ContentslistsavailableatScienceDirect
International
Journal
of
Applied
Earth
Observation
and
Geoinformation
j ou rn a l h o m epa g e :w w w . e l s e v i e r . c o m / l o c a t e /j a g
Multitemporal
landslides
inventory
map
updating
using
spaceborne
SAR
analysis
C.
Del
Ventisette
∗,
G.
Righini
1,
S.
Moretti,
N.
Casagli
EarthScienceDepartment,UniversityofFirenze.ViaLaPira,4,50121Firenze,Italy
a
r
t
i
c
l
e
i
n
f
o
Articlehistory: Received7October2013 Accepted21February2014 Keywords: Landslidesinventory Surfacedeformation SARinterferometry Remotesensing Valfurvaa
b
s
t
r
a
c
t
Deepseatedgravitationalslopedeformationandslowmovinglandslidesonlargeareaswereanalyzedby spaceborneSARinterferometry:atestsiteintheItalianAlpsofabout300km2wasselectedforupdating
pre-existinglandslideinventorymapsbasedontheadvancedinterferometricprocessingtechnique (A-DInSAR).
SARimagesfromERS-1/2satellites(1995–2000)andfromEnvisatsatellite(2002–2009)havebeen used,allowingthedeferred-timeanalysisofpastmovementsandtherecordofrecentslope move-ments.Inthemulti-temporalupdatedlandslideinventorydatabase,thecharacteristicsofthelandslides werehighlighted:geometry,stateofactivity,typology,monitoringsystems,interventions,sourceof informationandtheupdatingtimeandactions.Furthermore,foreachlandslidearea,theoccurrenceof persistentscattererspointsandthestatisticaldescriptionoftheirvelocitieswerereported.This method-ologymayallowthesystematicupdatingoflandslidesinventorymapskeepingallinformationoneach landslide,becomingthebasictoolfortherealizationandupdatingofthematicmapssuchasthelandslide susceptibilitymap.
©2014TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/3.0/).
1. Introduction
Thecostnecessarytomeetthehydrogeologicaldisastersisone ofthemajoritemsofexpenditureforthecivilprotection authori-ties.Therefore,inordertoreducecosts,itisessentialtoworkfora properlandmanagementandplanning.Theassessmentofthe spa-tialdistributionandstateofactivityoflandslideprocessesiscrucial forlandslidehazardandriskanalysisonaregionalscale,aimedat properurbanplanning.
NumerousapplicationsofSyntheticApertureRadar(SAR)data togrounddisplacementdetectionhavedemonstratedthatitisa usefultechniqueforslow-movinglandslidecharacterizationand mappinganditpermitstoreconstructthelandslideactivitywith a millimetre precision (Rott et al., 1999; Ferretti et al., 2001; MassonnetandFeigl,1998;Hilleyetal.,2004;Strozzietal.,2005; Pratietal.,2010;Lauknesetal.,2010;Herreraetal.,2013;Bianchini etal.,2012b).Coupledwithpre-existinglandslideinventorymaps
∗ Correspondingauthor.Tel.:+390552055302;fax:+390552055317.
E-mailaddresses:chiara.delventisette@unifi.it,chiara.delventisette@gmail.com
(C.DelVentisette).
1 Presentaddress:ENEA,BolognaResearchCenter,ViaMartiridiMonteSole4.
40127Bologna,Italy.
andthematicdata,SARinterferometryleadstoanefficient meth-ods tomake or updatelandslides inventoryespecially at basin scale(ColesantiandWasowski,2006;Hilleyetal.,2004;Meisina etal.,2008;Cascinietal.,2009;Herreraetal.,2009;Nottietal., 2010;Righinietal.,2012;Bianchinietal.,2012a;Liuetal.,2013; Bianchinietal.,2013;Tofanietal.,2014).SARtechniquesare suit-abletoolsinchecking/updatinginventorymapsdealingwithmass movementphenomenawhosetypicalvelocityvaluesrangefrom fewmillimeters/yearupto1.6m/y,i.e.,extremelyslowlandslides accordingtotheclassificationofCrudenandVarnes(1996).Indeed, theconventional methods forslope instabilityanalysis,as field campaigns,insitumeasurementsoraerialphotointerpretation, arenotalwayspracticallysuitableforsystematicinvestigationsof landslidephenomenaatsuchscaleandthequalityandaccuracy ofthemapsarestronglyrelateronthescaleresolution(Guzzetti, 2004).Furthermore,thankstomorethan15yearscoveredbyradar images,thisremotesensingtechniqueenablesaspatiallyand tem-porallydetailedcharacterizationofdisplacementrates.
