Bajat, Branislav

Kilibarda, Milan

Krunić, Nikola

Sekulić, Aleksandar

English

GraFar - Repository of the Faculty of Civil Engineering

Editors:Dr Biljana Abolmasov, University of Belgrade, Faculty of Mining and GeologyDr Miloš Marjanoviđ, University of Belgrade, Faculty of Mining and GeologyUroš uriđ, MSc, University of Belgrade, Faculty of Civil Engineering Proceedings of the 2nd Regional Symposium on L A N D S L I D E S in the AdriaƟ c-Balkan Region, ReSyLAB, Belgrade 14-16 May 2015University of Belgrade, Faculty of Mining and GeologyMay 2017PUBLISHER: University of Belgrade, Faculty of Mining and GeologyFOR PUBLISHER: Prof. Dušan Polomēiđ, Dean COVER DESIGN:  SrĜan KrsƟ đPRINTED BY: Sapient GraphicsISSUED: 250 CopiesFRONT COVER PHOTO: Landslide Leva Reka, Kraljevo, Serbia (by Biljana Abolmasov)BACK COVER PHOTO: Landslide Leva Reka, Kraljevo, Serbia, UAV photo (by Dragan Milovanoviđ and Stefan Miljkoviđ)CIP - ʶ̶̨̛̛̯̣̠̌̌̐̌̌̚ ̱ ̶̡̛̛̛̪̱̣̠̍̌ʻ̨̬̦̌̔̌ ̨̡̛̛̣̯̖̍̍̌ ˁ̛̬̠̖̍, ʥ̨̖̬̐̌̔551.4.037(082)624.131.53(082)624.138(082)REGIONAL Symposium on Landslides in the AdriaƟ c-Balkan Region (2 ;2015 ; Beograd)    Proceedings of the 2nd Regional Symposium on Landslides in theAdriaƟ c-Balkan Region, RESYLAB, Belgrade 14-16 May 2015 [Elektronskiizvor] ; editors Biljana Abolmasov, Miloš Marjanoviđ, Uroš uriđ /editors Biljana Abolmasov, Miloš Marjanoviđ, Uroš uriđ. - Belgrade :University of Belgrade, Faculty of Mining and Geology, 2017 (Belgrade :Sapient Graphics). - 1 elektronski opƟ ēki disk (CD-ROM) ; 12 cmSistemski zahtevi: Nisu navedeni. - Tiraž 250. - Invited lecturer: str.256-261. - Nasl. sa naslovnog ekrana. - BibliograĮ ja uz svaki rad. -Registar.ISBN 978-86-7352-296-8a) ʶ̛̛̣̹̯̌̚ - ʯ̶̨̛̛̬̦̍ b) ʶ̨̛̭̦̖ - ʯ̶̨̛̛̬̦̍COBISS.SR-ID 234417420DisclaimerThe content of this proceedings does not reﬂect the opinion of the editors or publisher. Responsibility for the information and views expressed in the papers lies entirely with the author(s). Proceedingsofthe2ndRegionalSymposiumonLandslides,Belgrade,2015   Assessment of population vulnerability in risk analysis using dasymetricdatabaseofSerbiaBranislavBajat(1),NikolaKruniđ(2)MilanKilibarda(1),AleksandarSekuliđ(1)1) UniversityofBelgrade, FacultyofCivilEngineering,DepartmentofGeodesyandGeoinformatics,BulevarkraljaAleksandra73,11000BelgradeSerbia2) InstituteofArchitectureandUrban&SpatialPlanningofSerbia,BulevarkraljaAleksandra73,11000BelgradeSerbiaAbstract This study reveals the importance ofdisaggregatingpopulationdata thathaspreviouslybeenaggregatedby census tractsormunicipalitypolygons inorder to achieve more accurate populationdistribution/location. Demographic census data aremappedasstatisticalsurfacesandareoftenpresentedonchoroplethmaps. Themajor drawback of suchmaps isthatpopulationdistributionsareoftenmisrepresentedashomogeneous cartographic unitswhen in fact thismaynot be the case. Thesemisrepresentations of data canfalsely omit uninhabited areas from within thecartographic units. A newlyǦdeveloped dasymetricmapping method that is suitable for modellingpopulationdistributionontheregionalorcountryscaleispresented in thispaper.Thispaper outlines an originalsolution for dasymetric mapping that is based onpreviousresultsconcerning theexperiencesofEuropeanandworldwideprojectsrelatedtodasymetricpopulationdensity grid production. The region of interest in thisstudy is Serbia, for which a database of the entireterritory’s spatial distribution of population andpopulationdensityhasbeenconstructedandisbasedonproposedmethodologyherein.Theconstructeddatabaseprovides a population statistical surface of 100 x 100mresolution,anditisalreadyavailableforfreeonlinetoallexpertsdealingwithhazardriskmanagement.A case study is presented here that compares theofficial aggregated estimates of Serbian population thatarepotentiallyimpactedbylandslidehazardproneareasin