Geoinformation from the Past: Computational Retrieval and Retrospective Monitoring of Historical Land Use

211 Pages·2018·5.822 MB·English

by  Hendrik Herold (auth.)

Hendrik Herold
Geoinformation
from the Past
Computational Retrieval
and Retrospective Monitoring
of Historical Land Use
Geoinformation from the Past
Hendrik Herold
Geoinformation
from the Past
Computational Retrieval
and Retrospective Monitoring
of Historical Land Use
Hendrik Herold
Dresden, Germany
Dissertation Dresden University of Technology, Germany, 2015
ISBN 978-3-658-20569-0 ISBN 978-3-658-20570-6 (eBook)
https://doi.org/10.1007/978-3-658-20570-6
Library of Congress Control Number: 2017963886
Springer Spektrum
© Springer Fachmedien Wiesbaden GmbH 2018
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part
of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,
recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission
or information storage and retrieval, electronic adaptation, computer software, or by similar or
dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this
publication does not imply, even in the absence of a specific statement, that such names are exempt
from the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this
book are believed to be true and accurate at the date of publication. Neither the publisher nor the
authors or the editors give a warranty, express or implied, with respect to the material contained
herein or for any errors or omissions that may have been made. The publisher remains neutral with
regard to jurisdictional claims in published maps and institutional affiliations.
Printed on acid-free paper
This Springer Spektrum imprint is published by Springer Nature
The registered company is Springer Fachmedien Wiesbaden GmbH
The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany
Preface
Cartographicdocumentsareconsideredtobeuniquestoragesforgeospatial
information;storagesbasicallyforcenturiessincePtolemy’sGeographikeHy-
phegesis,ifnotearlier. Thischaracteristicmakeshistoricalmapsexceedingly
valuableresourcesnotonlyforgeoscientific,geographic,andlandscapere-
search,butalsothedigitalhumanities. Inparticular,archivalmapscangive
spatiallyexplicitevidenceofthedynamiclandchangethathastakenplace
duringthelasttwocenturies,acrucialperiodproposedastheAnthropocene.
However,thisgeohistoricalinformationisconcealedinthedocumentsand
usuallyonlyvisuallyaccessible. Thisbooksummarizesmorethantenyears
ofresearchonthecomputationalacquisitionofretrospectivegeoinformation
fromtopographicmapsandisbasedontheauthor’sdoctoraldissertation.
Althoughitisaworkofanindividual, suchanendeavorisalwaysaccom-
paniedandsupportedbynumerouspeople. Iwanttothankmyacademic
advisorsProf. Dr. ElmarCsaplovicsfromDresdenUniversityofTechnology
andProf. Dr. NguyenXuanThinhfromUniversityofTechnologyDortmund
forreviewingthisworkandtheirvaluablecomments. IamespeciallyinDr.
Gotthard Meinel’s debt, my mentor and head of the land use monitoring
researchgroupatLeibnizInstituteofEcologicalUrbanandRegionalDeve-
lopmentforinitiatingthisresearch,forsupportingmeduringthepastyears,
forthespaceforfreethinkingandeventuallyforhispatiencewhilefinishing
thiswork. IthankProf. Dr. Dr. BernhardMüllerastheheadoftheLeibniz
InstituteofEcologicalUrbanandRegionalDevelopmentfortheinstitutional
supportofmyresearch,conferencestays,andtrainings. Furthermore,Iowe
thankstoallmyinstitute’scolleagues. Althoughitisimpossibletoaddress
them all here, I want to name a few: Dr. Marco Neubert, whose work on
imagesegmentationinitiatednotonlymyfirstthesis,butalsoledtovarious
publicationsontheevaluationofimagesegmentationalgorithms. Someof
theshortcomingsidentifiedinthatearlierworkinspiredpartsofthisresearch.
Thankstoalltheinstitute’sfellowdoctoralstudents,whilespecialthanksgo
tomyofficemateandPhDfellowDr.RobertHecht. Ithinkwehavelearned
a lot during these years of highly intensive work, about both science and
life. FurtherIthankDr. MartinBehnischforhisadvice,particularlywhile
finishingthiswork. SabineWitschasandUlrichSchumacherforsharingtheir
knowledgeabouthistoricalandinternationalmaps. Forprovidingexcellent
VI Preface
technicalsupportregardingallhard-andsoftwareissuesIthankJörgGössel
andCarstenHantzsch. AnjaHellerandAlbrechtRostowskiforthesupport
aslibrarians,SieglindeSauerfortheorganizationalsupport. Dr. GerdLintz
for his advice during my time as the representative as well as member of
thedoctoralcommitteeboard. IalsothankmyDiploma,Master’sandBach-
elor’sstudents,amongstthemUlrikeSchinke,BenjaminRichterandPatric
Röhm, for their support regarding laborious data collection, preparation
and processing. I thank Dr. Christine Wessollek, Dr. Rico Vogel, and Dr.
