acc
ordi
ng t
o IN
SPIR
E di
rect
ives
•Th
e co
re
–G
eogr
aphi
cal d
ata
dire
ctor
y at
NLS
–M
etad
ata
desc
riptio
ns (
acco
rdin
g to
ISO
) an
d se
rvic
es–
Def
initi
on o
f th
e co
re d
ata
sets
–H
arm
oniz
atio
n of
dat
a m
odel
s of
the
cor
e da
ta s
ets
•Re
quire
s–
Com
mon
agr
eem
ent
of m
etad
ata
desc
riptio
ns–
Org
aniz
ed a
rchi
tect
ure
•N
atio
nal C
ounc
il fo
r G
eogr
aphi
c In
form
atio
n
6/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Käy
ttäj
ä
Tied
ontu
otta
ja
Palv
elun
tuot
taja
Met
atie
topa
lvel
u
Käy
ttäj
ä
Tied
ontu
otta
ja
Palv
elun
tuot
taja
Met
atie
topa
lvel
u
Rek
iste
röiU
RL
(hak
emis
to)
Sisä
inen
met
atie
to-
järj
este
lmä
ISO
191
39JH
SIS
O 1
9139
JHS
ISO
191
39JH
SWeb
-sa
itti
Hae
Met
atie
to
CA
T 2.
0/C
SW
GU
IG
UI
Met
atie
to-
edito
ri
Ajo
ittai
nen
päiv
itys
RD
F/IS
O 1
9139
-tie
dost
ot
Hak
urob
otit,
Sem
antt
inen
web
Met
atie
topa
lvel
u-ar
kkite
htuu
ri
7/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
2) R
ecom
men
datio
ns f
or p
ublic
ad
min
istr
atio
n •
Reco
mm
enda
tions
for
pub
lic a
dmin
istr
atio
n ba
sed
on
ISO
sta
ndar
ds
–H
UT/
C&G
impl
emen
ts–
Min
istr
y of
Agr
icul
ture
and
For
estr
y fin
ance
s–
The
Advi
sory
Com
mitt
ee o
n In
form
atio
n M
anag
emen
t in
Pub
lic
Adm
inis
trat
ion
publ
ishe
s•
The
core
con
tent
s of
sta
ndar
ds a
re t
rans
late
d an
d ex
plai
ned
and
reco
mm
enda
tions
are
pro
duce
d on
–
The
sele
cted
met
adat
a an
d qu
ality
ele
men
ts,
–Q
ualit
y ev
alua
tion
proc
edur
es a
nd m
easu
res
•Re
com
men
datio
ns o
n G
eogr
aphi
cal M
etad
ata
•Re
com
men
datio
ns o
f Sp
atia
l Dat
a Q
ualit
y
8/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
ISO
sta
ndar
ds m
ake
the
basi
s
•M
etad
ata
–IS
O 1
9115
•
Qua
lity
Prin
cipl
es –
ISO
191
13•
Qua
lity
Eval
uatio
n Pr
oced
ures
–IS
O 1
9114
•D
ata
Qua
lity
Mea
sure
s –
ISO
191
38 (
final
dra
ft)
•St
anda
rds
incl
ude
defin
ition
s of
–M
etad
ata
elem
ents
, qua
lity
elem
ents
, qua
lity
eval
uatio
n pr
oced
ures
and
mea
sure
s–
Qua
lity
repo
rts
can
be c
reat
ed b
y te
stin
g th
e da
ta s
ets
•St
anda
rds
are
base
d on
the
ass
umpt
ion
–Th
at m
etad
ata
and
qual
ity in
form
atio
n ar
e cr
eate
d in
the
pr
oduc
tion
proc
ess
and
it is
ava
ilabl
e fo
r us
ers
9/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Qua
lity
man
agem
ent
poin
t of
vie
w
•In
the
rec
omm
enda
tions
we
have
trie
d to
de
scrib
e th
e en
tire
qual
ity m
anag
emen
t pr
oces
s fr
om t
he d
ata
prod
ucer
to
the
user
•By
des
crib
ing
the
step
s–
Requ
irem
ents
def
initi
on–
Dat
a pr
oduc
t de
finiti
on–
Dat
a co
llect
ion
–D
ata
proc
essi
ng–
Dat
a m
anag
emen
t–
Qua
lity
eval
uatio
n–
Dat
a de
liver
y
10/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Qual
ity
man
agem
ent
pro
cess
Pla
nn
ing
th
e q
uali
tyQ
uali
ty c
on
tro
l an
d q
uali
ty t
est
ing
Acc
epta
nce
tes
t
Imp
rovin
g t
he q
uali
ty
Produce
r
Cust
om
er
Qual
ity
eval
uat
-io
n
Dat
am
anag
emen
tD
ata
del
iver
yD
ata
colle
ctio
nD
ata
pro
cess
ing
Req
uirem
ents
def
initio
n
Dat
a pro
duct
def
initio
n
11/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
3) Q
ualit
y m
odel
s
•O
ne w
ay t
o im
plem
ent
stan
dard
s is
to
esta
blis
h qu
ality
m
odel
s of
geo
grap
hica
l dat
a ba
ses
and
data
set
s•
Nat
iona
l Lan
d Su
rvey