In this paper we present the resultsobtained by the inter-pretationofA-DInSARsatellitedatasetandtheirintegrationwith geologicalandgeomorphologicaldatatoobtainamulti-temporal updatingoflandslideinventorymap.Theactivitiesheredescribed were carried out in the framework of two European funded project:(1)Prevention,InformationandEarlyWarning–PREVIEW http://dx.doi.org/10.1016/j.jag.2014.02.008
C.DelVentisetteetal./InternationalJournalofAppliedEarthObservationandGeoinformation30(2014)238–246 239
Table1
Matrixofactivityusedtoupdatelandslideinventorymap.
a) Activity matrix used when only with ERS dataset are available ERS < 1.5 mm/y ERS > 1.5 mm/y Original
landslides inventory
Active Dormant Active
Dormant Dormant Active
Relict Relict Active
b) Activity matrix used when both ERS and Envisat data are available ERS < 1.5 mm/y ERS > 1.5 mm/y Envisat < 1.5 mm/y Relict Dormant
Envisat > 1.5 mm/y Active (reactivated) Active (continuous)
c) Activity matrix used to update a pre-existing landslide inventory map when both ERS and Envisat data are available
ENVISAT < 1.5 mm/y ENVISAT > 1.5 mm/y 2008
landslides inventory
Active Dormant Active
Dormant Dormant Active
Relict Relict Active
Landslides Platform (Sixth Framework Programme) and (2) Landslide Modelling and Tools for vulnerability assessment Preparedness and recovery management – LAMPRE (Seventh FrameworkProgramme).
In particular this work presents one of the outcomes in monitoring the deep-seated and slow-moving landslides using remote-sensinginterferometrictechniquesandtheintegrationof diverseinformationsourcesandpreoperationalfunctionstoobtain amulti-temporalupdatedlandslideinventorymapsusefulto esti-matelandslideriskassessmentandtoperformhazardzonation.The testsiteislocatedinValfurva,eastofBormio,intheRhaetianAlpsof theLombardiaRegion(Fig.1).LombardiaRegionisoneofthemost populatedandurbanizedregioninItalyanditisalsoveryprone tolandslidingsotheriskishighforhumanlifeandinfrastructures. TheValfurvaareais characterizedbyhighdensityof significant rock-slidesanddeep-seatedgravitationalslopedeformationsthat couldbeinvolvedmanycitizens(Agliardietal.,2001;Crostaand Agliardi,2003;DelVentisetteetal.,2012).
IntheValfurvaarealandslidesaffectpre-Permianmetapelites, metabasitesandmarbles,aswellasLatePleistoceneandHolocene glacialandrockglacierdeposits.Thedeformationstartedafterthe Late-Wurmianage(15,000±11,000yearsB.P.),andcontinueduntil fewcenturiesago,notexcludingapresent-daylow-rateactivity (Agliardietal.,2001).Theevolutionoffaultsystems,resultingin asymmetrictrenches,ledinsomecasestotheprogressivefailure oftheslopeduringthelast10,000years,astestifiedbylarge paleo-landslideaccumulations,anditisstillinprogress(Agliardietal., 2001).