the City of Belgrade with estimates obtained bydisaggregateddasymetricmapping.Theobtained resultsindicateseveredifferencesinpopulationcountsobtainedbythesetwodifferentdatasources.Keywords dasymetric modelling, land use suitability,cartographicwebserviceIntroductionThe importance of disaggregating population data thathasbeenpreviouslyaggregatedbycensustractsorotherunitshaspreviouslybeenhighlightedinmanyhazardriskanalysisstudiesthataimtowardsachievingmorerealisticpopulationdistributions (Chenetal.,2004;MaantayandMaroko,2009;Freire,2010;GiordanoandCheever,2010).Cartographic presentation of heterogeneity/homogeneity inthespatialdistributionofpopulation isstill amajor problem inmodern geography and othergeoǦsciencesaswell.Thetraditionalmethodofthematicor choroplethmapping rarely gives satisfactory results.The traditional choropleth map creates a misleadingimpressionofauniformdistributionofaphenomenoninspace, although it most often varies in the specificgeographicarea.IntheRepublicofSerbia,thepopulationdata are usually presented on the level of censusdesignation places by the aggregation of census andstatisticaldistrictsdata.In this study, Geographic Information Systems(GIS) technology constitutes the basis for themethodology developed to identify a vulnerablepopulation for any possible hazard.GIS technologyhasled to thedevelopmentof risk informationsystems thatcan be used to analyse risk and evaluate theconsequencesofdecisionsmade thatmitigateor reducerisk(vanWesten,2004).WorldgriddeddemographicdatabasesOneof theexamples formapping thespatialpopulationdistribution at a global level is the LandScan GlobalPopulationDatabase(LSGPD),whichhasbeendevelopedbytheOakRidgeNationalLaboratory(ORNL)withintheGlobalPopulationProject for theneedsofassessing thepopulationvulnerabilityafterdisastrousevents (Dobsonet al., 2000). The LandScan database is a dasymetricmodelofapopulationdistributioninagridformatandisbased on accumulated census data obtained fromcountries that provide a 24Ǧhour ambient populationestimate.The resolutionof theLandScandatabase isof30arcsecondsby30arcseconds(gridsize1×1km).There are also other public available databasesfordifferentpurposes on the global level (Bengtsson etal., 2006, Balk and Yetman, 2004, CIESIN and CIAT,2005) that depict population density over the entireworld,However,allofthesepubliclyavailablepopulationdensitiesareinappropriateforsmallerscaledemographicstudies that include analyses formicrolocations and forlarge scale social, economic and environmentalapplicationssuchashazardmapping.93B.Bajat,N.Kruni©,M.Kilibarda,A.Sekuli©–Assessmentofpopulationvulnerabilityinriskanalysis ExistingdesymetricdatabasesinSerbiaThere are already a number of studies related to thedasymetricmappinginSerbia.Theyaremainlyrelatedtoregionalor localspatial levels.Thepossibilityofusingadasymetricmethodforthepurposeofassessing“daily“or“ambient population“ and “night“ population in theterritory ofVojvodina has been presented in the paperwrittenbyagroupofauthors(Kruni©etal.,2011).Bajatetal.(2013)recentlypresentedamethodology forrescalingsoil imperviousness data by using a spatial database ofbuildingheighttypologyoftheCityofBelgrade inorderto develop a dasymetricmodel thatmight be used forestimatingpopulationdistributionsinurbanareas.MaterialsandmethodsPopulationdataofSerbiaTheRepublicofSerbiacoversanareaof88,361km²and,in accordance to the 2011 census, has a population of7,120,666 (no data for the Autonomous Province ofKosovoandMetohija)withapopulationdensityofabout92 inhabitants per km2. The estimated population ofSerbia in 2006 (SORS, 2012) was used in this study. Atotal of 160municipalities ofwhich 16 belonged to theCity of Belgrade, were encompassed within this study.The total estimated population in the year 2006 was7,411,982 inhabitants. The distribution of