Spatial Data Quality Issues of January, 2006, Wageningen Kirsi...
60
Strategies for dealing with risk, the 13 th of January, 2006, Wageningen Spatial Data Quality Issues in Finland Kirsi Virrantaus Helsinki University of Technology University of Wageningen 13.1.2006
Transcript of Spatial Data Quality Issues of January, 2006, Wageningen Kirsi...
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
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][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
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eys
Mitt
a-ka
ava
Hin
taG
eom
etrin
enra
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e
Geo
met
rinen
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nne
Mitt
a-ka
ava
Hin
ta
A B C D E F G H
Edul
lisim
mat
arvo
toi
keal
la ja
ylhä
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Yllä
pito
-tih
eys
Vrt.
mitt
akaa
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eom
etrin
enra
kenn
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inta
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jekt
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rä
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ittäi
n
[vuo
sitta
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roa
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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
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3th
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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
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k, t
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3th
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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
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gies
for
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006,
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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
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ling
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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
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ling
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k, t
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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
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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
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ris
k, t
he 1
3th
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anua
ry, 2
006,
Wag
enin
gen
Exam
ple
of k
riged
soi
l map
31/
15St
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gies
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ling
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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
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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
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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
with
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