2. Methodology
Slowmovinglandslidesonabasinscalecanbedetectedand analysed through the integration of spaceborne SAR interfer-ometry data with thematic maps, field campaigns and in situ monitoring(Farinaet al.,2004; Colesantiand Wasowski,2006; Liu et al., 2013; Righini et al., 2012; Bianchini et al., 2012; Herrera et al., 2009; Meisina et al., 2006; Farina et al., 2006; Cascini et al., 2010; Cigna et al., 2010, 2012; Bovenga et al., 2013; Del Ventisette et al., 2013; Tofani et al., 2014). The workflow (Fig. 2)used in this work started fromradar images processing. The radar images (in this paper ERS and Envisat dataset)areprocessedusingthepersistentscattererspairs PSP-DIFSAR technique developed by Telespazio/e-GEOS (Costantini
and Rosen, 1999; Costantini et al., 2002, 2008, 2009). Com-pared to the other persistent scatterer interferometry (PSI) techniques, one of the peculiarities of thePSP-DIFSAR method is touse only the properties of the signal relating to pairs of neighboring points to identify and to analyze the PS. Indeed, two neighbors points are equally affected by atmospheric artifactsandconsiderthespatialityofdata.Thisapproachallows tobetteridentifythePSoptimizingthecapacityofthePSI analy-sisespeciallyinvegetatedareas(weregenerallyPSarenotdense) andwhenthemovementsareornon-linearwiththetime.Like otheradvancedInSARtechniques,PSP-DIFSARestimatesthe inten-sityofdeformation alongtheLineof Sight(LOS)and notalong the real direction of movements. Furthermore new (and more recent) Envisat dataset derived from the Persistent Scatterers Interferometry Project (PSIP)fromthe Italian National Geopor-tal (ING) of theItalian Ministryof Environment, Land and Sea (http://www.pcn.minambiente.it/viewer/)wasanalyzedtoupdate thelandslidesinventoryupto2009.
Theresultsof radarimagesprocessing havebeenintegrated usingaGeographicalInformationSystem(GIS)withancillarydata (such asgeologicaland topographical maps), field surveysand, whereavailable,insitumeasurements.Inthecasestudypresented inthispaperwestartedfromapre-existinglandslideinventory (producedbyRegionalCivilProtectionoftheLombardiaRegionin 1998)inwhichsomecharacteristicsofthelandslideswere high-lighted inthedatabase(suchas geometry,stateofactivityand typology).
The main criteria used to define the state of activity(SoA) wererelatedtothemeanvelocitiesderived fromtheA-DInSAR processing.ToidentifytheunstablePS,athresholdmeanvelocity has been chosen; e.g., ±1.5mm/y (away or towards the satel-lite)inLOSdirection.ThePSthatshowsdifferentaveragespeed value(greaterthan1.5mm/yorlessthan−1.5mm/y)are classi-fiedasunstable.Toestimatethestateofactivityofeachlandslides an “activity matrix” that consider the average speed of PS is applied.
ToovercomealimitationofPSapproach,suchasthelossofthe pointduetoasuddenincreasingindeformationrate,and start-ingfromapre-existinglandslideinventorymap,three different updatedmapswereproduced.Thefirstoneismadeusingonlythe ERSdatasetandapplyingtheactivitymatrixinTable1aandthe secondupdate(for2008update)isimplementedusingbothERS andEnvisatdataandappliedTable1b(Table2).
Fig.1. Localizationofthestudyarea.
FollowingTable1a,theupdatelandslidestateofactivitystarts fromtheclassificationintheinventorymapand,ifthePSPsin land-slideareaareunstablethenewSoAisalways“active”.Inverselyif theoriginalSoAis“active”or“dormant”andunstablepointsare notpresentonthelandslide,thanintheupdatedinventorymap thelandslideisclassifiedas“dormant”.WhenbothERSandEnvisat areavailabletheupdatingwascarriedoutthroughtheintegration betweenthetwodatasets(Table1b).Toupdatetheinventoryup to2009theactivitymatrixinTable1cwasappliedstartingfrom
thedataderivedfrom2008updating.Inthisapproachwhen unsta-bleEnvisatPSsarepresentthelandslidewasdefinedas“active”; reactivateorcontinuousinrelationtothevelocityderivedfrom ERSdata.