populationdensityinaformofchoroplethmapisgiveninFig.1(left).Figure1Choroplet(left)anddasymetric(right)mapsofpopulationdenistyinSerbiafortheyear2006.AppliedDasymetricModelAdasymetricdatabaseofSerbiareferringtotheyear2006wasproducedand isbasedonanadapteddegreeofsoilsealingrasterlayerandterrainaltitude:³ ASSGD ,   [1]where GD represents dasymetric density, SSrepresents soil sealing and A represents altitude ofterrain. The soil sealing database represents the landsurfacethathasbecomeimperviousduetoanthropogenicimpact (Burghardt, 2006.) This database is available intwo spatial resolutions 20 m and 100 m, and for thispurpose we used the coarser one. The ASTER GDEMdigitalterrainmodelwithaspatialresolutionof30m(forthis study resampled to 100m resoultion)wasused forterrainaltitudes.More details about the methodology used forgeneratingadasymetricdatabaseofSerbiaareavailableinthepaperpresentedbyKruni©etal.(2015).94Proceedingsofthe2ndRegionalSymposiumonLandslides,Belgrade,2015   The result of dasymetricmodeling is presented asthematicmap in Figure 1 (right). The dasymetricmapindicates a more realistic presentation of a spatialpopulation distribution in comparison to a classicalchoroplethmap that reveals official publically availablecensusdata.The final results of the dasymetric database ofSerbia are portrayed as a thematic map that can becommunicated and shared easily through thecartographicwebmapǦbased service.Thewebmapwasachieved using recently developed packages in the Rlanguage environment including the newly developedpackageplotGoogleMaps(Kilibarda&Bajat,2012),whichis based on Asynchronous JavaScript and XMLtechnology (AJAX) and Google Maps ApplicationProgramming Interface (API) service that producesHTML filemapmashups. Thewebmap is available atURL:http://osgl.grf.bg.ac.rs/PopDensSerbia2006.html.Moreover, thedataof thedasymetricdatabase arealso available to download for each municipality inGeoTiffformat(byclickingonmunicipalitypolygon).Figure2Hazardpronedelineatedareasoverthechoroplet(left)anddasymetric(right)populationdensitymapsofBelgradecityarea.DataprocessingandresultsThe landǦuse suitability (LUS) data layer (Djuri© et al.2013) is readily usable in the GIS environment. TheMasterPlanoftheCityofBelgradewasusedtodelineateareas that are susceptible to landslide and groundsubsidencehazard.Theotherclassofinputdataconcernsspatialpopulationdistribution.The hazardǦprone areas were delineated byoverlaying the official data of population distributionaggregatedonmunicipalitylevelwithLUSlayerpolygonsthat refer tounsuitableandveryunsuitable landclasses(Fig2left).Thetotalcountofvulnerablepopulationwascalculated by multiplying the areas of hazard pronepolygonareaswiththeaveragepopulationdensityrelatedto particular municipality. The total number ofvulnerablepopulationobtained insuchway is48,418forthe entire case study area. On the other hand, byapplying the sameprocedurewith thedasymetric rasterdata,thetotalnumberofvulnerableinhabitantsis23,119.Thedifferencebetweenthosetwoestimatedamountsisaconsequence of the fact thatmost of the hazard proneareasactuallycoveruninhabitedspace.One can get the opposite results ifwe focus on aparticular hazardǦprone polygon covering a populatedarea. For example, the polygons depicted in Figure 3indicate 2527 people in accordance to the daymetricdatabase (Fig3right)areatriskwhereasofficialdataof95B.Bajat,N.Kruni©,M.Kilibarda,A.Sekuli©–Assessmentofpopulationvulnerabilityinriskanalysis population distribution indicates 578 people are at risk(Fig3left).Figure 3 Hazard prone delineated polygons overofficial data of population distribution (left) anddasymetricdatabase(right)ofBelgradecityarea.ConclusionOfficialcensusdatathat isusuallyaggregatedoncensustractsorevenon themunicipality levelarenot suitablefor population vulnerability assessment with regard tothebiasedestimateofpeopleunderrisk.Undercountingor