Pedogenic iron oxide determination of soil surfaces from laboratory spectroscopy and HyMap image data [Elektronische Ressource] : a case study in Cabo de Gata-Níjar Natural Park, SE Spain / eingereicht von Nicole Richter

Nicole Richter

Informations

• Publié par: humboldt-universitat_zu_berlin
• Publié le: 01 janvier 2010
• Nombre de lectures: 79
• Langue: English
• Poids de l'ouvrage: 7 Mo

Extrait

Humboldt Universität zu Berlin – Geographisches Institut
Dissertation
Pedogenic iron oxide determination of soil surfaces
from laboratory spectroscopy
and HyMap image data
A case study in Cabo de Gata-Níjar Natural Park, SE Spain

zur Erlangung des akademischen Grades
doctor rerum naturalium

eingereicht von
Nicole Richter

an der Mathematisch-Naturwissenschafltichen Fakultät II
der Humboldt-Universität zu Berlin
Dekan: Prof. Dr. Peter Frensch


Gutachter
Prof. Dr. Patrick Hostert
Prof. Dr. Hermann Kaufmann
Prof. Dr. Eyal Ben-Dor

eingereicht am 21. August 2009
Datum der Promotion: 20. Januar 2010

Acknowledgements

First of all I would like to thank Prof. Herrmann Kaufmann and Dr. Sabine Chabrillat for
the opportunity to work on this project and being my supervisors from the very beginning.
I am especially grateful to Sabine for keeping work not related to the project off my desk
and giving me the freedom to focus on the research. Her guidance in the field, intensive
discussions and valuable suggestions improved the quality of this thesis.
I am deeply thankful to Dr. Thomas Jarmer for his continuous interest in this work, for
sharing his knowledge and intensive discussions about soils, spectroscopy and statistics.
His approach to scientific working, encouragement and support have been of great value
for the successful completion of the thesis.
Prof. Cecilio Oyonarte from the University Almeria is appreciated for funding and
performing the soil samples chemical analysis within the Incamar Project, for technical
support of the field work, sharing his knowledge of the study site and enabling a five week
research stay in Almeria.
Acknowledgements are due to Prof. Patrick Hostert for being available as supervisor and
giving me the opportunity to submit the thesis at the Humboldt University. Through our
discussions and his initiative to meet Thomas the thesis was pushed to a stage where it
could be completed.
I wish to extend my warmest thanks to all my colleagues from the remote sensing section
of the GFZ Potsdam. Dr. Jan Anderssohn and Daniel Spengler are gratefully
acknowledged for being great officemates and friends, for all the fruitful discussions and
nice chats over a beer. Thanks for an unforgettable PhD time! Sylvia Magnussen is thanked
for her assistance with all types of technical problems - at any time, and Dr. Karl Segl for
discussions and his little software tools that were faster programmed than I could wish for.
i
My warmest thanks go to Andrea Neumann for her help with optical measurements,
discussions and invaluable field assistance. The field work would not have been
accomplished in time without her help. Thanks also for showing me around in Berlin, long
open talks and always being there in the phases of frustration. It will not be forgotten.
I am grateful to Dr. Martin Bachmann from the DLR for HyMap data processing and
µMESMA calculations, the EU Desurvey-IP Project under leadership of Prof. Juan
Puigdefabregas for generous funding of the project and Prof. Eyal Ben-Dor for being
available as referee for this thesis.
The support and encouragement of my family and friends were invaluable for completing
this thesis. I want to thank in particular Birgit, Christiane and Trond for continuous moral
support, understanding the problems of a PhD student and finding numerous arguments
against giving up;
Dorothea and Silke for the great time singing together and enjoying Italian food on
Monday night;
Arthur, Luise, Johannes, Tim, Milo, and Ruth, the newborn babies of family and friends,
for the wonderful hours together that cleared my mind;
My family and family Naumann for their love, trust and encouragement;
My parents for their love, care, support and for funding me all those years that I could
finish my education and realize my dreams.
For those of you whom I forgot to thank, my true apologies, please be assured that your
support is highly appreciated.
Finally, I am forever indebted to Marcel for his endless patience reading the manuscript
and transforming my abstract “pseudo-english” structures into better understandable
sentences and paragraphs. Without his love, encouragement, support and him just being
there, this thesis would still not be finished. I am sure he is just as happy that I finished the
project.
Viva la vida!
ii
Abstract

