Analysis and Modelling of Environmental Data

229 Pages·2004·17.212 MB·English

by  Mikhail Kanevski, Michel Maignan

ENVIRONMENSTCAILE NCES
ANALYSIS
ANDM ODELLING
OFS PATIAL
ENVIRONMETNALD ATA
MikhKaainle v&s Mkiic hMeali gnan
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TABLEO F CONTENTS
PREFACE vii
........ .... ............................................................. .............
Chapte1r INTRODUCTIONT O ENVIRONMENTALD ATA
ANALYSISA ND MODELLING I
.............................................
II. Introctdiuo.n.. ,,... ...................., ,,.. .. .,,,,.,, .. ..,,. ....... I
.................
1.2 Environdmee<.;nitssauilpo pnso yrstt aenmds
predimcaptpiinog..n . .......................................7
.... .. . . . .... . . . . . ..
I3 Presenotfta htceia ossnet u d.i.e.s. .........8. .............................
.
1.4 Spatidaalt aa nalwyitshGi eso sOtffiacte . 12
..... ....................
Chapte2r EXPLORATORYS PATIADLA TA ANALYSIS.
ANALYSIOSF MO ITORINGN ETWORKS.
DECLUSTERING. ...... ... ...... ...........17
..... ... . ..... . . .... .. . . .... ...... ... . ... .. .
2.1 Introd.u..ct.io.n. . ... .. .. .......17
. . .. .... ......... ... ... .... ... .... .. .... .... . .. . . . .
2.2 Explordaatatoanry a l.y.s.i.s. ...........1.8. .................................
2.3 Transfoomf1d aa.tt.ia.o .n. ............2.7. ....................................
2.4 Quantidteastcirvioepfm t oinoint onertiwnog.r ..k...s.3 0
. .. . ...
2.5 Declus.t.e.r.i.n.g. ..............3.8. ................................................
2.6 GeosOtffiactem :o nitoringa nnde tworks
declusteri11.g . . . . 43
........ . ........... .......... ................. ............... .....
27. Conclu.s.i.o.n..s. ..............4.4. .................................................
3
Chapter SPATIADLA TAA NALYSISD:E TERMINISTIC
INTERPOLATIONS.. .... ..........................47
.. . ... .... . .. .. .. ... .. ... . ... . .....
3.1 Introd.u.c.t.i..o.n. .............4.7. .................................................
3.2 Val.it.odoaltsi. on 48
.......... ................. ......................................
3.3 Modelso fd etermiinntiesrtpio.c.l. a..t.i..o...n.s... 5 1
. . .. ... ... .. ...
3.4 Determiinnitsetripcow liatGthei oosOntfsaf ti. .c...e.. 59
. .. .. ..
3.5 Conculsions..,,. ............... .. .............6. l
.... .... .... .. .. .... .... .. .. .. .. .. ..
Copynghmtaed 1al
X ANALYSIASN D MODELLINGO F SPATIAELN VIRONMENTAALN D POLLUTIODNA TA
Chapter4 INTRODUCTIONT O GEOSTATISTICS.
VARIOGRAPHY . ... ... . .. 63
............ .. .... ... ... .. .... ... ..... .. .............. .... .....
4.1 GeostatiTshteiocrsoy:fr egionalviazreida b.l.e..s ..63
.. . .. .... ..
4.2 GeostatiBsatsiichcsy :p othes.e.s .. ... ... .64
... ... ... . ... ....... .. ...... ..
4.3 Variograp.hy ... . . . ... ..65
..... ....... ........ ... .. ... ..... .... ..... ... . .... . . ..... . ..
4.4 Coregionalimzoadteilosn. ... .. .. ...7.1.
..... ... ... . ... ..... ...... . ....... .. .
4.5 Exploravtaorriyo grianpp hrya ctice . . . .75
.......... . ... ... ..... ...... ..
4.6 VariograwpihtGyhe -0stOaffitc e. .... ... .. .. 79
... .. .. ... .... ... . ... .. ....
4.7 Commentasn di nterpreta.t.i.o.n..s. ..........8.5.
.. . .. ... ..... .. ... ..... .
