Investigating the potential of hyperspectral remote sensing data for the analysis of urban imperviousness [Elektronische Ressource] : a Berlin case study / eingereicht von Sebastian van der Linden

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Humboldt-Universität zu Berlin – Geographisches Institut Dissertation Investigating the potential of hyperspectral remote sensing data for the analysis of urban imperviousness – a Berlin case study zur Erlangung des akademischen Grades doctor rerum naturalium eingereicht von Sebastian van der Linden an der Mathematisch-Naturwissenschafltiche Fakultät II Dekan: Prof. Dr. Wolfgang Coy Gutachter: Prof. Dr. Patrick Hostert Prof. Dr. Hermann Kaufmann Dr. Christopher Small eingereicht: 1. November 2007 Datum der Promotion: 29. Januar 2008 Preface Being a young researcher in environmental sciences I had to face two inevitable truths: at first, my data – enormously large data sets of uncountable dimensions, acquired on an odd-shaped ellipsoid and somehow projected onto 2-D. At second, my colleagues – interesting people who are lots of fun to work with. Let me extend on the second a little. Patrick Hostert, head of the Geomatics Lab at Humboldt-Universität zu Berlin and advisor of this work, accompanied me during most of my remote sensing career. His feedback to my work was always valuable and honest, the outcome of discussions fruitful, and his advice was an important guideline. These were essential drivers for me to take up and – more important – to finish this dissertation. For the past two years I was fortunate to work in two research groups.

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• Astronomie

Informations

• Publié par: humboldt-universitat_zu_berlin
• Publié le: 01 janvier 2008
• Nombre de lectures: 55
• Langue: English
• Poids de l'ouvrage: 22 Mo

Extrait

lin  Geographisches Institut boldt-Universität zu BerHum

Dissertation

Investigating the potential of the mote sensing data forehyperspectral ranalysis of urban imperviousness  a Berlin case study

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eingereicht von

Sebastian van der Linden

an der Mathematisch-Naturwissenschafltiche Fakultät II

Dekan: Prof. Dr. Wolfgang Coy

Gutachter:

. Patrick Hostert Prof. Dr

Prof. Dr. Hermann Kaufmann

all . Christopher SmDr

eingereicht: 1. November 2007

otion: 29. Januar 2008 der PromDatum

efPrace

Being a young researcher in environmental sciences I had to face two inevitable truths: at
first, my data  enormously large data sets of uncountable dimensions, acquired on an odd-
shaped ellipsoid and somehow projected onto 2-D. At second, my colleagues  interesting
people who are lots of fun to work with. Let m extend on the second a little. e

Berlin and advisor boldt-Universität zu Humatics Lab atPatrick Hostert, head of the Geomof this work, accompanied me during most of my remote sensing career. His feedback to
of discussions fruitful, and his ee outcommy work was always valuable and honest, thadvice was an important guideline. These were essential drivers for me to take up and 
portant  to finish this dissertation. more im

atics At the Geomrk in two research groups. For the past two years I was fortunate to wo colleagues yng, and enjoyable to work with mLab in Berlin it was always interesting, excitiEllen Diermayer, Frank Ebermann, Oliver Grübner, Simone Hofmann, Katja Janson, Jan
Knorn, Tobias Kümmerle, Tobia Lakes, Magdalena Main, Ruth Sonnenschein and
Magdalena Zwijacz-Kozica, or with students such as Patrick Griffiths, Mirjam Langhans
and Thomas Scheuschner  the group has grown so big that it's a problem to write more
than this simple list of names. Nevertheless I want to point out Alexander Damm for the
many hours we jointly spent on processing HyMap data and on measuring in the field.
Many times it was his endurance and cooperative way that kept me going. Andreas Janz
introduced me to support vector machines and much of this work would not have been
fort. possible without his skills and great ef

At the same time, I'd like to thank Matthias Braun, Gunter Menz and Walter Kühbauch for
giving me the opportunity to join the team at the Center for Remote Sensing of Land
Surfaces in Bonn. I've spent so many good times in- and outside the office with Vanessa
travicute, Nora Schneevoigt, Peabi, RomHeinzel, Jonas Franke, Ellen Götz, Jan Jaco

i

Torsten Welle, my former office mates Roland Goetzke, Albert Moll and Christof
Weissteiner, and all others involved in remote sensing at Bonn University.

mote sensing and I n-year career in reny nice people I met during my teaThere are mparticularly want to thank

Björn Waske and Benjamin Kötz  once fellow undergrad students, now colleagues, co-
st important friends. I hope that one o and mauthors, proof-readers and two of my very bestday we will learn to talk a little less about remote sensing while having time off.

Achim Röder, Thomas Udelhoven, Joachim Hill and others in Trier for introducing me to
remote sensing during my times as an undergraduate and the good cooperation ever since.

Chris Small for giving me the opportunity to spend time at Columbia University and for
being external advisor of thisrk neighborhood is far oY work. Field work in the East New more exciting than on the streets of Berlin-Mitte.

