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In den letzten Jahren wurden relativ komplexe Erosionsmodelle entwickelt, deren Teilprozesse immer mehr auf physikalisch begründeten Ansätzen beruhen. Damit verbunden ist eine höhere Anzahl aktueller Eingangsparameter, deren Bestimmung im Feld arbeits- und kostenaufwendig ist. Zudem werden die Parameter punktuell, also an bestimmten Stellen und nicht flächenhaft wie bei der Fernerkundung, erfasst. Im Rahmen dieser Arbeit wird gezeigt, wie Satellitendaten als relativ kostengünstige Ergänzung oder Alternative zur konventionellen Parametererhebung genutzt werden können. Dazu werden beispielhaft der Blattflächenindex (LAI) und der Bedeckungsgrad für das physikalisch begründete Erosionsmodell EROSION 3D abgeleitet. Im Mittelpunkt des Interesses steht dabei das Aufzeigen von existierenden Methoden, die die Basis für eine operationelle Bereitstellung solcher Größen nicht nur für Erosions- sondern allgemein für Prozessmodelle darstellen. Als Untersuchungsgebiet dient das primär landwirtschaftlich genutzte Einzugsgebiet des Mehltheuer Baches, das sich im Sächsischen Lößgefilde befindet und für das Simulationsrechnungen mit konventionell erhobenen Eingangsparametern für 29 Niederschlagsereignisse im Jahr 1999 vorliegen [MICHAEL et al. 2000]. Die Fernerkundungsdatengrundlage bilden Landsat-5-TM-Daten vom 13.03.1999, 30.04.1999 und 19.07.1999. Da die Vegetationsparameter für alle Niederschlagsereignisse vorliegen sollen, werden sie basierend auf der Entwicklung des LAI zeitlich interpoliert. Dazu erfolgt zunächst die Ableitung des LAI für alle vorhandenen Fruchtarten nach den semi-empirischen Modellen von CLEVERS [1986] und BARET & GUYOT [1991] mit aus der Literatur entnommenen Koeffizienten. Des Weiteren wird eine Methode untersucht, nach der die Koeffizienten für das Clevers-Modell aus den TM-Daten und einem vereinfachten Wachstumsmodell bestimmt werden. Der Bedeckungsgrad wird nach ROSS [1981] aus dem LAI ermittelt. Die zeitliche Interpolation des LAI wird durch die schlagbezogene Anpassung eines vereinfachten Wachstumsmodells umgesetzt, das dem hydrologischen Modell SWIM [KRYSANOVA et al. 1999] entstammt und in das durchschnittliche Tagestemperaturen eingehen. Mit den genannten Methoden bleiben abgestorbene Pflanzenteile unberücksichtigt. Im Vergleich zur konventionellen terrestrischen Parametererhebung ermöglichen sie eine differenziertere Abbildung räumlicher Variabilitäten und des zeitlichen Verlaufes der Vegetationsparameter. Die Simulationsrechnungen werden sowohl mit den direkten Bedeckungsgraden aus den TM-Daten (pixelbezogen) als auch mit den zeitlich interpolierten Bedeckungsgraden für alle Ereignisse (schlagbezogen) durchgeführt. Bei beiden Vorgehensweisen wird im Vergleich zur bisherigen Abschätzung eine Verbesserung der räumlichen Verteilung der Parameter und somit eine räumliche Umverteilung von Erosions- und Depositionsflächen erreicht. Für die im Untersuchungsgebiet vorliegende räumliche Heterogenität (z. B. Schlaggröße) bieten Landsat-TM-Daten eine ausreichend genaue räumliche Auflösung. Damit wird nachgewiesen, dass die satellitengestützte Fernerkundung im Rahmen dieser Untersuchungen sinnvoll einsetzbar ist. Für eine operationelle Bereitstellung der Parameter mit einem vertretbaren Aufwand ist es erforderlich, die Methoden weiter zu validieren und möglichst weitestgehend zu automatisieren.