overcounting of an impacted population could haveseriousimplicationsforriskmanagementandmitigation.Thedasymetricmappingmethodcouldsolvethisproblembydividingthemodelledspaceintozoneswithahigher degree of homogeneity; thereby reflectingmoretruthfully thevariations ina statisticalpopulation layer,with support of additional variables and theircorrelations. The production of population surfacemodels suitable for risk analysis applications can beachieved by coupling this methodology with the GISenvironmentandfreeopenaccessdatabaseofsoilsealing(soilimperviousness)..Theobtaineddatabase canbe an instrument toassess costǦbenefit ratios when local and governmentauthorities analyze the effect of certain mitigationmeasures. Moreover, the database could serve as animportant tool that canbe implemented in thedisasterawareness phase of disaster risk management at themunicipallevel.AcknowledgmentsThisworkwas supportedby theMinistry ofEducation,ScienceandTechnologicalDevelopmentof theRepublicofSerbia(ContractsNo.III47014andTR36035).ReferencesBajat B, Kruniđ N, Petroviđ MS, Kilibarda M (2013) Dasymetricmodelling of population dynamics in urban areas. GeodetskiVestnik.57(4):777Ͳ792.Balk D, Yetman G (2004) The global distribution of population:Evaluatingthegainsinresolutionrefinement,documentationforGPWv3. GPWv3 working paper. CIESIN. (available athttp://sedac.ciesin.org/gpw/docs/gpw3_documentation_final.pdf)BengtssonM, Shen Y, Oki T (2006) A SRESͲbased gridded globalpopulationdatasetfor1990–2100.PopulationandEnvironment.28(2):113Ͳ131.Burghardt W (2006) Soil sealing and soil properties related tosealing. Geological Society, London, Special Publications. 266:117Ͳ124.Chen K,McAneney J,BlongR, LeighR,Hunter L.,Magill C (2004)Definingareaatriskanditseffectincatastrophelossestimation:adasymetricmappingapproach.AppliedGeography.24(2):97Ͳ117.CIESINandCIAT(2005)GriddedPopulationoftheWorld,Version3(GPWv3). Palisades, NY: Socioeconomic Data and ApplicationsCenter (SEDAC), Columbia University. availableathttp://sedac.ciesin.columbia.edu/gpwDobsonJE,BrightEA,ColemanPR,DurfeeR,andWorleyBA(2000)Landscan: A global population database for estimatingpopulations at risk. Photogrammetric Engineering and RemoteSensing.66:849Ͳ857.DjuriđU,MarjanoviđM,ŠušiđV,PetroviđR,AbolmasovB,ZeēeviđS,Basariđ I (2013) LandͲuse suitability analysis of Belgrade citysuburbs using machine learning algorithm, Symposium GISOstrava 2013, CD Proceedings, 21th Ͳ 23th January 2013,Ostrava,CzechRepublic.ISBN978Ͳ80Ͳ248Ͳ2944Ͳ9.Freire S (2010)Modeling of spatiotemporal distribution of urbanpopulation at high resolution–value for risk assessment andemergency management. In Geographic information andcartography for risk and crisis management Konecny M,ZlatanovaS,BandrovaTL.(ed.)SpringerBerlinHeidelberg.(ISBN:978Ͳ3Ͳ642Ͳ03441Ͳ1).p.429.Giordano A, and Cheever L (2010) Using dasymetricmapping toidentifycommunitiesatriskfromhazardouswastegenerationinSanAntonio,Texas.UrbanGeography.31(5):623Ͳ647.Kilibarda M, Bajat B (2012) plotGoogleMaps: The RͲbased webͲmappingtoolforthematicspatialdata.Geomatica66(1):37Ͳ49.Kruniđ N, Bajat B, Kilibarda M (2015) Dasymetric mapping ofpopulation distribution in Serbia based on soil sealing degreeslayer. In Ruzickova K, Inspektor T (ed.). Surface Models forGeosciences.LectureNotes inGeoinformationandCartography.Springer.(inpress).MaantayJ,andMarokoA(2009)Mappingurbanrisk:Floodhazards,race,&environmental justice inNewYork.AppliedGeography.29(1):111Ͳ124.Statistical Office of the Republic of Serbia (SORS) (2012) NaturalchangesofpopulationintheRepublicofSerbia,StatisticalOfficeoftheRepublicofSerbia,Belgrade.vanWesten C J (2004) Geo Ͳ information tools for landslide riskassessment :anoverviewof recentdevelopments.Proceedingsofthe9thinternationalsymposiumonlandslides,June28ͲJuly2,2004RiodeJaneiro,Brazil.pp.39Ͳ56.96