4.8 Conclus.io.n.s. .... ..... ... ... ..88
... . ... .... .... .. ........... . ..... . .... . ........ ...
Chapte5r GEOSTATISTICALS PATIALP REDICTIONS. ...........8.9
. . .. .. ...
5.1 Introdu.c.t.i.o.n. .................... ..........8 9
... ... . .. . . .. ... .. . ... ....... .. .. .. .
5.2 Familoyf krigmiondge l.s. .. ... . . 90
... ... . .. ..... ...... . .... .............. ...
5.3 Krigipnrge dictwiiotnGhse ostOaffitc e.. ...... ........ ...........9.7
5.4 Spaticaol- estimaCtoi-oknrsi.g miondge l.s. ......1 11
. ... .... .. ....
5.5 Co·krigpirnedgi ct. iAo cnassset ud.y . .... ......1 14
..... ... ... ... ... ..
5.6 Conclusions .......,,.. .. ..............1.1.7. .........................
... ..... . .... . .
Chapte6r ESTIMATIONO F LOCAL PROBABILITYD ENSITY
FUNCTIONS L1 9
.............................................................................
6.1 Introduc..t.i.o.n.. ......... ............ ..119
. .... .. .. . .. .... . . ... .. ... .. ... .... ... ..
6.2 Indicaktroirg ia.g.. .... . . . ..............J 2 0
.... .. . . . ... ..... ... ... .... .. . . . .. ... .
6.3 IndicaKtroirg iAn gc.a sset udy. ... .... .. 123
.... .. .. .... .. .... ..... . .....
6.4 Conclusiaonndcs o mmenotnsi ndicaktroirg ing .127
........... .
Chapte7r CONDITIONALS TOCHASTIC SIMULATION.S. .....1. 29
. ... ... .
7.1 Introduc.t.io.n. . . .. . ...................129
.. ... ... ... . ... ... . ... ... . . .. .. .... .. . ... .
7. 2 Modelosfs patsiiamlu latio.ns . ... .... ..1 31
....... ..... ... ....... . ...... ..
7.3 Conditisotnoaclh cas sitmiulatiCoansses.t udie..s....... 138
7.4 Review of othsimulatieonr models 148
.. ....... ... ...... ... ....... ... ..
7. 5 Commentasn dd iscussio.ns. . . . . .152
....... ..... ... ... ...... ... .. ... ..... ..
7.6 Checko ft hes iumlatio.. n....s. ....... ......................... ...... ....15 5
7.7 Conclusio.n.s. . . . ................ 156
...... ... ... ..... ... ... .. . .... .. ... .. ... ... .....
Anne1x. C onditiosniimnugl atwiiotnhs
conditikorn1agli n.g. .... . ... . ....... .1 57
... .... .. ... ..... ... ... .... ... ... .. ... ...
2.
Annex Non-conditsiiomnualla toifos ntsa tionary
isotrompuilct igaursasnidaonfum n ctio.ns . 159
. ...... .... ...... ....
Annex3. S equentgiaauls sisainm ulatwiiotnhs
GeostOaffitc e. ...........................................1. 64.
. . . .. . .. . . . .. ... ... .
Copyngrll'taed ra l
ANALY SlASN DM ODELUNGO FS PATIEANLV IROM ENTALA NDP OLLUTIDOA TA XI
Chapte8 r ARTIFICIALE URAL NETWORKS A DS PATIAL
DATAA ALYSI.S. .. .....................1.6 9
. .... . ............. . . ... .... ... . . .. .. ... .. ..
8.1 Introd.u.c...tio.n .. .. . . 169
.... .. .................. ... ..... ... .... ........ ...........
8.2 BasiocfAsN N. ................................................1...07... ..........
8.3 Artifinceilantler tawlo lrekasrn .ing. ..........1 37
. ....... ... ... . . ... ...
8.4 Multifleaeydefro nrewuanrreadtl w orks 157
........ ........ ...... ...
8.5 Generreragels snieounnr eatlw (oGrRkS s). .. ........1.98
. .. . . .