was
the
firs
t or
gani
zatio
n in
Fi
nlan
d th
at im
plem
ente
d sp
atia
l dat
a qu
ality
in t
heir
Qua
lity
Mod
el o
f To
pogr
aphi
c D
ata
Base
–Al
read
y in
199
5–
no s
tand
ards
wer
e re
ady
at t
hat
time
–Ty
pica
l exa
mpl
e of
Pro
duce
r´s
qual
ity m
odel
•Th
e Fi
nnis
h D
efen
ce F
orce
s de
velo
ped
thei
r Q
ualit
y M
odel
of
Geo
grap
hic
Info
rmat
ion
in 2
004
–Ac
cord
ing
to t
he I
SO s
tand
ards
–Ty
pica
l exa
mpl
e of
Use
r´s
qual
ity m
odel
12/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Qua
lity
mod
el o
f To
pogr
aphi
c D
ata
Base
at
NLS
•Co
vers
all
data
typ
es o
f th
e TD
B•
Sele
cted
qua
lity
elem
ents
–Po
sitio
nal a
ccur
acy;
RM
SE, 1
4 ac
cura
cy c
lass
es–
Attr
ibut
e ac
cura
cy;
AQL
num
ber
–Te
mpo
ral a
ccur
acy
–To
polo
gica
l con
sist
ency
–
Com
plet
enes
s•
Doc
umen
ted
proc
edur
es f
or q
ualit
y m
anag
emen
t•
Prod
ucer
s´ q
ualit
y m
odel
13/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Qua
lity
mod
el o
f G
I at
FD
F
•FD
F do
not
cre
ate
own
GI
but
uses
GI
of N
LS a
s w
ell a
s ot
her
publ
ic o
rgan
izat
ions
and
priv
ate
com
pani
es•
Ther
e is
a n
eed
to d
ocum
ent
the
qual
ity o
f da
ta s
ets
•Co
vers
all
qual
ity e
lem
ents
of
the
stan
dard
–N
ot a
ll da
ta c
an b
e fil
led
in b
ecau
se it
is n
ot a
vaila
ble
–Th
e da
ta w
hich
is a
vaila
ble
is n
ow d
eliv
ered
for
all
user
s am
ong
FDF
•Im
plem
eted
as a
pilo
t sy
stem
–an
Exc
el –
appl
icat
ion
in I
ntra
net
•U
sers
´ qu
ality
mod
el
14/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
4) R
elat
ed r
esea
rch
topi
cs a
t H
UT
•Ah
onen
-Rai
nio,
Paul
a: V
isua
lizat
ion
of G
eosp
atia
l M
etad
ata
for
Sele
ctin
g G
eogr
aphi
c D
atas
ets
(200
5)•
Antt
i Jak
obss
on:
On
the
futu
re o
f To
pogr
aphi
c Ba
se
Info
rmat
ion
Man
agem
ent
in F
inla
nd a
nd in
Eur
ope
(def
ence
in 2
006)
•Ra
ngsi
ma
Suni
la:
Fuzz
y kr
igin
gfo
r so
il m
aps
(def
ence
in
2007
)•
Riik
ka H
enrik
sson
: O
ntol
ogie
s fo
r ha
rmon
izat
ion
of
geog
raph
ical
dat
a ba
ses
(def
ence
in 2
008)
•Ei
ri Va
lant
o: S
patia
l dat
a m
inin
g (j
ust
star
ted)
15/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
The
user
´s p
oint
of
view
: se
lect
ion
of
the
“bes
t fit
” da
ta s
et
•W
hen
the
user
wan
ts t
o se
lect
a d
ata
set
for
his/
her
spec
ified
use
•H
e/sh
e ca
n us
e se
lect
ed m
etad
ata
elem
ents
in
eval
uatin
g th
e fit
ness
for
use
•Q
ualit
y el
emen
ts a
re im
port
ant
but
not
the
only
one
•If
met
adat
a de
scrip
tions
are
ava
ilabl
e, d
ata
sets
can
be
com
pare
d by
usi
ng–
Visu
aliz
atio
n of
mul
tivar
iate
dat
a–
Som
e ex
ampl
es o
n th
e ne
xt s
lides
(sou
rce:
Pau
la A
hone
n-Ra
inio
, Vi
sual
izat
ion
of G
eosp
atia
l Met
adat
a fo
r Se
lect
ing
Geo
grap
hic
Dat
aset
s)
MAI
NTE
-N
ANC
E
SCAL
E
GEO
-M
ETR
Y
PRIC
E
OBJ
ECT
DEN
SITY
MAI
NTE
-N
ANC
ESC
ALE
GEO
MET
RY
PRIC
EO
BJEC
TD
ENSI
TY
[dai
ly]
[ann
ually
]
[1:2
000]
[com
plex
][1
50e]
[500
0pr]
[1:1
.6M
][p
oint
][2
8000
e][8
0000
0pr] Ah
onen
-Rai
nio,
Paul
a: V
isua
lizat
ion
of G
eosp
atia
l Met
adat
a fo
r Se
lect
ing
Geo
grap
hic
Dat
aset
s (2
005)
Yllä
pito
-tih
eys
Yllä
pito
-tih
eys
Mitt
a-ka
ava
Hin
taG
eom
etrin
enra
kenn
e
Geo
met
rinen
rake
nne
Mitt
a-ka
ava
Hin
ta
A B C D E F G H
Edul
lisim
mat
arvo
toi
keal
la ja
ylhä
ällä
Yllä
pito
-tih
eys
Vrt.