PierreKarraschfromDresdenUniversityofTechnologyfortheircomments
on parts of the work. Furthermore, I want to thank some people from all
around the world, who have contributed with their advice, motivation or
inspiration: Dr. HermannKuxfromInstitutoNacionaldePesquisasEspaciais
IowethanksforperfectlyorganizingmyresearchvisitatBrazil’sINPEand
theinspiringdiscussions. Dr. PrashantReddyMarpufromMasdarUniversity
for the discussions on image segmentation algorithms that inspired some
ofthemethodologicalapproaches. Prof. Dr. StefanLeykfromUniversityof
Colorado for sharing his expertise in the field of automated map analysis,
andtogetherwithProf. Dr. Yao-YiChiangfromUniversityofSouthernCali-
forniaforinspiringdiscussionsontheperspectivesandstateoftheartinthe
researchfield. Dr. PetrPˇridalfromOldmapsonline.organdDr. LynnUsery
fromU.S.GeologicalSurveyforencouragingtalksonthefuturedigitalmap
repositories. Dr. ManonKohlerfromtheNationalUniversityofSingaporeI
thankforhervaluablehintsandthelanguagesupport. IthankAnitaWilke
fromthepublisherSpringerNatureforthehelpfulcommentsonthemanu-
scriptaswellasthesupportconcerningthefinalbooklayout. Lastnotleast,
Ideeplyexpressmygratitudetoallofmyfamilyfortheirlovingsupportand
understandingforallthetimeIdedicatedtothisresearchduringthepast
years. Iamespeciallyinmyparents’andgrandparents’debtfortheirefforts
inteachingmebothholisticandreductionisticviews,intrinsiccuriosity,but
also persistence and commitment, needed to cope with the challenges of
suchascientificendeavor.
Abstract
Land use changes have become a major contributor to the anthropogenic
globalchange. Theongoingdispersionandconcentrationofthehumanspe-
cies,beingattheirordersunprecedentedsinceitsappearance,havealtered
Earth’ssurfaceandatmosphere. Theeffectsaresosalientandirreversible
thatanewgeologicalepoch,followingtheinterglacialHolocene,hasbeen
announced: the“Anthropocene”. Whileitsonsetisbysomescholarsdated
back to the Neolithic revolution, it is commonly referred to the late 18th
century. Therapideconomicanddemographicgrowthsincetheindustrial
revolutionanditsimplicationsgaverisetoanincreasingawarenessofthe
pervasiveanthropogeniclandchangeandledtoanurgentneedforsustain-
ablestrategiesforlanduseandlandmanagement. Bypreservinglandscape
andsettlementpatternsatdiscretepointsintime,archivalgeospatialdata
sourcessuchasremotesensingimageryandhistoricalgeotopographicmaps,
inparticular,couldgiveevidenceofthedynamiclandusechangeduringthis
crucialperiod.
Inthiscontext,thisbooksetouttoexplorethepotentialsofretrospective
geoinformationformonitoring,communicating,modelingandeventually
understandingthecomplexandgraduallyevolvingprocessesoflandcover
andlandusechange. Currently, largeamountsofgeospatialdatasources
suchasarchivalmapsarebeingworldwidemadeonlineaccessiblebylibrar-
iesandnationalmappingagencies. Despitetheirabundanceandrelevance,
theusageofhistoricallanduseandlandcoverinformationinresearchisstill
oftenhinderedbythelaboriousvisualinterpretation,limitingthetemporal
andspatialcoverageofstudies. Thus,thecoreofthethesisisdedicatedto
thecomputationalacquisitionofgeoinformationfromarchivalmapsources
bymeansofdigitalimageanalysis. Basedonacomprehensivereviewofliter-
ature,availabledatasourcesandproposedalgorithms,twomajorchallenges
for long-term retrospective information acquisition and change detection
were identified: first, the diversity of geographical entity representations
overspaceandtime,andsecond,theuncertaintyinherenttoboththedata
sourceitselfanditsutilizationforlandchangedetection.
To address the former challenge, image segmentation is considered a
global non-linear optimization problem. The segmentation methods and
theirparametersareadaptivelyadjustedusingametaheuristic,evolutionary
VIII Abstract
approach. Forpreservingadaptabilityinhighlevelimageanalysis,ahybrid
model-anddata-drivenstrategy,combiningaknowledge-basedandaneural
netclassifier,isrecommended. Toaddressthesecondchallenge,aprobab-
ilisticobject-andfield-basedchangedetectionapproachformodelingthe
positional,thematic,andtemporaluncertaintyadherenttobothdataand
processing,isdeveloped. Experimentalresultsindicatethesuitabilityofthe
methodologyinsupportoflandchangemonitoring. Inconclusion,potentials
ofapplicationanddirectionsforfurtherresearcharegiven.