8.6 Neurnaelt wroerski kdruiaglmi ondg(e NlN RK). 199
....... ....
87. Conclu..s.i.o.n.s... ... . . . 205
. . ... ... .. . . .. ..... ........... ...... ...... ............ .
Chapte9r SUPPORT VECTOR MACHINESF OR
E VIRONMENTALS PATIALDATA 207
............ .......................
9.1 Introduction. . . .. . 207
....... ........... .... ..... ........ ........... .. . ...... .........
9.2 Suppvoerctmt aocrh icnleass si.fi..c..a.t..i.o.n. 208
. .. .. ... ...... . . .
9.3 Spacdiaamtlaa p piwnigts hu pport
vecrteogrr ession 212
........... ................ ...................................
9.4 Ac asset udy ............ . . ..2.1 6
............ ... ... .. .... .. . ... .... . ....... ..... ... ...
9.5 EvaluoafSt VioMbn i nasrpya tcilaals sification
with nonparamesttroicch sacisomtnuidlcia t2t2ii7oo nnasl
...
9.6 GeoSVcMo mpuptreorg ram . ..235
............... ......... ........ ... ... ..
9.7 Conclus.i.o.n..s. .........................237
........ ... .. ... .. .. .. .. .. .. . ..... .. .. .
Chapte1r0 GEOGRAPHICAL INFORMATIONS YSTEMS
... .. . 239
AND SPATIALD ATAA NALYSIS
. ... ... ....... .. . ......... ...... .....
10.1I ntrodu.c.t..io.n . 239
..... ... ... ... ............. ................... .............. ....
1.02 Contridbiustciinapgnl tdie ncehsn olo.gie.s2 40
........ ......... ....
l0 .3 GItSe chnology . .........................2.42
............. ..... .... . ... . . .. .. .. . ..
l0 .4 GTfSu ncti.ona.li.ty ..243
....... . ....... ....... ................. .......... .... . ..
1.05 Basoibcj eocfGt IsS . 244
...... .................................................
1.06 Represeonftt haGetI Sio obnj e.c.t... . .244
... ...... .......... ......... ..
1.07 GJlSa yer.s.. .. . . .247
...... ... ... ... ....................................... ......... .
1.08 Mapp rjoetcinos .. .. ... .........248
..... .. ........... . .. .... .... .... ... ... . .. . .. ..
1.09 GeosOtfaftai ncGdeJ S ........ .........2.48
.......... . ........ ... .... . ... .. ..
1.0l0 Conclusion.s . . . . .254
......... ..... .................. ............. ......... ... ..... ..
Chapte1r1 CONCLUSIONS . . . ... .......... ....257
........... .... ........ .... . ...... ... . ...... .... .. ..
259
GLOSSARIES
................. ....................................... ...................
StatiGsetoisctsa,Ft riascttiac..ls.s,.. ...... .......2 59
....... ... . .. ... ........ . ... ...
MachiLneea rni.ng . .. ..... . ...267
......... ....... ..... ..... . ... .. . . ..... .... ......... ... ...
REFERE CES .. . .276
...... . .......... ........... ........ ............. ..... .... ...... .... ..
Copynghmtaedte 1 al
CHAPTER 1
INTRODUCTITOONE NVIRONMENTAL
DATAA NALYSIASND M ODELLING
1.1I NTRODUCTION
1.1D.a1 tmao dels
Fort hea nalyosfsi psa tidailsltyr idbauttaae fu,dn damenatsaplei csfit r st
considceartneh ddea: t baei nterpoorla arttehe edoy,fs ucaht ypteh aanti nterpolation
betwetewnov alumeesa suartde idff erleoncta tmiaoknensso s ense?
Int hec asoef i nterpoldaattoeand,e w iluls uaelnlcyo unvtaerri albilkees
chemigcraaldo erts h ickwnheiscvsha rmyo roerl esslso wflryoo mn leo cattoit ohne
othaern,df owrh icsho maes sumpotfsi toenp wviasrei abaiplpiertaeyrl se vTahnet .
methopdrse seinnt etbdho ioaskp pmlayi ntloty h tiysp oefd ateai,t fhoeprro llution
measureomrefo nrot rsbe o digersa des.