Themeaningof“dormant”isherequitedifferentfromstandard definition:inthispapera“dormant”landsliderepresentsthestate ofactivityofalandslidethathasnotshownevidenceofmovements from1992to2000,i.e.,thetimingcoveredbyERSdata,orthat from2002to2009,i.e.,thetimespancoveredbyavailableEnvisat
Fig.2. Proposedworkflowtocreateand/orupdateamultitemporallandslideinventorymaps.PSPDIFSAR:PSP-DIFSARtechniquedevelopedbyTelespazio/e-GEOS;PSIP:
C.DelVentisetteetal./InternationalJournalofAppliedEarthObservationandGeoinformation30(2014)238–246 241
Table2
NumberoflandsidesandaffectedareaderivedfromOLIMclassifiedinrelationto
theStateofactivity.
Stateofactivity (number)
Landsidetype Landslide number Interestedarea (km2) Active(292) Complex 84 3.8 Debrisflow 119 1.7 Flow 1 0.1 Rotationalslide 86 1.8 Topple 2 0.1 Dormant(425) Complex 16 4.3 Debrisflow 7 0.2 Rotationalslide 402 22.8 Relict(88) Complex 11 3.3 Rotationalslide 77 22.9 “n.d.”(56) Toople 33 1.3 Debrisflow 18 0.05 n.d. 5 0.2
data.Obviously,followingthisapproach,anytypeofSoAchangeis possibleifno(orfewandnotrepresentative)PSsareinthelandslide perimeter.
Furthermore integration between the results derived from A-DInSAR processing and available ancillary data and in situ measurementsweremadebeforeappliedeachchangeto elabo-rateanintegratedgeomorphologicalmap(Ciampalinietal.,2012). Tovalidatetheupdatedinventorymapandtoconfirmthemade change,fieldcampaignswereorganized.InparticularonJuly2007, a field survey onthe Ruinon landslide was carried out, in the frameworkofanexerciseregardinglandslideorganizedwithusers (NationalCivilProtectionAgency,CivilProtectionofRegione Lom-bardia,ARPALombardia);theobjectiveoffieldsurveyistoobtain anoverviewoftherecentevolutionofthedebrisflowsand out-crops,andtocheckthestatusoftheinsituinstruments.Several findingsofterrainmovementsweredetectedontheslope corre-spondingtothemainlandslidebodysuchascracks,toppedtrees, andstructuraldamagesonbuildings.Moreover,evidencesoffew localdisruptionswereidentifiedinthemonitoring instrumenta-tion
2.1. Methodslimitation
Though the adopted methodology has many advantages in relationtoconventionaltechniques,thatgenerallyareextremely expensiveintermofcostandtime,therearetwotypesof limita-tionsthatareworthconsideringbeforeusedthisapproachforthe landslidesdetection.ThefirstoneisrelatedtoSARinterferometry approachandconcernstheunderestimationoftherealmovement magnitudeduetothedirectionofmeasurements(LOSdirection) thatdiffersfromtherealmovementdirection.Furthermore, consid-ering the direction of satellitemovements, some directions of movement are not detectable(N-S direction). The secondones regardtheworkflowandtheuseofaPersistentScatterersasmain indicatorforlandslidedetectionandactivity.Indeed,ifthesliding issudden,PSsarelostinthatarea.So,asexpectedbyworkflow, anytypeofchangeininventoryispossible,butthatlandslideis moving!Forthesereasonweusethedatasetsindependentlyand proceedwithconsecutiveupdating.Whenaslidingaccelerationis recognizedasubsetofprocessedimagecanbedesirableevenif inthiswaytheaccuracyofthismethoddiminish.Forthese rea-sonsafieldsurveymustbecarriedouttoresolvetheambiguous interpretationandtovalidatetheupdatesofthelandslide inven-tories.
3. Availabledata 3.1. Ancillarydata
In this paper we integrated the results of A-DInSAR with differentthematicmaps(ancillarydata).Mapsongeology, geomor-phology,tectonicswerecollected.Topographicmapsat1:10,000 scaleweregivenusbytheRegionalCartographicOfficewhilea DigitalElevationModel(DEM)at20mspatialresolutionwas avail-ableatourpremises.Digitalcolororthophotos(VoloItalia2000), with1mofresolutioninmonoscopicconfigurationwasaccessible fortheentirearea.CorineLandCover2006mapat1:100,000(EEA, 2007)wasanalyzedusingthe3rdclassificationrank.