Gangschwärme nehmen eine bedeutende Stellung im Verständnis zur kontinentalen Fragmentierung ein. Einerseits markieren sie das Paläo-Spannungsfeld und helfen bei der Rekonstruktion der strukturellen Entwicklung der gedehnten Lithosphäre, andererseits gibt ihre petrologische Beschaffenheit Aufschluß über die Entstehung des Magmas, Aufstieg und Platznahme und schließlich erlaubt ihre Altersbestimmung die Rekonstruktion einer chronologischen Reihenfolge magmatischer und struktureller Ereignisse. Das Arbeitsgebiet im namibianischen Henties Bay-Outjo Dike swarm (HOD) war zur Zeit der Unterkreide einem Rifting mit intensiver Platznahme von überwiegend mafischen Gängen unterworfen. Geochemische Signaturen weisen die Gänge als erodierte Förderkanäle der Etendeka Plateaubasalte aus. Durch den Einsatz von hochauflösenden Aeromagnetik- und Satellitendaten war es möglich, die Geometrie des Gangschwarmes erstmals detailliert synoptisch zu erfassen. Viele zu den Schichten des Grundgebirges foliationsparallel verlaufende magnetische Anomalien können unaufgeschlossenen kretazischen Intrusionen zugeordnet werden. Bei der nach Norden propagierenden Südatlantiköffnung spielte die unterschiedliche strukturelle Vorzeichnung durch die neoproterozoischen Faltengürtel sowie Lithologie und Spannungsfeld des Angola Kratons eine bedeutende Rolle. Im küstennahen zentralen Bereich war dank der Vorzeichnung des Nordost streichenden Damara-Faltengürtels ein Rifting in Nordwest-Südost-Richtung dominierend, bis das Angola Kraton ein weiteres Fortscheiten nach Nordosten hemmte und die Vorzeichnung des Nordwest streichenden Kaoko-Faltengürtels an der Westgrenze den weiteren Riftverlauf und die letztendlich erfolgreiche Öffnung des Südatlantiks bestimmte. Aus diesem Grund kann das Gebiet des HOD als ein failed rift betrachtet werden. Die Entwicklung des Spannungsfeldes im HOD kann folgendermaßen skizziert werden: 1. Platznahme von Gängen bei gleichzeitig hoher Dehnungsrate und hohem Magmenfluß. 2. Platznahme von Zentralvulkanen entlang reaktivierter paläozoischer Lineamente bei Abnahme der Dehnungsrate und fortbestehendem hohen Magmenfluß. 3. Abnahme/Versiegen des Magmenflusses und neotektonische Bewegungen führen zur Bildung von Halbgräben.
Gegenstand dieser Arbeit ist die Konzeption, Entwicklung und exemplarische Implementierung eines generischen Verfahrens zur Erfassung, Verarbeitung, Auswertung und kartographischen Visualisierung urbaner Strukturen im altweltlichen Trockengürtel mittels hochauflösender operationeller Fernerkundungsdaten. Das Verfahren wird am Beispiel der jemenitischen Hauptstadt Sanaa einer Vertreterin des Typus der Orientalischen Stadt angewandt und evaluiert. Das zu entwickelnde Verfahren soll auf Standardverfahren und Systemen der raumbezogenen Informationsverarbeitung basieren und in seinen wesentlichen Prozessschritten automatisiert werden können. Daten von hochauflösenden operationellen Fernerkundungssystemen (wie z.B. QuickBird, Ikonos u. a.) erlauben die Erkennung und Kartierung urbaner Objekte, wie Gebäude, Straßen und sogar Autos. Die mit ihnen erstellten Karten und den daraus gewonnenen Informationen können zur Erfassung von Urbanisierungsprozessen (Stadt- und Bevölkerungswachstum) herangezogen werden. Sie werden auch zur Generierung von 3D-Stadtmodellen genutzt. Diese dienen z.B. der Visualisierung für touristische Anwendungen, für die Stadtplanung, für Lärmanalysen oder für die Standortplanung von Mobilfunkantennen. Bei dem in dieser Arbeit erzeugten 3D-Visualisierung wurden jedoch keine Gebäudedetails