mitt
akaa
vaG
eom
etrin
enra
kenn
eH
inta
Tiet
o-ob
jekt
ien
mää
rä
päiv
ittäi
n
[vuo
sitta
in]
ei k
oska
an
1:20
00
[1:2
00 0
00]
1:1,
6 m
ilj.
kom
plek
si
[viiv
a]pi
ste
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kim
äär.]
pien
i
suur
i10
0 eu
roa
[7 0
00 e
ur]
28 0
00 e
ur
Edul
lisar
vot
ylhä
ällä
Ahon
en-R
aini
o,Pa
ula:
Vis
ualiz
atio
n of
Geo
spat
ial
Met
adat
a fo
r Sel
ectin
g G
eogr
aphi
c D
atas
ets
(200
5)
A B C D E F G H
yllä
pito
geom
etria
mitt
akaa
va hint
aob
jekt
ien
mää
rä
A B C
D E F
G H
Kas
vonp
iirte
etku
vast
avat
kuin
ka h
yvin
ai
neis
to v
asta
akä
yttä
jän
aset
tam
ia
vaat
imuk
sia.
suu:
yllä
pito
tihey
s silmät
: ”m
ittak
aava
” kulmakarvat:
geom
etria
Ahon
en-R
aini
o,Pa
ula:
Vis
ualiz
atio
n of
Geo
spat
ial
Met
adat
a fo
r Sel
ectin
g G
eogr
aphi
c D
atas
ets
(200
5)
19/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
The
prod
ucer
s´po
int
of v
iew
: Q
ualit
y in
th
e m
ulti-
prod
ucer
env
ironm
ent
•W
hen
impl
emen
ting
the
natio
nal s
patia
l dat
a in
fras
truc
ture
and
whe
n de
finin
g th
e “c
ore”
dat
a se
ts t
he
prob
lem
of
vario
us p
rodu
cers
is t
he e
ssen
tial o
ne–
how
to
harm
oniz
e th
e da
ta b
ases
-W
ith d
iffer
ent
onto
logi
es-
With
diff
eren
t qu
ality
leve
ls-
With
nat
iona
l, m
unic
ipal
and
priv
ate
acto
rs
•O
ne s
olut
ion
is t
o cr
eate
an
info
rmat
ion
man
agem
ent
syst
em t
hat
wor
ks o
n qu
ality
man
agem
ent
fram
ewor
k an
d in
tegr
ates
all
(sou
rce:
A. J
akob
sson
, the
sis
man
usrip
t)
20/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Terr
ain
Dat
aset
A
Dat
aset
B
Prod
uctio
n
Harmon
isatio
n
Mul
tisou
rce
Topo
grap
hic
Dat
abas
e
MapU
ser
Dat
abas
e
Dat
a us
er
Inte
rnet
Info
rmat
ion
and
qual
itym
anag
emen
t
The
core
idea
and
hyp
othe
sis
of th
is re
sear
ch is
the
esta
blis
hmen
t of a
mul
tisou
rce
Topo
grap
hic
data
base
und
er th
e co
ntro
l of I
nfor
mat
ion
and
Qua
lity
Man
agem
ent
21/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
prod
uctio
nce
ntre
d
plan
ning
cent
red
cust
omer
cent
red
syst
emce
ntre
d
Dat
a qu
ality
desc
ripiti
ons
Erro
rpr
opag
atio
n
Dat
a us
abili
tyRisk
analy
sis
Com
mon
qual
ityre
quire
men
tsSD
Is
Information management
Unc
erta
inty
Use
r re
quire
men
ts
Quality
contr
ol
ISO
191
13IS
O 1
9114
Qualityassurance
Applicatio
n
development
harm
onisa
tion
intero
perab
ility
ISO
191
15m
etad
ata
Cus
tom
er
satis
fact
ion
Qua
lity
visu
aliz
atio
n
Proc
ess
man
agem
ent
22/
15St
rate
gies
for
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ling
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anua
ry, 2
006,
Wag
enin
gen
Harmonisation
Nat
iona
l
Vec
tor
Sate
llite
/rast
er
Glo
bal
Euro
pean
Loca
l
Reg
iona
l
New data acquisition
Con
flict
Dou
ble
pyra
mid
par
adig
m
23/
15St
rate
gies
for
dea
ling
with
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k, t
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anua
ry, 2
006,
Wag
enin
gen
Ont
olog
ies
of g
eogr
aphi
c in
form
atio
n
•O
ntol
ogie
s be
com
e an
issu
e–
In h
arm
oniz
atio
n–
In m
etad
ata
serv
ices
–In
sem
antic
web
•Th
e go
al:
to c
reat
e so
me
kind
of
inte