3.2. Originallandslideinventorymap
Theoriginallandslideinventorymapofthestudyareawas pro-ducedbyRegionalCivilProtectionoftheLombardiaRegionin1998. Itispartofthelandslideinventoryofthealpineareasthatisalarge databasewithmorethan60,000phenomena,amongwhich13,863 slides,802complexlandslides, 1000largerock-falls,276 earth-flows,43,600debrisflows.Thevulnerabilityoftheareaisthusan issueasmorethan23km2ofurbanizedareasintheLombardyAlps
arelocatedonlandslides,other6km2lieonalluvialfansrecognized
asactiveandhazardousand,severaldamsarelocatedinproximity tolandslides.
Inthestudyarea,thatcoveredabout318km2,866landslide
(morethan62km2)and13(about 59km2)deep-seated
gravita-tionalslopedeformation(DSGSD)havebeenrecognized(Fig.3). Thestateofactivityofthe866landslideswasclassifiedasfollows inTable2;allDSGSDareclassifiedas“Relict”.
3.3. SARdata
ThePSP-DIFSARprocessingwasappliedbyTelespazioonaset of63images(5imagearediscardedfortheirlowradiometric char-acteristics)acquiredindescendingmodebythesensorsERS1/2in theperiodApril1995–April2001(Track437;Frame2673)and onasetof30images(theAugust8,2002imagewasdiscarded) acquiredindescendingmodebythesensorsEnvisatintheperiod August2002–March2008(Track437;Frame2673).Considering thecharacteristicsoftheimagetheMarch26,1998forERSdata andtheDecember2004imagewereselectedasmasterimage.The referencepointhasbeenchoseninthecenteroftheBormiovillage.
From ERS Images 26,345 PSPs (with a density of
82.8points/km2) wereextracted (Fig.4a); insteadfrom Envisat
imageswereobtained10624PSP(33.4points/km2;Fig.4b).
Furthermore thePersistent ScatterersInterferometry Project (PSIP) of the Italian Ministry of Environment Land and Sea dataset, acquired both in ascending and in descending orbits (http://www.pcn.minambiente.it/;Fig.5)obtainedandintegrated inGISthroughtheWMSservices,wasanalyzedtoupdatethe land-slideinventorymapupto2009.
ConsideringtheavailabledatainthePREVIEWprojectonlya restrictednumberofcoherentpointsarelocatedonthelandslides andonDSGSDpolygonsoftheOLIM(Fig.6).Thelandslides char-acterizedbythepresenceofcoherentpoints(ERSand/orEnvisat) are151ofthetotal861(interestedarea27.83km2of62.76km2,
morethan40%oflandslidearea).TheDSGSDcharacterizedbythe presenceofcoherentpoints(ERSand/orEnvisat)are10ofthetotal 13(interestedarea49.49km2of59.2km2).
4. Results
Threeupdatedlandslideinventorymapswereproducedusing theA-DInSARtechnique.ThefirstupdateisbasedonERS1/2data;
Fig.3.Originallandslideinventorymap(OLIM;RegioneLombardia,1998).
Fig.4.SpatialdistributionofcoherentpointsextractedfromERS-1andERS-2images(a)andfromEnvisatimages(b)processedintheframeworkofPREVIEWProject.
Fig.5.SpatialdistributionofPersistentScattersderivedfromEnvisatimages(2002–2009)ofthePersistentScatterersInterferometryofthe(http://www.pcn.minambiente.it/)
C.DelVentisetteetal./InternationalJournalofAppliedEarthObservationandGeoinformation30(2014)238–246 243
Fig.6. Overlapbetweenoriginallandslideinventorymapandavailablecoherentpoint.
thesecondstartsfromtheERSupdatedlandslideinventoryandwas madeusingEnvisatdatasetupto2008.Afurtherupdateoflandslide inventorywascarried outbyconsideringtheEnvisatpersistent scatterersupdatedto2009derivedfromPSIP.