erfasst. Entscheidend war vielmehr die Wiedergabe der Siedlungsstruktur, die im Vorhandensein und in der Anordnung der Gebäude liegt. In dieser Arbeit wurden Daten des Satellitensensors Quickbird von 2005 verwendet. Sie zeigen einen Ausschnitt der Stadt Sanaa in Jemen. Die Fernerkundungsdaten wurden durch andere Daten, u.a. auch Geländedaten, ergänzt und verifiziert. Das ausgearbeitete Verfahren besteht aus der Klassifikation der Satellitenbild-aufnahme, die u.a. pixelbezogen und für jede Klasse einzeln (pixelbezogene Klassifikation auf Klassenebene) durchgeführt wurde. Zusätzlich fand eine visuelle Interpretation der Satellitenbildaufnahme statt, bei der einzelne Flächen und die Straßen digitalisiert und die Objekte mit Symbolen gekennzeichnet wurden. Die aus beiden Verfahren erstellten Stadtkarten wurden zu einer fusioniert. Durch die Kombination der Ergebnisse werden die Vorteile beider Karten in einer vereint und ihre jeweiligen Schwächen beseitigt bzw. minimiert. Die digitale Erfassung der Konturlinien auf der Orthophotomap von Sanaa erlaubte die Erstellung eines Digitalen Geländemodells, das der dreidimensionalen Darstellung des Altstadtbereichs von Sanaa diente. Die 3D-Visualisierung wurde sowohl von den pixelbezogenen Klassifikationsergebnissen auf Klassenebene als auch von der digitalen Erfassung der Objekte erstellt. Die Ergebnisse beider Visualisierungen wurden im Anschluss in einer Stadtkarte vereint. Bei allen Klassifikationsverfahren wurden die asphaltierten Straßen, die Vegetation und einzeln stehende Gebäude sehr gut erfasst. Die Klassifikation der Altstadt gestaltete sich aufgrund der dort für die Klassifikation herrschenden ungünstigen Bedingungen am problematischsten. Die insgesamt besten Ergebnisse mit den höchsten Genauigkeitswerten wurden bei der pixelbezogenen Klassifikation auf Klassenebene erzielt. Dadurch, dass jede Klasse einzeln klassifiziert wurde, konnte die zu einer Klasse gehörende Fläche besser erfasst und nachbearbeitet werden. Die Datenmenge wurde reduziert, die Bearbeitungszeit somit kürzer und die Speicherkapazität geringer. Die Auswertung bzw. visuelle Validierung der pixel-bezogenen Klassifikationsergebnisse auf Klassenebene mit dem Originalsatelliten-bild gestaltete sich einfacher und erfolgte genauer als bei den anderen durch-geführten Klassifikationsverfahren. Außerdem war es durch die alleinige Erfassung der Klasse Gebäude möglich, eine 3D-Visualisierung zu erzeugen. Bei einem Vergleich der erstellten Stadtkarten ergibt sich, dass die durch die visuelle Interpretation erstellte Karte mehr Informationen enthält. Die von den pixelbezogenen Klassifikationsergebnissen auf Klassenebene erstellte Karte ist aber weniger arbeits- und zeitaufwendig zu erzeugen. Zudem arbeitet sie die Struktur einer orientalischen Stadt mit den wesentlichen Merkmalen besser heraus. Durch die auf Basis der 2D-Stadtkarten erstellte 3D-Visualisierung wird ein anderer räumlicher Eindruck vermittelt und bestimmte Elemente einer orientalischen Stadt deutlich gemacht. Dazu zählen die sich in der Altstadt befindenden Sackgassen und die ehemalige Stadtmauer. Auch die für Sanaa typischen Hochhäuser werden in der 3D-Visualisierung erkannt. Insgesamt wurde in der Arbeit ein generisches Verfahren entwickelt, dass mit geringen Modifikationen auch auf andere städtische Räume des Typus orientalische Stadt angewendet werden kann.
Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.% for the soil moisture (range of in situ values: 1-46vol.%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.