grat
ion
betw
een
diff
eren
t on
tolo
gies
•Co
uld
be u
tiliz
ed in
the
impl
emen
tatio
n of
NSD
I•
This
res
earc
h ha
s ju
st s
tart
ed (R
iikka
Hen
rikss
on)
24/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Out
side
the
sta
ndar
ds:
Mod
ellin
g im
prec
isio
n of
GI
•Th
e st
anda
rds
do n
ot t
ouch
the
pro
blem
of
impr
ecis
ion
(vag
uene
ss)
•H
owev
er in
spa
tial a
naly
ses
it is
an
issu
e th
at
have
str
ong
impl
icat
ions
on
the
relia
bilit
y of
the
re
sults
–th
e ris
k th
at w
e w
ant
to t
ake
in
deci
sion
mak
ing
•Fu
zzy
mod
elin
g is
one
met
hod
to m
anag
e th
e im
prec
isio
n of
the
nat
ure
–Li
ke im
prec
isio
n of
soi
l pol
ygon
s in
soi
l map
s–
(sou
rce:
Ran
gsim
a Su
nila
, Fuz
zy-k
rigin
g in
mod
ellin
gof
soi
l map
s, t
hesi
s m
anus
cipt
)
25/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Qua
tern
ary
depo
sits
map
•Q
uate
rnar
y de
posi
ts in
1 m
eter
m
appi
ng d
epth
•Q
uate
rnay
dep
osits
map
ping
is
cond
ucte
d m
anua
lly b
y in
terp
reta
tion
and
field
obs
erva
tion
•In
gen
eral
, top
ogra
phic
map
s, a
eria
l ph
otos
and
geom
orph
olog
y ar
e us
edto
def
ine
soil
boun
darie
s
•So
me
sam
ples
may
be
take
nto
the
so
il la
bora
tory
for
deta
iled
test
•Su
rvey
ors’
expe
rienc
es a
re u
sed
in
deci
sion
mak
ing
26/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Aim
sof
the
res
earc
h
•In
trod
uctio
nof
fuz
zy m
odel
ling
and
krig
ed
mod
ellin
gfo
r im
prec
ise
soil
poly
gon
boun
darie
s.•
Com
paris
onof
mod
els.
•Al
tern
ativ
esfo
r m
odel
sel
ectio
n ba
sed
on
suita
ble
appl
icat
ion.
•D
evel
opm
ent
of F
uzzy
krig
ing
mod
el
27/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Fuzz
y m
odel
of im
prec
ise
soil
poly
gon
boun
darie
s
Expe
rt kn
owle
dge
on
the
soil
map
ping
pro
cess
Der
ived
exp
ert k
now
ledg
e
Fuzz
y m
embe
rshi
p
Fuzz
y ru
le b
ase
Fuzz
y so
il m
ap
28/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Exam
ple
of f
uzzy
soi
l map
29/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Krig
ed m
odel
of im
prec
ise
soil
poly
gon
boun
darie
s
Ran
dom
sam
ple
poin
tsK
riged
mod
elkr
iged
soil
map
30/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Exam
ple
of k
riged
soi
l map
31/
15St
rate
gies
for
dea
ling
with
ris
k, t
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3th
of J
anua
ry, 2
006,
Wag
enin
gen
Furt
her
stud
y
•D
evel
opm
ent
of k
riged
met
hod
–in
dica
tor
krig
ing
–co
krig
ing
–fu
zzy
krig
ing
32/
15St
rate
gies
for
dea
ling
with
ris
k, t
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3th
of J
anua
ry, 2
006,
Wag
enin
gen
Cokr
igin
g
•Co
krig
ing
is a
n in
terp
olat
ion
tech
niqu
e th
at a
llow
s on
e to
use
am
ore
inte
nsel
y sa
mpl
ed c
ovar
iate
in t
he e
stim
atio
n of
val
ues
for
a re
late
d va
riate
. •
Cokr
igin
gis
a s
impl
yan
ext
ensi
onof
aut
okrig
ing
in t
hat
it ta
kes
into
ac
coun
t ad
ditio
nal c
orre
late
d in
form
atio
nin
the
sub
sidi
ary
varia
bles
.•
If t
he p
rimar
y va
riate
is d
iffic
ult
or e
xpen
sive
to
mea
sure
and
it is
co
rrel
ated
with
a m
ore
avai
labl
e co
varia
te, c
okrig
ing
can
grea
tly
impr
ove
inte
rpol
atio
n es
timat
es.