Assessment of population vulnerability in risk analysis using dasymetric database of Serbia

 GraFar - Repository of the Faculty of Civil Engineering


Editors:
Dr Biljana Abolmasov, University of Belgrade, Faculty of Mining and Geology
Dr Miloš Marjanovi?, University of Belgrade, Faculty of Mining and Geology
Uroš ?uri?, MSc, University of Belgrade, Faculty of Civil Engineering 
Proceedings of the 
2nd Regional Symposium on 
L A N D S L I D E S 
in the Adria? c-Balkan Region, 
ReSyLAB, Belgrade 14-16 May 2015
University of Belgrade, Faculty of Mining and Geology
May 2017

PUBLISHER: 
University of Belgrade, Faculty of Mining and Geology
FOR PUBLISHER: 
Prof. Dušan Polom?i?, Dean 
COVER DESIGN: 
 Sr?an Krs? ?
PRINTED BY: 
Sapient Graphics
ISSUED: 
250 Copies
FRONT COVER PHOTO: 
Landslide Leva Reka, Kraljevo, Serbia (by Biljana Abolmasov)
BACK COVER PHOTO: 
Landslide Leva Reka, Kraljevo, Serbia, UAV photo (by Dragan Milovanovi? and Stefan Miljkovi?)
CIP - ?????????????? ? ???????????
??????? ?????????? ??????, ???????
551.4.037(082)
624.131.53(082)
624.138(082)
REGIONAL Symposium on Landslides in the Adria? c-Balkan Region (2 ;
2015 ; Beograd)
    Proceedings of the 2nd Regional Symposium on Landslides in the
Adria? c-Balkan Region, RESYLAB, Belgrade 14-16 May 2015 [Elektronski
izvor] ; editors Biljana Abolmasov, Miloš Marjanovi?, Uroš ?uri? /
editors Biljana Abolmasov, Miloš Marjanovi?, Uroš ?uri?. - Belgrade :
University of Belgrade, Faculty of Mining and Geology, 2017 (Belgrade :
Sapient Graphics). - 1 elektronski op? ?ki disk (CD-ROM) ; 12 cm
Sistemski zahtevi: Nisu navedeni. - Tiraž 250. - Invited lecturer: str.
256-261. - Nasl. sa naslovnog ekrana. - Bibliogra? ja uz svaki rad. -
Registar.
ISBN 978-86-7352-296-8
a) ???????? - ???????? b) ?????? - ????????
COBISS.SR-ID 234417420
Disclaimer
The content of this proceedings does not reflect the opinion of the editors or publisher. 
Responsibility for the information and views expressed in the papers lies entirely with the author(s). 
Proceedings?of?the?2nd?Regional?Symposium?on?Landslides,?Belgrade,?2015 
 