Current climate warming is affecting arctic regions at a faster rate than the rest of the world. This has profound effects on permafrost that underlies most of the arctic land area. Permafrost thawing can lead to the liberation of considerable amounts of greenhouse gases as well as to significant changes in the geomorphology, hydrology, and ecology of the corresponding landscapes, which may in turn act as a positive feedback to the climate system. Vast areas of the east Siberian lowlands, which are underlain by permafrost of the Yedoma-type Ice Complex, are particularly sensitive to climate warming because of the high ice content of these permafrost deposits. Thermokarst and thermal erosion are two major types of permafrost degradation in periglacial landscapes. The associated landforms are prominent indicators of climate-induced environmental variations on the regional scale. Thermokarst lakes and basins (alasses) as well as thermo-erosional valleys are widely distributed in the coastal lowlands adjacent to the Laptev Sea. This thesis investigates the spatial distribution and morphometric properties of these degradational features to reconstruct their evolutionary conditions during the Holocene and to deduce information on the potential impact of future permafrost degradation under the projected climate warming. The methodological approach is a combination of remote sensing, geoinformation, and field investigations, which integrates analyses on local to regional spatial scales. Thermokarst and thermal erosion have affected the study region to a great extent. In the Ice Complex area of the Lena River Delta, thermokarst basins cover a much larger area than do present thermokarst lakes on Yedoma uplands (20.0 and 2.2 %, respectively), which indicates that the conditions for large-area thermokarst development were more suitable in the past. This is supported by the reconstruction of the development of an individual alas in the Lena River Delta, which reveals a prolonged phase of high thermokarst activity since the Pleistocene/Holocene transition that created a large and deep basin. After the drainage of the primary thermokarst lake during the mid-Holocene, permafrost aggradation and degradation have occurred in parallel and in shorter alternating stages within the alas, resulting in a complex thermokarst landscape. Though more dynamic than during the first phase, late Holocene thermokarst activity in the alas was not capable of degrading large portions of Pleistocene Ice Complex deposits and substantially altering the Yedoma relief. Further thermokarst development in existing alasses is restricted to thin layers of Holocene ice-rich alas sediments, because the Ice Complex deposits underneath the large primary thermokarst lakes have thawed completely and the underlying deposits are ice-poor fluvial sands. Thermokarst processes on undisturbed Yedoma uplands have the highest impact on the alteration of Ice Complex deposits, but will be limited to smaller areal extents in the future because of the reduced availability of large undisturbed upland surfaces with poor drainage. On Kurungnakh Island in the central Lena River Delta, the area of Yedoma uplands available for future thermokarst development amounts to only 33.7 %. The increasing proximity of newly developing thermokarst lakes on Yedoma uplands to existing degradational features and other topographic lows decreases the possibility for thermokarst lakes to reach large sizes before drainage occurs. Drainage of thermokarst lakes due to thermal erosion is common in the study region, but thermo-erosional valleys also provide water to thermokarst lakes and alasses. Besides these direct hydrological interactions between thermokarst and thermal erosion on the local scale, an interdependence between both processes exists on the regional scale. A regional analysis of extensive networks of thermo-erosional valleys in three lowland regions of the Laptev Sea with a total study area of 5,800 km² found that these features are more common in areas with higher slopes and relief gradients, whereas thermokarst development is more pronounced in flat lowlands with lower relief gradients. The combined results of this thesis highlight the need for comprehensive analyses of both, thermokarst and thermal erosion, in order to assess past and future impacts and feedbacks of the degradation of ice-rich permafrost on hydrology and climate of a certain region.
