Remote Sensing of Vegetation: Along a Latitudinal Gradient in Chile

123 Pages·2019·8.23 MB·English

by  Christian Julian Bödinger

Christian Julian Bödinger
Remote Sensing
of Vegetation
Along a Latitudinal Gradient in Chile
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Christian Julian Bödinger
Remote Sensing
of Vegetation
Along a Latitudinal Gradient in Chile
W ith a Foreword by Prof. Dr. rer. nat. Volker Hochschild
Christian Julian Bödinger
Faculty of Science – Geography
Eberhard Karls University of Tübingen
Tübingen, Germany
Additional material to this book can be downloaded from http://extras.springer.com.
ISSN 2625-3577 ISSN 2625-3615 (electronic)
BestMasters
ISBN 978-3-658-25119-2 ISBN 978-3-658-25120-8 (eBook)
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Foreword
This master thesis written by Christian Bödinger is an excellent example of
the enormous potential multi-sensoral remote sensing has for the derivation
of biophysical vegetation parameters. It shows that satellite science can help
us a lot in understanding changes in the environment as a consequence of
climatic changes. This work, which was done in preparation of the DFG
funded priority program “EarthShape” to evaluate the impact of vegetation
on surface formation, received top grades from both reviewers with its scien-
tific approach being close to that of a doctoral thesis.
The thesis describes a remote-sensing based vegetation classification in four
different eco zones of Chile, while also investigating the vegetation devel-
opment with high-resolution satellite time-series during El-Niño years and
drought periods. This is done with approaches from the strongly emerging
field of machine learning and a critical reflection on the own results, which I
consider an essential foundation of good scientific work.
In the meantime, Christian Bödinger has left the Geoinformatics work group
to join the remote sensing company EOMAP in Seefeld. I am sure he will
stay open to research questions of modern science and make his way in earth
observation. I wish him success in doing so and to those interested in the
topic, a pleasant read.
Prof. Dr. rer. nat. Volker Hochschild
(Chair of Geoinformatics,
Geographical Institute,
University of Tübingen)
Acknowledgements
The preparation of this work would not have been possible without the dedi-
cated support of those to whom I would like to express my heartfelt thanks.
My first thanks goes to Prof. Volker Hochschild and Prof. Michael Märker
for supervising this work. I would also like to express my special thanks to
Prof. Hochschild for giving this topic to me and for his intensive and contin-
uous guidance throughout all work phases.
My sincere thanks also goes to the coordination of the EarthShape project
especially to Prof. Todd Ehlers and Dr. Kirstin Übernickel, who did not just
contribute significantly to the success of this work through their pertinent
advice, but also enabled me to participate at excellent and informative con-
ferences. Not forgetting all other project members for interesting and en-
lightening discussions, especially Juliana Klein and Liesbeth van den Brink
for the geotagged onsite pictures and all voluntary reviewers of this work.
Thanks also goes to the DLR for granting me access to the TanDEM-X
DEMs without cost and the people from Springer for their support.
Finally, I would like to express a deep sense of gratitude to my parents, who
have always stood by me like a pillar in times of need and to whom I owe my
life for their constant encouragement, moral support and benevolence.
Christian Bödinger
Introduction of the Work Group
The geoinformatics working group at the geographical institute of the Uni-
versity of Tübingen with a 14-year history has its research priorities in the
field of multi-sensoral remote sensing of hydrological-glaciological process-
es in the high mountainous areas and the recognition of urban structure types
in high dynamical metropolitan areas. Recently, spectacular results were
achieved during the monitoring of environmental impacts of refugee camps
and gravitational mass movement events in subtropical highlands. A regional
focus is laid on countries of south-east Asia and Africa. Now, the interna-
tional working group has more than 10 employees.
Besides the remote sensing focus, the working group applies innovative
methods of analysis (machine learning, etc.) in the field of Geographical
Information Systems (i.a. Web-GIS-Applications) and uses comprehensive
geo-relational data bases as well as various numerical modelling approaches
in hydrology and geomorphology. Worth emphasizing are also the more than
10-years of cooperation with the University´s archeologists for landscape
reconstruction and the role of culture in early human expansions originating
from Africa.
Methods of geoinformatics are practiced during the bachelor’s degree course
and intensified in the popular master course “Umweltgeographie”. For four
years the chair also engages in the Tübingen center for scientific advanced
training with the Geodata Manager qualification, which is also certified by
the employment agency.
The working group has comprehensive soft- and hardware suitable for GIS-
analyses and digital image processing as well as various other equipment
(field spectrometer, laser particle counter, differential GPS, TDR probes,
hemispherical camera, UAVs, etc.) to successfully validate remote sensing
data in the field. Hence, the work group is a popular international coopera-
tion partner for geoscientific projects of all kinds.
Prof. Dr. rer. nat. Volker Hochschild
Table of Contents
Foreword ..................................................................................................V
Acknowledgements ............................................................................... VII
Introduction of the Work Group ............................................................ IX
List of Figures ......................................................................................XIII
List of Tables ..................................................................................... XVII
Abbreviations ...................................................................................... XIX
Abstract ............................................................................................... XXI
Zusammenfassung ............................................................................. XXIII
1 Introduction ............................................................................................ 1
2 State of Research .................................................................................... 3
2.1 The EarthShape Program............................................................... 3
2.2 Previous Work & Research Gaps .................................................. 4
2.3 Study Objectives ........................................................................... 5
3 Study Areas ............................................................................................. 9
3.1 Pan De Azúcar ............................................................................. 11
3.2 Santa Gracia ................................................................................ 12
3.3 La Campana................................................................................. 14
3.4 Nahuelbuta .................................................................................. 16
4 Data & Methods ................................................................................... 19
4.1 Data ............................................................................................. 19
4.1.1 Sentinel Optical and Radar Data .................................... 19
4.1.2 TanDEM-X DEM ........................................................... 21
4.1.3 Training & Validation Data ............................................ 22
4.1.4 Landsat Surface Reflectance .......................................... 24
XII Table of Contents
4.2 Methods ....................................................................................... 25
4.2.1 Sentinel Preprocessing .................................................... 26
4.2.2 Derivation of Terrain Variables ...................................... 27
4.2.3 GLCM ............................................................................ 28
4.2.4 Spectral Vegetation Indices ............................................ 30
4.2.5 Land Cover Classes ........................................................ 32
4.2.6 Machine Learning ........................................................... 34
4.2.7 Accuracy Assessment ..................................................... 36
4.2.8 Time series Analysis ....................................................... 38
5 Results ................................................................................................... 41
5.1 Comparison of Topographic Corrections .................................... 41
5.2 Class Separability ........................................................................ 44
5.3 Classification Accuracy ............................................................... 45
5.3.1 Impact of the Classifier................................................... 45
5.3.2 Impact of Topographic Correction and DEM ................. 47
5.4 Final LULC Maps ....................................................................... 51
5.5 Variable Importance .................................................................... 62
5.6 Time Series Analysis ................................................................... 66
5.6.1 Catchment-wide Analysis ............................................... 68
5.6.2 Height-specific Analysis................................................. 71
5.6.3 Class-wise Analysis ........................................................ 74
5.7 Summary & Interpretation of Results .......................................... 77
6 Discussion .............................................................................................. 83
6.1 Hypothesis 1 ................................................................................ 83
6.2 Hypothesis 2 ................................................................................ 88
6.3 Hypothesis 3 ................................................................................ 91
7 Conclusions & Outlook ........................................................................ 97
References.................................................................................................... 99