 
Assessment? of? population? vulnerability? in? risk? analysis? using? dasymetric?
database?of?Serbia?
Branislav?Bajat(1),?Nikola?Kruni?(2)?Milan?Kilibarda(1),?Aleksandar?Sekuli?(1)?
1) University?of?Belgrade,? Faculty?of?Civil?Engineering,?Department?of?Geodesy?and?Geoinformatics,?Bulevar?kralja?Aleksandra?73,?
11000?Belgrade?Serbia?
2) Institute?of?Architecture?and?Urban?&?Spatial?Planning?of?Serbia,?Bulevar?kralja?Aleksandra?73,?11000?Belgrade?Serbia?
?
Abstract? This? study? reveals? the? importance? of?
disaggregating?population?data? that?has?previously?been?
aggregated?by? census? tracts?or?municipality?polygons? in?
order? to? achieve? more? accurate? population?
distribution/location.? Demographic? census? data? are?
mapped?as?statistical?surfaces?and?are?often?presented?on?
choropleth?maps.? The?major? drawback? of? such?maps? is?
that?population?distributions?are?often?misrepresented?as?
homogeneous? cartographic? units?when? in? fact? this?may?
not? be? the? case.? These?misrepresentations? of? data? can?
falsely? omit? uninhabited? areas? from? within? the?
cartographic? units.? A? newly?developed? dasymetric?
mapping? method? that? is? suitable? for? modelling?
population?distribution?on?the?regional?or?country?scale?is?
presented? in? this?paper.?This?paper? outlines? an? original?
solution? for? dasymetric? mapping? that? is? based? on?
previous?results?concerning? the?experiences?of?European?
and?worldwide?projects?related?to?dasymetric?population?
density? grid? production.? The? region? of? interest? in? this?
study? is? Serbia,? for? which? a? database? of? the? entire?
territory’s? spatial? distribution? of? population? and?
population?density?has?been?constructed?and?is?based?on?
proposed?methodology?herein.?The?constructed?database?
provides? a? population? statistical? surface? of? 100? x? 100?m?
resolution,?and?it?is?already?available?for?free?online?to?all?
experts?dealing?with?hazard?risk?management.??
A? case? study? is? presented? here? that? compares? the?
official? aggregated? estimates? of? Serbian? population? that?
are?potentially?impacted?by?landslide?hazard?prone?areas?
in? the? City? of? Belgrade? with? estimates? obtained? by?
disaggregated?dasymetric?mapping.?The?obtained? results?
indicate?severe?differences?in?population?counts?obtained?
by?these?two?different?data?sources.?
?
Keywords? dasymetric? modelling,? land? use? suitability,?
cartographic?web?service??
?
?
Introduction?
The? importance? of? disaggregating? population? data? that?
has?been?previously?aggregated?by?census?tracts?or?other?
units?has?previously?been?highlighted?in?many?hazard?risk?
analysis?studies?that?aim?towards?achieving?more?realistic?
population?distributions? (Chen?et?al.,2004;?Maantay?and?
Maroko,?2009;?Freire,?2010;?Giordano?and?Cheever,?2010).?
Cartographic? presentation? of? heterogeneity?
/homogeneity? in?the?spatial?distribution?of?population? is?
still? a?major? problem? in?modern? geography? and? other?
geo?sciences?as?well.?The?traditional?method?of?thematic?
or? choropleth?mapping? rarely? gives? satisfactory? results.?
The? traditional? choropleth? map? creates? a? misleading?
impression?of?a?uniform?distribution?of?a?phenomenon?in?
space,? although? it? most? often? varies? in? the? specific?
geographic?area.?In?the?Republic?of?Serbia,?the?population?
data? are? usually? presented? on? the? level? of? census?
designation? places? by? the? aggregation? of? census? and?
statistical?districts?data.?
In? this? study,? Geographic? Information? Systems?
(GIS)? technology? constitutes? the? basis? for? the?
methodology? developed? to? identify? a? vulnerable?
population? for? any? possible? hazard.?GIS? technology?has?
led? to? the?development?of? risk? information?systems? that?
can? be? used? to? analyse? risk? and? evaluate? the?
consequences?of?decisions?made? that?mitigate?or? reduce?
risk?(van?Westen,?2004).??
?
World?gridded?demographic?databases?
One?of? the?examples? for?mapping? the?spatial?population?
distribution? at? a? global? level? is? the? LandScan? Global?
Population?Database?(LSGPD),?which?has?been?developed?
by?the?Oak?Ridge?National?Laboratory?(ORNL)?within?the?
Global?Population?Project? for? the?needs?of?assessing? the?
population?vulnerability?after?disastrous?events? (Dobson?
et? al.,? 2000).? The? LandScan? database? is? a? dasymetric?
model?of?a?population?distribution?in?a?grid?format?and?is?
based? on? accumulated? census? data? obtained? from?
countries? that? provide? a? 24?hour? ambient? population?
estimate.?The? resolution?of? the?LandScan?database? is?of?
30?arc?seconds?by?30?arc?seconds?(grid?size?1×1?km).?
There? are? also? other? public? available? databases?
for?different?purposes? on? the? global? level? (Bengtsson? et?
al.,? 2006,? Balk? and? Yetman,? 2004,? CIESIN? and? CIAT,?
2005)? that? depict? population? density? over? the? entire?
world,?However,?all?of?these?publicly?available?population?
densities?are?inappropriate?for?smaller?scale?demographic?
studies? that? include? analyses? for?microlocations? and? for?
large? scale? social,? economic? and? environmental?
applications?such?as?hazard?mapping.?
?
93
B.?Bajat,?N.?Kruni?,?M.?Kilibarda,?A.?Sekuli??–?Assessment?of?population?vulnerability?in?risk?analysis?
 