Landslides are one of the biggest natural hazards in Georgia, a mountainous country in the Caucasus. So far, no systematic monitoring and analysis of the dynamics of landslides in Georgia has been made. Especially as landslides are triggered by extrinsic processes, the analysis of landslides together with precipitation and earthquakes is challenging. In this thesis I describe the advantages and limits of remote sensing to detect and better understand the nature of landslide in Georgia. The thesis is written in a cumulative form, composing a general introduction, three manuscripts and a summary and outlook chapter. In the present work, I measure the surface displacement due to active landslides with different interferometric synthetic aperture radar (InSAR) methods. The slow landslides (several cm per year) are well detectable with two-pass interferometry. In same time, the extremely slow landslides (several mm per year) could be detected only with time series InSAR techniques. I exemplify the success of InSAR techniques by showing hitherto unknown landslides, located in the central part of Georgia. Both, the landslide extent and displacement rate is quantified. Further, to determine a possible depth and position of potential sliding planes, inverse models were developed. Inverse modeling searches for parameters of source which can create observed displacement distribution. I also empirically estimate the volume of the investigated landslide using displacement distributions as derived from InSAR combined with morphology from an aerial photography. I adapted a volume formula for our case, and also combined available seismicity and precipitation data to analyze potential triggering factors. A governing question was: What causes landslide acceleration as observed in the InSAR data? The investigated area (central Georgia) is seismically highly active. As an additional product of the InSAR data analysis, a deformation area associated with the 7th September Mw=6.0 earthquake was found. Evidences of surface ruptures directly associated with the earthquake could not be found in the field, however, during and after the earthquake new landslides were observed. The thesis highlights that deformation from InSAR may help to map area prone landslides triggering by earthquake, potentially providing a technique that is of relevance for country wide landslide monitoring, especially as new satellite sensors will emerge in the coming years.
Within a research project about future sustainable water management options in the Elbe River basin, quasi-natural discharge scenarios had to be provided. The semi-distributed eco-hydrological model SWIM was utilised for this task. According to scenario simulations driven by the stochastical climate model STAR, the region would get distinctly drier. However, this thesis focuses on the challenge of meeting the requirement of high model fidelity even for smaller sub-basins. Usually, the quality of the simulations is lower at inner points than at the outlet. Four research paper chapters and the discussion chapter deal with the reasons for local model deviations and the problem of optimal spatial calibration. Besides other assessments, the Markov Chain Monte Carlo method is applied to show whether evapotranspiration or precipitation should be corrected to minimise runoff deviations, principal component analysis is used in an unusual way to evaluate local precipitation alterations by land cover changes, and remotely sensed surface temperatures allow for an independent view on the evapotranspiration landscape. The overall insight is that spatially explicit hydrological modelling of such a large river basin requires a lot of local knowledge. It probably needs more time to obtain such knowledge as is usually provided for hydrological modelling studies.
The Arctic tundra, covering approx. 5.5 % of the Earth’s land surface, is one of the last ecosystems remaining closest to its untouched condition. Remote sensing is able to provide information at regular time intervals and large spatial scales on the structure and function of Arctic ecosystems. But almost all natural surfaces reveal individual anisotropic reflectance behaviors, which can be described by the bidirectional reflectance distribution function (BRDF). This effect can cause significant changes in the measured surface reflectance depending on solar illumination and sensor viewing geometries. The aim of this thesis is the hyperspectral and spectro-directional reflectance characterization of important Arctic tundra vegetation communities at representative Siberian and Alaskan tundra sites as basis for the extraction of vegetation parameters, and the normalization of BRDF effects in off-nadir and multi-temporal remote sensing data. Moreover, in preparation for the upcoming German EnMAP (Environmental Mapping and Analysis Program) satellite mission, the understanding of BRDF effects in Arctic tundra is essential for the retrieval of high quality, consistent and therefore comparable datasets. The research in this doctoral thesis is based on field spectroscopic and field spectro-goniometric investigations of representative Siberian and Alaskan measurement grids. The first objective of this thesis was the development of a lightweight, transportable, and easily managed field spectro-goniometer system which nevertheless provides reliable spectro-directional data. I developed the Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS). The outcome of the field spectro-radiometrical measurements at the Low Arctic study sites along important environmental gradients (regional climate, soil pH, toposequence, and soil moisture) show that the different plant communities can be distinguished by their nadir-view reflectance spectra. The results especially reveal separation possibilities between the different tundra vegetation communities in