4.1. LandslideinventoryupdatesusingERS1/2data(ERSupdated landslideinventorymap)
AmongalltheERS1/2PSPs(26345)onlyarestrictnumberare locatedinareasmappedasmassmovementin theOLIM;5018 (19.04%ofallERScoherentpoints)inlandslidesand3200(12.14%) inDSGSD.ThelandslidescharacterizedonlybyERScoherentpoints are65(7.21km2),whileonlytwoDSGSD(3.39km2)are
character-izedbytheERS1/2PSPs.Thesedata,applyingtheactivitymatrix inTable1a,haveenabledafirstupdateoftheavailableinventory. ERSPSPsallowedtochangethestateofactivityof7landslides(4
rotationaland3topple)andtoidentify4landslides.Regardingthe DSGSD,thestateofactivityof1DSGSDwaschangedfromrelictto active.
4.2. LandslideinventoryupdatesusingERSandEnvisatdata (2008updateand2009update)
ThePSPs extractedfromEnvisatimage updatedto2008are 10,624;only1814(17.07%)and1437(15.53%)arelocatedon land-slidesandDSGSDrespectively.In75(20.35km2)landslidesEnvisat
PSPsarepresent.Changesoccurredin42landslides(Fig.7a);in35 ofwhichthestateofactivitywaschanged.
Thenew(until2009)ascendinganddescendingEnvisatdataset allowedtoupdate/verify139landslide(28.7km2)andtoupdate
theinventoryupto2009(Fig.7b).
Fig.7.(a)2008updatedlandslideinventorymapusingbothERS1/2andEnvisatPSPsderivedfromPREVIEWProject.(b)2009updatedlandslideinventorymapusingdataset
derivedfromPSIPandanalyzedintheframeworkofLAMPREproject.LandslidesareinthinlinewhileDSGSDareinthickline.Differentcolorshowthestateofactivity:red:
Fig.8. ComparisonbetweenOLIM(a)andmulti-temporal(b)updatedlandslideinventorymap.
Table3
Resultsderivedfromtheapplicationofproposedmethodology(comparisonbetweenOLIMand2009inventory).
Bynumber Byarea(km2) Bytipology:number/affectedarea
Rotational Complex Topple Debris
Newlandslides 5 0.4 N.V. N.V. N.V. N.V.
Stateofactivity 62 14.4 50(13.5) 3(0.2) 6(0.4) 3(0.3)
StateofactivityGeometry 3 0.2 3(0.2) – – –
Geometry 6 0.4 1(0.1) 2(0.1) – 3(0.2)
Confirmed 135 17.8 100(12.8) 18(4.5) 2(0.3) 15(0.2)
N.V.=notvalidated.
EnvisatPSPslocatedinto9DSGSD(48.3km2)allowupdating thestateofactivityof7DSGSDfromrelicttoactive(Fig.7). 5. Discussionandconclusion
Morethanhalfofthemappedlandslidesintheoriginallandslide inventorymaphavebeenupdatedapplyingtheproposedmethod
(Fig.8).TheupdatesoftheOLIMgiveevidenceoftheimportance ofthedetectionandmappingof slopeunstableareasusingthe grounddeformationratesfromPSIdata.Eachtypeofvariationare reportedinTable3.Inmorethan8km2(65landslide),
represent-ingjustunderhalfoftheentiresurfaceinlandslide,theupdating regardsthestateofactivity(Table3;Fig.9).Mainchangeconcern theattributionofanactivestateto37landslides,involvingseveral
Fig.9. Examplesofchangesinlandslideactivityapplyingtheproposedmethods(locationisinFig.8)betweentheoriginallandslideinventorymap(ontheleft)and
C.DelVentisetteetal./InternationalJournalofAppliedEarthObservationandGeoinformation30(2014)238–246 245
Table4
Proposedchanges inlandslide activity (comparisonbetweenOLIM and 2009
inventory). Originalstate ofactivity Updatedstate ofactivity Numberof landslides Landslides interestedarea (km2) n.d. Active 1 0.2 n.d. Relict 3 0.1 Relict Active 13 6.4 Relict Dormant 10 3.4 Dormant Relict 6 0.4 Dormant Active 24 2.1 Active Dormant 5 0.4 Table5
ProposedchangesformappedDSGSD.