•In
thi
sca
se s
tudy
, we
use
–el
ectr
ical
sou
ndin
gda
ta–
soil
sam
ples
data
(Sou
rces
: R. W
ebst
eran
d M
.A. O
liver
, 200
1, G
eost
atis
tics
for
Envi
ronm
enta
l Sci
entis
tsw
ww
.gam
mad
esig
n.co
m)
33/
15St
rate
gies
for
dea
ling
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k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Dat
a
34/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Res
ulte
d m
aps
35/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Nex
t st
ep:
Fuzz
y kr
igin
g
•Fu
zzy
krig
ing
was
intr
oduc
ed b
y Ba
rdos
syA.
, Bog
ardi
I., a
nd K
elly
W.E
. in
1990
•Fu
zzy
krig
ing
is k
rigin
g w
ith im
prec
ise
(fuz
zy)
vario
gram
s.
•Bo
th k
riged
val
ues
and
estim
atio
n va
rianc
es a
re c
alcu
late
das
fuz
zy
mem
bers
and
char
acte
rized
by
thei
r m
embe
rshi
p fu
nctio
ns.
•Kr
iged
val
ues
are
expr
esse
das
fuz
zy m
embe
rs w
hich
may
be
char
acte
rized
by
the
fuzz
y m
ean
and
rang
e.•
Estim
atio
n va
rianc
e ca
n be
cal
cula
ted
also
as a
fuz
zy n
umbe
r.•
In t
his
stud
y, w
e pl
anto
use
–gr
ound
pen
etra
ting
rada
r da
ta–
soil
sam
ple
data
36/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Spat
ial d
ata
min
ing
•A
prel
imin
ary
stud
y ha
s be
en m
ade
(Ver
a Ka
raso
va,
2005
; no
w c
ontin
uing
her
stu
dies
at
Not
tingh
am
Uni
vers
ity a
s a
post
grad
uate
stu
dent
•W
e w
ant
to c
reat
e m
etho
d w
hich
incl
ude
know
lded
ge o
n sp
atia
l dat
a –
topo
logy
, spa
tial c
orre
latio
n an
d ca
usal
ities
; sp
atia
l dat
a st
ruct
ures
•W
e w
ant
to s
tudy
the
pos
sibi
litie
s to
sup
port
NSD
I by
sp
atia
l dat
a m
inin
g–
auto
mat
ed m
etad
ata
crea
tion
–au
tom
ated
dat
a se
rvic
es f
or u
sers
•Ei
ri Va
lant
oju
st s
tart
ed r
eser
ach
37/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Som
e de
velo
pmen
t ca
ses:
Mili
tary
GIS
•FD
F is
ver
y ac
tive
in
–de
velo
ping
the
ir G
IS a
pplic
atio
ns
–Im
plem
entin
g G
IS s
tand
ards
, esp
ecia
lly t
he S
DQ
sta
ndar
ds
•a)
Ana
lysi
s of
the
unc
erta
inty
of
mili
tary
ter
rain
ana
lysi
s–
Mon
teCa
rlo s
imul
atio
n +
aut
oreg
ress
ive
proc
ess
for
crea
ting
cont
inuo
us s
oil p
olyg
ons
with
out
frag
men
tatio
n–
Res
ult:
a m
etho
d to
mod
el s
patia
lly v
aryi
ng u
ncer
tain
ty a
nd it
´svi
sual
izat
ion
•b)
Vis
ualiz
atio
n of
unc
erta
inty
in t
he C
omm
on
oper
atio
nal P
ictu
re /
Situ
atio
n Pi
ctur
e–
Unc
erta
inty
of
diff
eren
t te
rrai
n an
alys
is r
esul
ts
–U
ncer
tain
ty o
f ob
serv
atio
n m
essa
ges
38/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
a)Rel
iabi
lity
of t
he r
esul
ts o
f m
ilita
ry t
erra
in a
naly
sis
•M
ilita
ry c
ross
-cou
ntry
mob
ility
ana
lysi
s is
bas
ed o
n so
il m
aps
–ot
her
inpu
t da
ta:
DEM
, veg
etat
ion,
dep
th o
f sn
ow, d
epth
of
fros
t•
Soil
map
is p
rodu
ced
man
ually
–as
we
saw
bef
ore!