Existing?desymetric?databases?in?Serbia?
There? are? already? a? number? of? studies? related? to? the?
dasymetric?mapping?in?Serbia.?They?are?mainly?related?to?
regional?or? local?spatial? levels.?The?possibility?of?using?a?
dasymetric?method?for?the?purpose?of?assessing?“daily“?or?
“ambient? population“? and? “night“? population? in? the?
territory? of?Vojvodina? has? been? presented? in? the? paper?
written?by?a?group?of?authors?(Kruni??et?al.,?2011).?Bajat?et?
al.?(2013)?recently?presented?a?methodology? for?rescaling?
soil? imperviousness? data? by? using? a? spatial? database? of?
building?height?typology?of?the?City?of?Belgrade? in?order?
to? develop? a? dasymetric?model? that?might? be? used? for?
estimating?population?distributions?in?urban?areas.?
?
Materials?and?methods?
Population?data?of?Serbia?
The?Republic?of?Serbia?covers?an?area?of?88,361?km²?and,?
in? accordance? to? the? 2011? census,? has? a? population? of?
7,120,666? (no? data? for? the? Autonomous? Province? of?
Kosovo?and?Metohija)?with?a?population?density?of?about?
92? inhabitants? per? km2.? The? estimated? population? of?
Serbia? in? 2006? (SORS,? 2012)? was? used? in? this? study.? A?
total? of? 160?municipalities? of?which? 16? belonged? to? the?
City? of? Belgrade,? were? encompassed? within? this? study.?
The? total? estimated? population? in? the? year? 2006? was?
7,411,982? inhabitants.? The? distribution? of? population?
density?in?a?form?of?choropleth?map?is?given?in?Fig.1?(left).?
?
?
Figure?1?Choroplet?(left)?and?dasymetric?(right)?maps?of?population?denisty?in?Serbia?for?the?year?2006.?
?
Applied?Dasymetric?Model?
A?dasymetric?database?of?Serbia?referring?to?the?year?2006?
was?produced?and? is?based?on?an?adapted?degree?of?soil?
sealing?raster?layer?and?terrain?altitude:?
?
? ASSGD , ? ? [1]?
?
where? GD? represents? dasymetric? density,? SS?
represents? soil? sealing? and? A? represents? altitude? of?
terrain.? The? soil? sealing? database? represents? the? land?
surface?that?has?become?imperviousdue?to?anthropogenic?
impact? (Burghardt,? 2006.)? This? database? is? available? in?
two? spatial? resolutions? 20? m? and? 100? m,? and? for? this?
purpose? we? used? the? coarser? one.? The? ASTER? GDEM?
digital?terrain?model?with?a?spatial?resolution?of?30?m?(for?
this? study? resampled? to? 100?m? resoultion)?was?used? for?
terrain?altitudes.??
More? details? about? the? methodology? used? for?
generating?a?dasymetric?database?of?Serbia?are?available?
in?the?paper?presented?by?Kruni??et?al.?(2015).?
94
Proceedings?of?the?2nd?Regional?Symposium?on?Landslides,?Belgrade,?2015 
 