Anothcearso efi nterpdoaltaiatsc e odn stibtycu atteedg odraitwcaah,le rteh e
valiunef eartran e odn -mealsoucraetidisn o oantv alcuoen taiintn hesedu rrounding
valubeusat,v alueb ec thoo saemno nagg ivseenot fc ategofroiirne sst,a asn ociel
typ\Veh.e ni nterpobleattwietnewgno p oinotnsa mapw hicphr esdeinffte rent
categoofrs ioeiosln seh, a uss uanlolttyod efina"e p ercenotfca agtee"gb oertyw een
thcea tegoorfei aecpsho ibntut,tod efintehs ep atfiraoln wthieertreh s eo cialt egory
woulcdh anfgreo omn et ot hoet hdeerc isbioounn dbaertyw ecelna sssheosu bled
founuds ianvga ildaabtalane d knowledge.
Amonngo ni nterpdoaltaoatn eecd a finn da lkli nodfss patiinadli caatnido ns
measuremwehnitccsha nnboet" spreoavde"tr h seu rfaocneec: a nniontt erpolate
betwetewnol ocatwiiotnhhso spi"tAa"wl is tah b edasn,d " B'w'it bh be dso,r
interpboeltawteteew noa dminisdtartaat.i ve
Then on-intedraptwoail loalftt eebndeh andalsec do nstrfaotirhn ceta sr tography
oft hien terpdoaltafato,per rd o blleimkcsea rtogorfpa oplhlyu ftoiarod nm inistrative
domaiTnhseu. n derstoafni dnitnegr paonlndao tne-di ntedraptocala banet a edda pted
tot hper oblpeoms efdo:trh cea rtogorfar pahdyow ni,ti hn domoera suremoennet s,
will diinstpelrapymo alpaostfr e add coonn tsepnrte,oa vdet rh e wahroelaaen, td h is
interpdoaltawato eudlb der elevoannlityaf h ouwseer teob eb uiolnst u cahna rea.
Thed atmae asureamrecenh tasr actbeytr hiescieordo rdinat(eesl:e vation),
z
x,y,
antd( timEei)t.ht eh(reX ,J'a.riZer) r egudliasrtlryib beuctaeoudfst, eh s ea mploirn g,
thceo lleocftmi eoans uremweasnd tosna ec cortdoiv nagr icoounss troarti hnetys ,
2 ANALYSAINSD M ODELLIONFGS PATEEANLV IRONMENATNADPL O LLUTIDOANT A
locatoenda r eguglraiardsl attdiactueas ,u aalr leyc tanggruioldva,ert r h weh ole
are
areuan der study.
Thel atticea reed iatthae r maecatsuuarle moernt thser, e suolfts so me
computamtoidoenlw hsi,c dhe liavnee rs timoartm eodde llveadl fouree acnho de
oft hger iTdh.es atelilmiatgaeen ,dm orpea rticutlharere lmyo steen sriencgo rds
constainti umtpeo rtcaantte gaomryo ntgh elsaet t(ircaesd taetra).
Thew holper oceosfsc omputecrairtsoegdr caopnhsyii nse tsst imavtailnuaget s
locatiwohnesrn eom easureomren nom tosd eldlaetwdae raev ailoarib nle ex,t racting
sommea in charaicdteenrtiaisssfit peiadct ssi,ta rlu cotrup raetst aemrnosn tgh lea rge
amouonfta vailianbfloer mation.
Onec acno nsiedietrth heartt hm ee asudraetdra e pretshetenr tu itnht ,hs ee nse
thatth eayr aec curraetper,o duocri" bdleet,e rmionrit shtatithc me"e ,a surements
incleurdreo arnsdt,h arte peastaemdp hantcg l olsoec atwioounldsde lidvieffre rent
valuseots h,at th" es tochansattiucor"fte h dea tmau sbtec onsidered.
Basdiact tyap es
InG eograpIhnifcoarlm Saytsitoednma sta arc el assiintfi hefedo llomwainnnge r
[GIsSe llefa rnitnogo2 l0,0 1]:
• RatDiaot a.