•M
etad
ata
of s
oil m
aps
are
not
avai
labl
e •
Qua
lity
info
rmat
ion
is c
olle
cted
“af
terw
ards
” –
By in
terv
iew
s an
d qu
estio
nnai
res
(geo
logi
sts)
–Pr
esen
ted
as m
iscl
assi
ficat
ion
mat
rices
•Fo
llow
ing
slid
es:
(sou
rce
Hor
ttan
aine
n,P.
, 200
4)–
Mili
tary
soi
l map
, cro
ss-c
ount
ry a
naly
sis
resu
lt,m
iscl
assi
ficat
ion
mat
rix, s
imul
ated
rea
lizat
ions
of
soil
map
s w
ithou
t au
torg
eres
sive
proc
ess,
cro
ss-c
ount
ry a
naly
sis
com
pute
d by
us
ing
sim
ulat
ed d
ata
20Q
2D4
20Q
2D4
20Q2D4
Bedr
ock
Coar
se til
lSa
ndy
tillSi
lty til
lSa
ndy
heat
hSi
ltCl
aySw
amp
Wat
er a
rea
Bedr
ock
88-9
010
Coar
se til
lSa
ndy
till8
86-8
8Si
lty til
lSa
ndy
heat
h86
-93
Silt
81-8
85-
10Cl
ay10
-15
86-9
3Sw
amp
2-5
2-5
2-5
2-5
2-5
100
Wat
er a
rea
100
21N4A1
Bedr
ock
Coar
se til
lSa
ndy
tillSi
lty til
lSa
ndy
heat
hSi
ltCl
aySw
amp
Wat
er a
rea
Bedr
ock
88-9
019
-20
Coar
se til
lSa
ndy
till8
76-7
8Si
lty til
lSa
ndy
heat
h86
-93
Silt
81-8
85-
10Cl
ay10
-15
86-9
3Sw
amp
2-5
2-5
2-5
2-5
2-5
100
Wat
er a
rea
100
Classification
Classification
In reality %In reality %
6.1.
Kan
gas
Suo
Siltt
i
Ves
i
Hie
kkam
oree
ni
Savi
Kal
lioK
anga
sK
anga
s
Suo
Suo
Siltt
iSi
ltti
Ves
iV
esi
Hie
kkam
oree
niH
iekk
amor
eeni
Savi
Savi
Kal
lioK
allio
20Q
2D4
21N
4A1
01
23
45
6
20Q
2D4
21N
4A1
01
23
45
60
12
34
56
0011
2233
4455
66
46/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
b) V
isua
lizat
ion
of u
ncer
tain
ty in
the
Com
mon
op
erat
iona
l Pic
ture
•At
FD
F a
new
pla
tfor
m w
an s
elec
ted
for
all G
IS
appl
icat
ions
–ES
RI
prod
ucts
•Th
e Co
mm
on o
pera
tiona
l Pic
ture
/Situ
atio
n pi
ctur
e is
one
ex
ampl
e of
a G
IS a
pplic
atio
n th
at w
ill b
e de
velo
ped
•So
me
rese
arch
/dev
elop
men
t w
ork
has
been
don
e fo
r th
e be
com
ing
COP
–W
hich
are
the
ter
rain
ana
lyse
s th
at c
ould
sup
port
qua
lity
eval
uatio
n ?
–H
ow t
he q
ualit
y ca
n be
eff
icie
ntly
vis
ualiz
ed ?
•Fi
rst
step
tow
ards
to
risk
anal
ysis
app
roac
h ha
s be
en
take
n•
On
the
follo
win
g sl
ides
som
e ex
ampl
es r
elat
ed t
o sp
atia
l da
ta q
ualit
y, e
spec
ially
the
vis
ualiz
atio
n of
the
qua
lity
47/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Loca
tion
anal
ysis
: ca
nit
beth
ere?
Cro
ssco
untr
y an
alys
isre
sult
as a
ref
eren
ce.
48/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Visi
bilit
yan
alys
is:
Can
itbe
see
n fr
omth
ere?
Vie
wsh
ed:
DEM
, veg
etat
ion.
49/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Exam
ple:
Der
ivin
g th
e qu
ality
of
obse
rvat
ion
thro
ugh
terr
ain
anal
yses
•
Rec
onna
issa
nce
patr
ol(a
t th
e bo
ttom
of
the
pict
ure)
iden
tifie
da
T-80
en
emy
tank
at 3
.15
pm
•Lo
catio
n an
d vi
ewsh
ed
anal
yses
are
com
pute
dfo
r th
e ob
serv
atio
n•
Acco
rdin
g to
the
an
alys
es t
he r
elia
bilit
y of
th
e ob
serv
atio
n is
ver
y hi
gh•
the
obse
rvat
ion
is
acce
pted
to
the
data
ba
se a
s a
cert
ain
obse
rvat
ion
50/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
His
tory
,thi
sm
omen
t, t
he p
redi
ctio
nVi
sual
izat
ion
of t
he u
ncer
tain
ty
Unc
erta
inty
: in
case
the
anal
yses
gi
ve a
dou
bt
abou
tthe
qua
lity
His
tory
–tra
nspa
renc
y50
%A
t pre
sent
–m
ain
hues
(full
satu
ratio
n)P
redi
ctio
n–
fuzz
y bo
unda
ryB
ackg
roun
d m
ap1:
50
000
tact
icm
ap,
with
mod
ified
satu
ratio
nan
d va
lue.