The knowledge of the soil condition and development is decisive when characterizing and
monitoring the change of ecosystems. The global presence of iron oxides and their highly
variable concentration and mineralogy reflecting different soil conditions make them a
suitable indicator. Optical remote sensing methods are employed to determine and map the
soil iron oxide concentrations on the example of the Cabo de Gata-Níjar Natural Park, a
semi-arid ecosystem in SE Spain. In an initial laboratory spectroscopy study, a
methodology is developed that links iron oxide content (Fe , citrate-dithionite extractable d
iron oxides) with iron spectral absorption bands. Texture-dependent Fe prediction models d
are developed for sand- and clay-silt-dominated samples. They yield highly accurate
estimations with less than 15 % prediction error. Similar accuracies are achieved from
texture-independent models.
Texture-independent models are applied to the HyMap image data because a pixel-wise
determination of the predominating soil texture is not possible. However, the spatial
distribution of Fe concentration in the study area is determined with comparable accuracy d
as in the laboratory. Laboratory analysis of vegetation vitality and density impact on the
soil reflectance spectra and Fe prediction accuracy has shown that reliable estimations are d
possible until about 20 % leaf cover. Accordingly, three Fe prediction accuracy levels are d
defined based on the joint detectability of vegetation and iron absorption features. The final
Fe prediction map is used to evaluate the current soil conditions and identify potentially d
eroded soils surfaces. The present method has due to low complexity a high potential for
the global monitoring of such sensitive areas from current and future spaceborne sensors.
iii
Zusammenfassung

Kenntnisse über den Zustand und die Entwicklung von Böden sind entscheidend für die
Charakterisierung von Ökosystemen und deren Veränderungen. Die weltweite Verbreitung
von Eisenoxiden und ihre von der Bodenentwicklung abhängige Konzentration und
mineralogische Zusammensetzung machen sie zu geeigneten Indikatoren. Methoden der
optische Fernerkundung wurden angewandt, um am Beispiel des Cabo de Gata-Níjar
Naturparks, einem semi-ariden Ökosystem in Südostspanien, die Konzentrationen von
Eisenoxiden im Boden zu bestimmen und zu kartieren. In der zuerst durchgeführten labor-
spektroskopischen Studie wurde eine Methode entwickelt, welche den Eisenoxidgehalt
(Fe , Citrat-Dithionit extrahierbares Eisenoxid) mit den Eisenabsorptionsbanden verknüpft. d
Korngrößenabhängige Fe -Vorhersagemodelle wurden sowohl für sand- als auch ton-d
schluff-haltige Proben erstellt. Beide liefern hochgenaue Schätzungen mit weniger als 15%
Vorhersagefehler. Ähnliche Werte wurden für korngrößenunabhängige Modelle erreicht.
Korngrößenunabhängige Modelle wurden zur Analyse der HyMap-Bilddaten verwendet,
da eine pixelbezogene Bestimmung der vorherrschenden Bodentextur nicht möglich war.
Die räumliche Verteilung der Fe Konzentration im Untersuchungsgebiet wurde mit einer d
den Laborergebnissen vergleichbaren Genauigkeit bestimmt. Laboruntersuchungen zum
Vegetationseinfluss in Bezug auf Vitalität und Bedeckungsgrad auf die Bodenreflektions-
spektren und die Fe Vorhersagegenauigkeit zeigten, dass zuverlässige Abschätzungen bis d
zu einer Vegetationsbedeckung von ca. 20 % möglich sind. Dementsprechend wurden drei
Vorhersagegenauigkeitsklassen definiert, basierend auf der gemeinsamen Detektierbarkeit
von Vegetation und Eisenabsorptionsbanden im Bildpixel. Die abgeleitete Fe Verteilungs-d
karte dient der Einschätzung des vorliegenden Bodenzustands und dem Ausweisen von
erodierten Oberflächen. Die entwickelte Methode hat aufgrund ihrer Einfachheit ein großes
Potential für ein globales Monitoring von sensitiven Gebieten unter der Verwendung von
gegenwärtig verfügbaren als auch zukünftigen satellitengestützten Sensoren.
v
Contents

Acknowledgements i
Abstract iii
Zusammenfassung v
Contents vii
List of Figures xi
List of Tables xv
Abbreviations xvii

Chapter 1: Introduction and objectives 1

Chapter 2: Fundamentals of soil remote sensing 5
2.1 Interaction of radiation and soil surfaces 5
2.1.1 Mechanisms of absorption 6
2.1.2 Geometrical considerations 8
2.2 Reflectance properties of pedogenic iron oxides 9
2.3 Effects of other soil constituents on soil reflectance 11
2.3.1 Mineral composition 12
2.3.2 Soil organic matter 13
2.3.3 Soil moisture 14
2.4 Natural parameters affecting soil r