DefinitMieoans:u remtehnarttes p reqsueanntt iitnti eersm osf e qual
interavnaadln as b solzuetrpeoo ionfot r igEixpnr.e susseidnn ugm betrhsa t
cabne t ransfoorrc moemdb iwnietdah n mya themaftuinccattliog o enn erate
meaninrgefuslu Elxatmsp.l rinecsl umdeea sureomfec nhtasr actseurcihs tics
asa gef,r equepnhcyys,id ciaslt aanncdme osn etvaarlyuR ea.ti inop muatp
datcaa nb eu sefdo trh feo llowsitnagt iospteircaatlSi uomnA,sv :e rage,
MaximuMmi,n imuMme,d ian, MajoriDtiyv,e r(MsViiantroyir aeinttdyy ),
Range.
• InteDravtaal.
DefinitMieoans:u remtehnarttes p reqsueanntt iitnti eersm osf e qual
interovrad lesg reoefds i fferbeuntwc heo,s zee rpoo int (oorf point
beginniinsag r)b itreasrtialbyl Uissehde qdut.a on tdiifyff erebnucnteo st
proportainocdnh sa racrteelraiptsoiesv iet iinso pnasct ei,mo erm agnitude.
Exampilnecsl luadtei tluodnegsi,t udesd,i rceocmtptiaiosmnsoes fsd, a y
anndo rmalsicsoerIden st.e irnvpamulat pd atcaa bne u sefodrt hfeo llowing
statisotpeircaatli oSnusm:,A veragMea,x imuMmi,n imuMme,d ian,
MajorMiitnyo,r Diitvye,r (sViatryi aentRdya )n ge.
• OrdiDnaatla .
DefinitMieoans:u remtehnaqttus a ntdiiffyf erbeyno cred(sei r. ient. e rms
ofv aluseusca hs' moroer'' l es'sl'a,ro gre' rs'm allneomrta' g)n,i ttuhdaet
ist,h sei zoeft hien terivsna olstsp eciOfifteedun.s ewdh erqeu antitative
differencaepsp arbeunhtta rtdom easu(rie.w eh.e vna lues rae present
are
rankoerdd eErxa)m.p liensc ltuhddeei stinbecttwieoeponno r,m oderate,
angdo oqdu alaigtryi cullatn(udgr iavnleo is n dicoafte ixoanch tolwmy u ch
better/ewaocrhs ei s otthhaenOr rstd)hi.ein naplmu atp d atcaa bne u sed
fotrh efo llowsitnagt isotpiecraaltM iaoxnism:u Mmi,n imum> Median,
MajorMiitnyo,r Diitvye,r (sVairtiye atnyRd) a nge.
INTROOUCTNITOOENVIROM E TALDATAANALYSISANMDODELLING 3
• NominaDla ta.
DefinitiVoanl:u etsh arte presqeunatl itriaetsh tehra nq uantiatnided so
sow ithoaunty r eferetnoca e l inesacra l(ei .'em.e asuremiennt te'r mosf
namesor d esignatoifod niss cruentiet osrc ategorEixeasm)p.l iensc lude
telephnounmeb erpso,s tcodoerss o,i tly peNso.m inailn pumta pd atcaa n
beu sedf ort hef ollowsitnagt isotpiecraalt ions: MMianjoorriiattnyyd,,
Divers(iVtayr iety).
Datar epreenstation
1.1.2
Spatidaalt caa nb er epresenitnae ddi fferentt awbalyec:sh ,a rtgsr,a phics,
etcV.i sualins oaftr iaowd atai sa veryi mportpaanrt t soof- calelxepdl oratory
dataa nalysIitgs i.v eas fi rsitm pressaiboonu tth es patioarlg anisaotfti hoend ata,
clusteorfim nogn itornientgw orakvsa,i laboifle irtryoa rnsdo utlieetrcs.,
Theraer mea nyw aysf osrp atdiaatlva i sualisiantcilound,si inmgp dlaet pao stplot
(colouorfps l osty mboldse penodn d atvaa Jueasr)e,a -of-inpflluoetniscn,ed icator
plot(sd ataar et ransfontnoie ndd icatsoeres ,fo llocwhianpgt eprrso)p,o rtipolnoatls
(plottsiynmgb oilsp roportitootn haedl a tvaa luee)t,cS .i mplaen ds traightforward
interpolmaettihoondc sa nb eu setdo v isualise wdealtTlah. e sa asm em ethocdasn b e
usetdo v isualtihsere e suolfts sp atdiaatlma o dellitnoog.