Siz
eof
the
map
ca. 8
km
x 1
0 km
.
Sym
bol f
illed
with
the
colo
ur o
nly
to th
e m
iddl
e.
51/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Visi
bilit
y m
aps
The
unce
rtain
ty o
f th
e bo
unda
ry o
f the
vi
sibi
lity
area
is
show
n by
a fu
zzy
zone
.
Frie
ndly
troo
ps-b
lue
Ene
my
troop
s-r
edO
verla
ppin
g ar
ea p
urpl
e.
52/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Impo
rtan
ce o
f ris
k an
alys
is
•In
CO
P ap
plic
atio
n on
e im
port
ant
activ
ity is
to
pred
ict
the
poss
ible
mov
emen
ts o
f th
e en
emy
•Th
e si
mpl
e m
etho
d fo
r pr
edic
ting
is t
o us
e ac
cess
ibili
ty
anal
ysis
and
sho
rtes
t pa
th o
ptim
izat
ion
•Th
ese
anal
yses
are
com
pute
d ba
sed
on–
Cros
s-co
untr
y an
alys
is r
esul
t la
yer
–ha
s (k
now
n) u
ncer
tain
ty in
cl
assi
ficat
ion/
attr
ibut
e ac
cura
cy–
Addi
tiona
l kno
wle
dge
abou
t fo
r ex
ampl
e m
ine
field
s –
they
mig
ht
have
low
spa
tial a
ccur
acy
and
also
low
com
plet
enes
s/am
ount
of
mis
sing
min
es c
an b
e hi
gh•
In c
ase
we
have
no
info
rmat
ion
abou
t th
e co
mpl
eten
ess
of t
he m
ine
field
s in
a d
ecis
ion
base
d on
the
ana
lysi
s re
sults
a b
ig r
isk
is t
aken
–In
som
e si
tuat
ions
eve
n a
big
risk
has
to b
e ta
ken
!!!
53/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Acce
ssib
ility
and
the
sho
rtes
t pa
th
Acc
essi
bilit
yis
pre
sent
edby
the
diffe
rent
inte
nsiti
esof
blue
hue.
Zone
s an
d zo
nes
+ bo
unda
ries.
Acc
essi
bilit
yzo
nes
and
the
shor
test
path
.
54/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Shor
test
pat
hs w
ithou
t m
inef
ield
s(r
ed),
pat
hs w
ith
min
efie
lds
(gre
en).
Do
we
know
the
com
plet
enes
s of
m
ine
field
s?
55/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Som
e ex
ampl
e fr
om t
he f
ores
t re
sear
ch
field
•
At H
elsi
nki U
nive
rsity
, Fac
ulty
of
Fore
stry
a lo
t of
re
sear
ch b
ased
on
spat
ial d
ata
anal
yses
is c
arrie
d ou
t;
also
Uni
vers
ity o
f Jo
ensu
u•
Fore
st r
esea
rher
sha
ve s
tron
g tr
aditi
ons
in s
tatis
tical
an
alys
is, t
hus
also
qua
lity
issu
es h
ave
been
the
re m
uch
mor
e th
an in
ave
rage
in G
IS a
pplic
atio
ns•
Som
e ex
ampl
es o
n–
Spat
ial s
ampl
ing
met
hods
for
for
estr
y –
Qua
lity
in f
ores
t in
vent
ory
–Ris
k an
d un
cert
aint
y in
for
estr
y de
cisi
on a
naly
sis
–Q
ualit
y is
sues
in t
he u
se o
f ae
rial p
hoto
grap
hs a
nd s
atel
lite
imag
es in
for
est
inve
ntor
y
56/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Cont
rolo
f fie
ldan
d m
apda
ta a
nd d
ecis
ion
mak
ing
•Sa
mpl
ing
erro
r/bi
as•
Fiel
dda
ta–
Kang
as, A
nnik
a&
Hei
kkin
en, E
lina
&
Mal
tam
o, M
atti.
–
Accu
racy
of p
artia
llyvi
sual
lyas
sess
edst
and
char
acte
ristic
s: a
cas
e st
udy
of F
inni
shfo
rest
inve
ntor
yby
com
part
men
ts. C
anad
ian
jour
nal
of f
ores
tre
sear
ch34
(20
04)
: 4,
s. 9
16-9
30
•D
ecis
ion
mak
ing
erro
rs–
Kang
as, A
nnik
a&
Kan
gas,
Jyr
ki.