Numberof DSGSD DSGSD interestedarea (km2) Confirmed 4 12.6
Stateofactivitychanged(from “stabilized”to“Active”)
6 33.83
Stateofactivitychanged(from “stabilized”to“Dormant”)
3 9.5
squaredkilometers,alreadymappedinOLIMasdormantorrelict andofadormantstateto10landslidepreviouslyclassifiedasrelict (Table4).Theseupdatesprovidecrucialinformationtoend-users andstakeholdersfortheproperriskmitigationactionsplanning, consideringalsothefactthathigherdensityofPSisretrievedwhere thepresenceofurbanfabricandroadnetworkrevealsmanygood radar reflectors.Indeed,furtherimplementationsof theapplied methodologycouldrelyontheintegrationoftheupdatedlandslide inventorymapwithadetaileddatasetofsurvey-recordeddamages tofacilitiesthatmayrepresentindicatorsofmovements(Cascini etal.,2013).
Ontheotherhand,thestateofactivitywasdowngradedfor5 landslidesonly,fromactivetodormant,alsobecausetheuseof theactivitymatrixiscarriedoutusinga‘conservative’approach andtheactivityofsuchphenomenaisnotlowered,unlessfield evidencesandinsitudataconfirmclearlythismodificationofthe activity.
AsconcerntheDSGSDmappedintheinventory,inelevenof themPSPsdirectlyconnectedtoDSGSDactivityaredetected.The proposedchanges instate ofactivityare shown inTable 5; no updateregardinggeometryhasbeenpossibleduetothelackof asufficientnumberofPSP.
Theupdatingofslow-movinglandslideinventorymapscanbe anextremelyexpensiveandtimeconsumingtaskwhencarriedout withtraditionaltechniquesonly.AsdemonstratedonValfurvaarea theapproachusingremotesensingdatarepresentsavaluabletool andasustainablemethod,intermoftimeandcosts(inrelationto theobservedarea),toaperiodicupdateofthestateofactivityof slowmovinglandslidesatregionalscaleinrelationtonetof moni-toringsystems.HoweverthemainlimitationsofthePSItechniques, suchasnotenoughbenchmarksorsatelliteimagesavailablefor certainperiod,theLOSdirectionandtheresolutioncouldaffectthe reliabilityofresults;improvementswillcomefromnewsatellite missionswithhigherspatialandspectralresolutionanddifferent spectralbandsandfromenhancementofradardataprocessingthat willmakeasignificantadvanceinobtainingmoreandwidespread PS.
The results of this work confirm the capabilities of multi-interferometricInSARdatatosupportlandslideinvestigationat regionalscaleandthecontributionofsuchapproachtodefinition ofasustainableurbanplanningandinfrastructure development whereriskconditionsarehigher.Infact,consideringthehighcost
derivedfromlandslidedamagesandthedifficultiesinthe assess-mentofthestateofactivity,theuseoftheproposedmethodology cangiveanaddedvaluetostakeholdersforriskmitigation. Acknowledgments
ThisstudywaspartiallyfoundedbytheSixthFramework Pro-grammeoftheEuropeanCommission:Prevention,Informationand Early Warning (PREVIEW)and partiallyby the Seventh Frame-workProgrammeofEuropeanCommission:LandslideModelling andToolsforvulnerabilityassessmentPreparednessandrecovery management(LAMPRE).
We thank theentireteam of EarthScienceDepartment and the“LandslideServices”teamof PreviewProject.We especially acknowledgethe Officeof Prevention of theCivil Protection of RegioneLombardiaandtheItalianNationalDepartmentofCivil ProtectionbothofwhichwereinvolvedintheactivitiesofPREVIEW Project.CiminelliM.G.,CiccodemarcoS.,PellegrinoD.,Costantini M.,MalvarosaF.andMinatiF.frome-GEOS,arethankedfortheir supportandforERSandEnvisatdataprocessing.
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