the visible (VIS) blue and red wavelength regions. Additionally, the near-infrared (NIR) shoulder and NIR reflectance plateau, despite their relatively low values due to the low structure of tundra vegetation, are still valuable information sources and can separate communities according to their biomass and vegetation structure. In general, all different tundra plant communities show: (i) low maximum NIR reflectance; (ii) a weakly or nonexistent visible green reflectance peak in the VIS spectrum; (iii) a narrow “red-edge” region between the red and NIR wavelength regions; and (iv) no distinct NIR reflectance plateau. These common nadir-view reflectance characteristics are essential for the understanding of the variability of BRDF effects in Arctic tundra. None of the analyzed tundra communities showed an even closely isotropic reflectance behavior. In general, tundra vegetation communities: (i) usually show the highest BRDF effects in the solar principal plane; (ii) usually show the reflectance maximum in the backward viewing directions, and the reflectance minimum in the nadir to forward viewing directions; (iii) usually have a higher degree of reflectance anisotropy in the VIS wavelength region than in the NIR wavelength region; and (iv) show a more bowl-shaped reflectance distribution in longer wavelength bands (>700 nm). The results of the analysis of the influence of high sun zenith angles on the reflectance anisotropy show that with increasing sun zenith angles, the reflectance anisotropy changes to azimuthally symmetrical, bowl-shaped reflectance distributions with the lowest reflectance values in the nadir view position. The spectro-directional analyses also show that remote sensing products such as the NDVI or relative absorption depth products are strongly influenced by BRDF effects, and that the anisotropic characteristics of the remote sensing products can significantly differ from the observed BRDF effects in the original reflectance data. But the results further show that the NDVI can minimize view angle effects relative to the contrary spectro-directional effects in the red and NIR bands. For the researched tundra plant communities, the overall difference of the off-nadir NDVI values compared to the nadir value increases with increasing sensor viewing angles, but on average never exceeds 10 %. In conclusion, this study shows that changes in the illumination-target-viewing geometry directly lead to an altering of the reflectance spectra of Arctic tundra communities according to their object-specific BRDFs. Since the different tundra communities show only small, but nonetheless significant differences in the surface reflectance, it is important to include spectro-directional reflectance characteristics in the algorithm development for remote sensing products.
The continuously increasing demand for rare earth elements in technical components of modern technologies, brings the detection of new deposits closer into the focus of global exploration. One promising method to globally map important deposits might be remote sensing, since it has been used for a wide range of mineral mapping in the past. This doctoral thesis investigates the capacity of hyperspectral remote sensing for the detection of rare earth element deposits. The definition and the realization of a fundamental database on the spectral characteristics of rare earth oxides, rare earth metals and rare earth element bearing materials formed the basis of this thesis. To investigate these characteristics in the field, hyperspectral images of four outcrops in Fen Complex, Norway, were collected in the near-field. A new methodology (named REEMAP) was developed to delineate rare earth element enriched zones. The main steps of REEMAP are: 1) multitemporal weighted averaging of multiple images covering the sample area; 2) sharpening the rare earth related signals using a Gaussian high pass deconvolution technique that is calibrated on the standard deviation of a Gaussian-bell shaped curve that represents by the full width of half maxima of the target absorption band; 3) mathematical modeling of the target absorption band and highlighting of rare earth elements. REEMAP was further adapted to different hyperspectral sensors (EO-1 Hyperion and EnMAP) and a new test site (Lofdal, Namibia). Additionally, the hyperspectral signatures of associated minerals were investigated to serve as proxy for the host rocks. Finally, the capacity and limitations of spectroscopic rare earth element detection approaches in general and of the REEMAP approach specifically were investigated and discussed. One result of this doctoral thesis is that eight rare earth oxides show robust absorption bands and, therefore, can be used for hyperspectral detection methods. Additionally, the spectral signatures of iron oxides, iron-bearing sulfates, calcite and kaolinite can be used to detect metasomatic alteration zones and highlight the ore zone. One of the key results of this doctoral work is the developed REEMAP approach, which can be applied from near-field to space. The REEMAP approach enables rare earth element mapping especially for noisy images. Limiting factors are a low signal to noise ratio, a reduced spectral resolution, overlaying materials, atmospheric absorption residuals and non-optimal illumination conditions. Another key result of this doctoral thesis is the finding that the future hyperspectral EnMAP satellite (with its currently published specifications, June 2015) will be theoretically capable to detect absorption bands of erbium, dysprosium, holmium, neodymium and europium, thulium and samarium. This thesis presents a new methodology REEMAP that enables a spatially wide and rapid hyperspectral detection of rare earth elements in order to meet the demand for fast, extensive and efficient rare earth exploration (from near-field to space).