–Pr
obab
ility
, pos
sibi
lity
and
evid
ence
: ap
proa
ches
to
cons
ider
ris
k an
d un
cert
aint
y in
fo
rest
ry d
ecis
ion
anal
ysis
. //
Fore
st p
olic
y an
d ec
onom
ics
6 (2
004)
: 2
, s. 1
69-1
88
57/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Rel
iabi
lity
of r
emot
ese
nsin
gre
sults
•U
seof
Sat
ellit
eda
ta in
For
estr
y–
Toko
la, T
., P
itkä
nen
, J.,
Par
tin
en, S
. an
d M
uin
onen
, E.
19
96
. –
Poi
nt
Acc
ura
cy o
f a
Non
-Par
amet
ric
Met
hod
in
Esti
mat
ion
of
Fore
st C
har
acte
rist
ics
wit
h D
iffe
ren
t Sa
telli
te M
ater
ials
. In
tern
atio
nal
Jou
rnal
of
Rem
ote
Sen
sin
g 1
7(1
2):
23
33
-23
51
.–
Toko
la, T
. 20
00
. –
The
infl
uen
ce o
f fi
eld
sam
ple
data
loca
tion
on
gro
win
g st
ock
volu
me
esti
mat
ion
in L
ands
atTM
-ba
sed
fore
st
inve
nto
ry in
eas
tern
Fin
lan
d. R
emot
e Se
nsi
ng
of
Envi
ron
men
t 7
4(3
):4
21
-43
0.
•U
seof
Aer
ialp
hot
ogra
phs
in F
ores
try
–K
orpe
la, I
. an
d To
kola
, T. 2
00
6.
–P
oten
tial
of
aeri
al im
age-
base
d m
onos
copi
can
d m
ult
ivie
w s
ingl
e-tr
ee f
ores
t in
ven
tory
-a
sim
ula
tion
ap
proa
ch. A
ccep
ted
to F
ores
t Sc
ien
ce.
–M
äkin
en, A
ntt
iM, K
orpe
la, I
., To
kola
, T. a
nd
Kan
gas,
A.
20
06
.–
Effe
cts
of I
mag
ing
Con
diti
ons
on C
row
n D
iam
eter
M
easu
rem
ents
fro
m H
igh
Res
olu
tion
Aer
ial I
mag
es.
Acc
epte
d to
Can
adia
n J
ourn
al o
f Fo
rest
Res
earc
h.
58/
15St
rate
gies
for
dea
ling
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ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
5. C
onlc
usio
nsTo
pics
for
dev
elop
men
t an
d re
sear
ch
•Fr
om t
he q
ualit
y de
scrip
tion
poin
t of
vie
w:
–Th
e im
plem
enta
tion
of s
tand
ards
by
esta
blis
hing
pr
oper
qua
lity
mod
els
in o
rgan
izat
ions
.–
Mak
ing
data
eva
luat
ion
a ro
utin
e pr
oced
ure
thro
ugho
ut t
he li
fe c
ycle
of
GI
–fr
om p
rodu
cers
to
user
s.–
Dev
elop
men
t of
spa
tially
var
ying
qua
lity
mod
els.
59/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Conc
lusi
ons…
•Fr
om t
he a
pplic
atio
n po
int
of v
iew
:–
Whi
ch a
re t
he im
port
ant
qual
ity e
lem
ents
in e
ach
appl
icat
ion?
W
hich
mea
sure
s sh
ould
be
used
?–
If w
e tr
y to
tak
e al
l ele
men
ts in
to a
ccou
nt t
he u
ncer
tain
ty m
odel
w
ill b
ecom
e to
o co
mpl
icat
ed.
–Ris
k an
alys
is is
som
ehow
the
onl
y po
ssib
le a
ppro
ach
beca
use
it al
low
s -
to d
efin
e th
e de
cisi
on s
ituat
ion
in q
uest
ion
and
thus
als
o -
to r
educ
e th
e am
ount
of
qual
ity e
lem
ents
.
–Ris
k an
alys
is g
ives
exa
ctly
tha
t in
form
atio
n th
at is
nee
ded
in
deci
sion
mak
ing
and
is u
sefu
l for
the
use
rs.
–Th
e re
sults
wou
ld b
e ev
en m
ore
usef
ul f
or t
he e
nd u
sers
if
effic
ient
vis
ualiz
atio
ns w
ere
avai
labl
e.
60/
15St
rate
gies
for
dea
ling
with
ris
k, t
he 1
3th
of J
anua
ry, 2
006,
Wag
enin
gen
Mor
e in
form
atio
n
•w
ww
.hut
.fi/U
nits
/Car
togr
aphy
–Re
sear
ch–
Kirs
i.virr
anta
us@
hut.
fi
•w
ww
.nls
.fi–
Nat
iona
l Lan
d Su
rvey
•w
ww
.vm
.fi–
Min
istr
y of
Agr
icul
ture
and
For
estr
y