 
The? result? of? dasymetric?modeling? is? presented? as?
thematic?map? in? Figure? 1? (right).? The? dasymetric?map?
indicates? a? more? realistic? presentation? of? a? spatial?
population? distribution? in? comparison? to? a? classical?
choropleth?map? that? reveals? official? publically? available?
census?data.?
The? final? results? of? the? dasymetric? database? of?
Serbia? are? portrayed? as? a? thematic? map? that? can? be?
communicated? and? shared? easily? through? the?
cartographic?web?map?based? service.?The?web?map?was?
achieved? using? recently? developed? packages? in? the? R?
language? environment? including? the? newly? developed?
package?plotGoogleMaps?(Kilibarda?&?Bajat,?2012),?which?
is? based? on? Asynchronous? JavaScript? and? XML?
technology? (AJAX)? and? Google? Maps? Application?
Programming? Interface? (API)? service? that? produces?
HTML? file?map?mashups.? The?web?map? is? available? at?
URL:?http://osgl.grf.bg.ac.rs/PopDensSerbia2006.html.??
Moreover,? the?data?of? the?dasymetric?database? are?
also? available? to? download? for? each? municipality? in?
GeoTiff?format?(by?clicking?on?municipality?polygon).?
?
?
Figure?2?Hazard?prone?delineated?areas?over?the?choroplet?(left)?and?dasymetric?(right)?population?density?maps?of?Belgrade?city?area.?
?
?
Data?processing?and?results?
The? land?use? suitability? (LUS)? data? layer? (Djuri?? et? al.?
2013)? is? readily? usable? in? the? GIS? environment.? The?
Master?Plan?of?the?City?of?Belgrade?was?used?to?delineate?
areas? that? are? susceptible? to? landslide? and? ground?
subsidence?hazard.?The?other?class?of?input?data?concerns?
spatial?population?distribution.??
The? hazard?prone? areas? were? delineated? by?
overlaying? the? official? data? of? population? distribution?
aggregated?on?municipality?level?with?LUS?layer?polygons?
that? refer? to?unsuitable?and?very?unsuitable? land?classes?
(Fig?2?left).?The?total?count?of?vulnerable?population?was?
calculated? by? multiplying? the? areas? of? hazard? prone?
polygon?areas?with?the?average?population?density?related?
to? particular? municipality.? The? total? number? of?
vulnerable?population?obtained? in?such?way? is?48,418?for?
the? entire? case? study? area.? On? the? other? hand,? by?
applying? the? same?procedure?with? the?dasymetric? raster?
data,?the?total?number?of?vulnerable?inhabitants?is?23,119.?
The?difference?between?those?two?estimated?amounts?is?a?
consequence? of? the? fact? that?most? of? the? hazard? prone?
areas?actually?cover?uninhabited?space.??
One? can? get? the? opposite? results? if?we? focus? on? a?
particular? hazard?prone? polygon? covering? a? populated?
area.? For? example,? the? polygons? depicted? in? Figure? 3?
indicate? 2527? people? in? accordance? to? the? daymetric?
database? (Fig?3?right)?are?at?risk?whereas?official?data?of?
95
B.?Bajat,?N.?Kruni?,?M.?Kilibarda,?A.?Sekuli??–?Assessment?of?population?vulnerability?in?risk?analysis?
 
population? distribution? indicates? 578? people? are? at? risk?
(Fig?3?left).?
?
??
Figure? 3? Hazard? prone? delineated? polygons? over?
official? data? of? population? distribution? (left)? and?
dasymetric?database?(right)?of?Belgrade?city?area.?
?
Conclusion?
Official?census?data?that? is?usually?aggregated?on?census?
tracts?or?even?on? the?municipality? level?are?not? suitable?
for? population? vulnerability? assessment? with? regard? to?
the?biased?estimate?of?people?under?risk.?Undercounting?
or? overcounting? of? an? impacted? population? could? have?
serious?implications?for?risk?management?and?mitigation.?
The?dasymetric?mapping?method?could?solve?this?
problem?by?dividing?the?modelled?space?into?zones?with?a?
higher? degree? of? homogeneity;? thereby? reflecting?more?
truthfully? the?variations? in?a? statistical?population? layer,?
with? support? of? additional? variables? and? their?
correlations.? The? production? of? population? surface?
models? suitable? for? risk? analysis? applications? can? be?
achieved? by? coupling? this? methodology? with? the? GIS?
environment?and?free?open?access?database?of?soil?sealing?
(soil?imperviousness)..?
The?obtained?database? can?be? an? instrument? to?
assess? cost?benefit? ratios? when? local? and? government?
authorities? analyze? the? effect? of? certain? mitigation?
measures.? Moreover,? the? database? could? serve? as? an?
important? tool? that? can?be? implemented? in? the?disaster?
awareness? phase? of? disaster? risk? management? at? the?
municipal?level.?
?
?
Acknowledgments??
This?work?was? supported?by? the?Ministry? of?Education,?
Science?and?Technological?Development?of? the?Republic?
of?Serbia?(Contracts?No.?III?47014?and?TR36035).?
?
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Assessment of population vulnerability in risk analysis using dasymetric database of Serbia

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