Keywords: LandChangeScience,LandUse,Long-TermMonitoring,Anthro-
pocene,HistoricalMaps,GIScience,AdaptiveImageAnalysis,Evolutionary
Algorithms,NeuralNets,UncertaintyModeling.
Résumé
Les changements d’occupation des sols imputables à l’homme et ses acti-
vitéssontdevenusuncontributeurmajeurdeschangementsglobauxactuels.
Ladispersiondel’espècehumainesurTerreainsiquesaconcentrationen
certainslieuxsansprécédentdepuisl’apparitiond’HomoSapiens,ontaltéré
la surface terrestre et l’atmosphère. Les effets sont d’une telle magnitude
etirréversiblesqu’unenouvelleépoquegéologique,suivantl’époqueinter-
glaciaireHolocène,aétépromulguée: l’Anthropocène. Alorsquecertains
chercheursconsidèrentlarévolutionnéolithiquecommedatededébutde
l’Anthropocène,ilestpluscommunémentadmisquecelle-cidébuteraitsoit
àlafindu18esièclesoitenmilieudusiècledernieraucommencementde
la dite « Grande accélération » période. La croissance démographique et
économiquerapidedepuisledébutdelarévolutionindustrielleainsiqueson
implicationdansleschangementsactuelsaentrainéuneprisedeconscience
croissantedel’intensitédeschangementsd’occupationdessolsinhérentsà
l’hommeainsiquedel’urgencedestratégiesdegestiondurabledesterres.
Enconservantlesinformationsrelativesauxpaysagesetauxpeuplements
endespointsdiscretsdutemps,lessourcesarchivéesdesdonnéesgéospa-
tialiséescommelesimagessatellitesetlescartestopographiqueshistoriques
peuvent fournir des indices précieux quant à la dynamique paysagère de
cettepériodecruciale.
Danscecontexte,leprésentlivreentendexplorerlepotentieldesinforma-
tionsgéographiquesrétrospectivespoursuivre,communiquer,modéliser,et
éventuellement comprendre les processus des changements d’occupation
et d’utilisation des sols. Actuellement, d’importante quantité de données
géospatialestelsquelescarte-archivessontmisesàdispositionenligneau
traversdesbibliothèquesetinstitutscartographiquesnationaux. Malgréleur
abondanceetleurpertinence,l’utilisationenrecherchedecesinformations
historiquesestsouvententravéeparleurinterprétationvisuellelaborieuse,
limitant ainsi la couverture spatio-temporelle de telles études. Aussi, le
cœurdecettethèseestdédiéàl’acquisitionautomatiséedesinformations
géographiquescontenuesdanslescarte-archivesaumoyend’analysedigitale
d’images. Baséesurunerevuedelittératureexhaustiveainsiquesurlesbases
de données et algorithmes existants, deux défis majeurs ont été identifiés
àl’acquisitionrétrospectived’informationsgéographiquesetàladétection
X Résumé
deschangementspaysagers: toutd’abordladiversitédesreprésentations
dansletempsetl’espacedesentitésgéographiques,etensuite,l’incertitude
inhérenteauxsourcesdedonnéesetàleurutilisationpourladétectiondes
changementsd’occupationdusol.
Afin de relever le premier défi, la segmentation d’image est considérée
comme un problème d’optimisation globale non linéaire. Les méthodes
de segmentation et ses paramètres sont ajustés de manière adaptative au
moyend’uneapprochemétaheuristique. Pourpréserverl’adaptabilitédans
l’analysed’imagehaut-niveau,unmodèlehybrideetdesstratégiesorientées
donnéescombinantunclassificateuràlafoisexpertetàlafoisneuronale
sontrecommandés. Afindereleverleseconddéfi,uneapprocheprobabiliste
baséeobjetetterraindedétectiondechangementspourlamodélisationde
l’incertitudepositionnelle,thématiqueettemporelleestdéveloppée. Lesré-
sultatsexpérimentauxdecetteétudeconfirmentlapertinencedelaméthode
danslesuivideschangementspaysagers. Enconclusion,despotentialités
d’applicationdelaméthodeetfuturschampsd’investigationsontdonnées.
Mot-clés: Dynamiquepaysagère,Occupationdusol,Observationdelongue
durée,Anthropocène,Carteshistoriques,Systèmed’InformationGéograph-
ique, Traitements et analyses adaptatives d’image, Algorithmes évolution-
nistes,Réseauxdeneuronesartificiels,Modélisationd’incertitude.