�
,
�
� !i...
� !
11
�
§ ... e ·" )t 49 f '1l1 �1$ UI NI 131
� r;- Rrr.I!
•.. .,,,,.i:1�_1:1
J.1E xamploefvs i sualiosfa2tDdi aotnaa n dt hree suolftm sod elling.
Fig.
An importdaanttva i sualisaantdic ohne ckitnogo ils b aseodn Geographical
InformatiSoyns temSsu.c hv isualishaetlipousnn derstantdhienr ge lationships
betwereanw d ata/resouflm tosd ellwiintgc ho rrespongdeionggr aphirceaflelrye nced
infom1ation.
4 ANALYSIASN DM ODELUNGO FS PATIAL ENVIRONMAENNDTP AOLL LUTIDOANT A
Continiunotuesr povlaartiea(dbc loensc entroaftp ioolnlsu tairotenh t)e y pe
ofd attah awtew ilald drmeasisn Elyxa.m ploefs tshpea tdiaatalan dt hree suolft s
modelcloinntgi niunotuesr pvoalraitaebdl perse seinnFt iegdu lrl.e.
are
Jnt hcea soefc ategovrairciaalab nle exsa,m polfse o tiylp aepsp earisnF igure
as
1.w2i.t thh pel aairneb ae longtioon ngec ategory.
Ofc ourvsies,u aliosfda attiaaon ndt hree suslhtosub leda ppropfroitrah tee
qualaintdqy u antoifdt ayt aan dt hoeb jectoiftv hesest udIyns. o mcea see.,g .
simulattihoern ass,tp erre sentaarteti hoemn oss atp propvriisautael tiooslisn g
becauosfve a riaboifdl aitatany sd u ppoWrtb.e nu sisnmgoo thimnogd eilsso,l ines
presen(tdaetliionnoe faz toinoecnsa )bn e a pplied.
Lng enervails,u aliosfda attriaeo flne bcatssti ocp oloogbijceauclst esfod r t he
20d atpao:i nltisna,en spd o lygTohnesst.oe p olougniictastl h gaerr aep hbiacsaoilfs
GeograpShyisctaealmsw s e ll.
I
•
l 1
Fig1.. 2S oitlype variabiinBl riitya nrsekg i(oRnu ssiAan) e.x ampolfec ategordiactmaaal p pinDgi.ff erent
coloucrosr respotnodd i ffesroeinlt types.
l.1D.a3t foar mats
Thearreme a ndya tfao rmwaitdse ulsyefo dr s tatiasntailcayanslfdi o s(r s patial)
geostatTihsetreiexc icsso.tn verftreoermas c fho rmtaoat n othGeero.E AfiSl ies a
wideulsyes dt anddaartfidal. i eng eostaitTihsiitssai p clsa.i nAfiSlChela lv isnigm ple
strucTthueGr ee.o EAfiSl ies b asfiilcte y pfeo trh wee ll-kGnSoLwInsB o ftware
libr[aDreyu tasncJdh o ume1l9,9 8G]e.o sOtffiacte ( GSOs)o ftwaarcec ompanying
thbeo ouks eGse oEAfiSl eisna ddittiooo tnhfi elrfoe r mats.
Thefirs tf ewli noefas s amlpeG coEAfoSr mafitl aer per esefonrtt ehhdee ader.
Thefirs t linoef tfihlceeo ntaadi enssc ritpitt(iluvtepeo 8 0c haractesresc)o.n dT he
line intdhnieuc mabtoeefrsv a ria(bNlVeAsRi )nt hdea tfial( ew iatm ha ximoufm4 8