The global carbon cycle is closely linked to Earth’s climate. In the context of continuously unchecked anthropogenic CO₂ emissions, the importance of natural CO₂ bond and carbon storage is increasing. An important biogenic mechanism of natural atmospheric CO₂ drawdown is the photosynthetic carbon fixation in plants and the subsequent longterm deposition of plant detritus in sediments.
The main objective of this thesis is to identify factors that control mobilization and transport of plant organic matter (pOM) through rivers towards sedimentation basins. I investigated this aspect in the eastern Nepalese Arun Valley. The trans-Himalayan Arun River is characterized by a strong elevation gradient (205 − 8848 m asl) that is accompanied by strong changes in ecology and climate ranging from wet tropical conditions in the Himalayan forelad to high alpine tundra on the Tibetan Plateau. Therefore, the Arun is an excellent natural laboratory, allowing the investigation of the effect of vegetation cover, climate, and topography on plant organic matter mobilization and export in tributaries along the gradient.
Based on hydrogen isotope measurements of plant waxes sampled along the Arun River and its tributaries, I first developed a model that allows for an indirect quantification of pOM contributed to the mainsetm by the Arun’s tributaries. In order to determine the role of climatic and topographic parameters of sampled tributary catchments, I looked for significant statistical relations between the amount of tributary pOM export and tributary characteristics (e.g. catchment size, plant cover, annual precipitation or runoff, topographic measures). On one hand, I demonstrated that pOMsourced from the Arun is not uniformly derived from its entire catchment area. On the other, I showed that dense vegetation is a necessary, but not sufficient, criterion for high tributary pOM export. Instead, I identified erosion and rainfall and runoff as key factors controlling pOM sourcing in the Arun Valley. This finding is supported by terrestrial cosmogenic nuclide concentrations measured on river sands along the Arun and its tributaries in order to quantify catchment wide denudation rates. Highest denudation rates corresponded well with maximum pOM mobilization and export also suggesting the link between erosion and pOM sourcing.
The second part of this thesis focusses on the applicability of stable isotope records such as plant wax n-alkanes in sediment archives as qualitative and quantitative proxy for the variability of past Indian Summer Monsoon (ISM) strength. First, I determined how ISM strength affects the hydrogen and oxygen stable isotopic composition (reported as δD and δ18O values vs. Vienna Standard Mean Ocean Water) of precipitation in the Arun Valley and if this amount effect (Dansgaard, 1964) is strong enough to be recorded in potential paleo-ISM isotope proxies. Second, I investigated if potential isotope records across the Arun catchment reflect ISM strength dependent precipitation δD values only, or if the ISM isotope signal is superimposed by winter precipitation or glacial melt. Furthermore, I tested if δD values of plant waxes in fluvial deposits reflect δD values of environmental waters in the respective catchments.
I showed that surface water δD values in the Arun Valley and precipitation δD from south of the Himalaya both changed similarly during two consecutive years (2011 & 2012) with distinct ISM rainfall amounts (~20% less in 2012). In order to evaluate the effect of other water sources (Winter-Westerly precipitation, glacial melt) and evapotranspiration in the Arun Valley, I analysed satellite remote sensing data of rainfall distribution (TRMM 3B42V7), snow cover (MODIS MOD10C1), glacial coverage (GLIMSdatabase, Global Land Ice Measurements from Space), and evapotranspiration (MODIS MOD16A2). In addition to the predominant ISM in the entire catchment I found through stable isotope analysis of surface waters indications for a considerable amount of glacial melt derived from high altitude tributaries and the Tibetan Plateau. Remotely sensed snow cover data revealed that the upper portion of the Arun also receives considerable winter precipitation, but the effect of snow melt on the Arun Valley hydrology could not be evaluated as it takes place in early summer, several months prior to our sampling campaigns. However, I infer that plant wax records and other potential stable isotope proxy archives below the snowline are well-suited for qualitative, and potentially quantitative, reconstructions of past changes of ISM strength.