Hermann Kaufmann for taking over as external advisor of this work and being member of
the scientific committee, Gunnar Nützmann for being head of the committee, and

field campaigns in the BUwe Rascher and Michael Eiden for the good ordeaux region. cooperation and hopefully for more joint

I am especially grateful to the German Federal Environmental Foundation (DBU) that
funded me during my time as a PhD student. It was always fun to spend time at seminars
with my fellow stipends and the people from the Osnabrück office. I would also like to
thank the German Academic Exchange Service (DAAD) for covering the cost of my stay at
Columbia University, New York.

nn, aand colleagues such as Henrike GrundmThis work was co-funded by Berlin friends Carl Jan Keuck, Jan Kürschner or Michael Schwarz who hosted me during my many visits.

lk about science all day and night long and , there are also people who do not taFortunatelyce neighbors in Bonn and Berlin of all the good friends and nifortI really appreciate the efke the past years so joyful. ato m

This leads me to the few even more important people. I will always be thankful to my dear
parents Karin and Wilhelm Schiefer, to my sister Susanne and brother Philipp with their
families, and  most of all  my wife Anna and son Johann for their trust, the everlasting
support, and simply being there. I am sure they are just as happy that I am done.

ii

Abstract

Urbanization is one of the most powerful and irreversible processes by which humans

modify the Earth's surface. Optical remote sensing is a main source of Earth observation

products which help to better This c process and its consequences. iunderstand this dynam

ation on to provide informl of airborne hyperspectral datawork investigates the potentia

urban imperviousness that is needed for an integrated analysis of the coupled natural and

human systems therein. For this purpose the complete processing workflow from

ps on land cover and aage to the generation of geocoded mmpreprocessing of the raw i

impervious surface coverage is performed using Hyperspectral Mapper data acquired over

Berlin, Germany. The traditional workflow for hyperspectral data is extended or modified

l e caused by directionaness gradients that aralization of brightat several points: a norm

reflectance properties of urban surfaces is included into radiometric preprocessing; support

vector machines are used to classify five spectrally complex land cover classes without

previous feature extraction or the definition of sub-classes. A detailed assessment of such

maps is performed based on various reference products. Results show that the accuracy of

derived maps depends on several steps within the processing workflow. For example, the

ectral data itself is accurate but geocoding achine classification of hyperspsupport vector m

without detailed terrain information introduces critical errors; impervious surface estimates

pervious surface below generally vering imcorrelate well with ground data but trees co

causes offsets; image segmentation does not enhance spectral classification accuracy of the

spatially heterogeneous area but offers an interesting way of data compression and more

time effective processing. Findings from this work help judging the reliability of data

nsion of urban remproducts and in doing so advance a possible extete sensing approaches o

to areas where only little additional data exists.

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iv

Zusammenfassung

ert die Menschheit die Erdoberfläche in Durch den Prozess der Urbanisierung verändgroßem Ausmaß und auf unwiederbringliche Weise. Die optische Fernerkundung ist eine
Art der Erdbeobachtung, die das Verständnis dieses dynamischen Prozesses und seiner
inwiefern untersucht, nde Arbeit Auswirkungen erweitern kann. Die vorliegehyperspektrale Daten Informationen über Versiegelung liefern können, die der integrierten
Analyse urbaner Mensch-Umwelt-Beziehungen dienen. Hierzu wird die Verarbeitungskette
von Vorverarbeitung der Rohdaten bis zur Erstellung referenzierter Karten zu
Landbedeckung und Versiegelung am Beispiel von Hyperspectral Mapper Daten von
Berlin ganzheitlich untersucht. Die traditionelle Verarbeitungskette wird mehrmals
erweitert bzw. abgewandelt. So wird die radiometrische Vorverarbeitung um die
Normalisierung von Helligkeitsgradienten erweitert, welche durch die direktionellen
ssifikation in fünf spektral Die KlaOberflächen entstehen.Reflexionseigenschaften urbaner komplexe Landnutzungsklassen wird mit Support Vector Maschinen ohne zusätzliche
Merkmalsextraktion oder Differenzierung von Subklassen durchgeführt. Eine detaillierte
Ergebnisvalidierung erfolgt mittels vielfältiger Referenzdaten. Es wird gezeigt, dass die
Kartengenauigkeit von allen Verarbeitungsschritten abhängt: Support Vector Maschinen
ngenauigkeit wird durch dieaten akkurat aber die Karteklassifizieren HyperspektraldGeoreferenzierung deutlich gemindert; die Versiegelungskartierung stellt die Situation am
e bedingt rsiegelter Flächen durch Bäum aber die Überdeckung ve,Boden gut darsystematische Fehlschätzungen; eine Bildsegmentierung führt zu keiner Verbesserung der
fektiveren Möglichkeit zur efetet jedoch eine sinnvolle gebnisse, biKlassifikationserProzessierung durch Datenkomprimierung. Auf diesem Weg ermöglicht die vorliegende
Arbeit Rückschlüsse zur Verlässlichkeit von Datenprodukten, die eine Ausweitung
e voranbringt. dokumentierte urbane RäumAnalysen in weniger gutfernerkundlicher

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Contents

eface Pr iii Abstractsammenfassung v uZContents vii List of List of FiguTablesre s
noductio I: IntrChapterThe first urban ce