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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.
Hartmut Asche prägte über ein Vierteljahrhundert maßgeblich die Forschungsfelder der Geoinformation, Visualisierung und Kartographie. Die vorliegende Festschrift stellt eine würdige Gabe von Mitarbeiterinnen und Mitarbeitern des Institutes für Geographie der Universität Potsdam anlässlich seiner Emeritierung im März 2017 dar. International renommierte, Herrn Asches Karriere begleitende Autorinnen und Autoren, konnten für Fachbeiträge aus den Bereichen Geographie, Geoinformatik, Kartographie und Fernerkundung gewonnen werden. Es werden in fachlich hervorragender Weise Schwerpunkte umrissen, mit welchen Herr Asche sich in seiner von zahlreichen Höhepunkten geprägten wissenschaftlichen Karriere beschäftigte.
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.
Mountain ranges can fundamentally influence the physical and and chemical processes that shape Earths’ surface. With elevations of up to several kilometers they create climatic enclaves by interacting with atmospheric circulation and hydrologic systems, thus leading to a specific distribution of flora and fauna. As a result, the interiors of many Cenozoic mountain ranges are characterized by an arid climate, internally drained and sediment-filled basins, as well as unique ecosystems that are isolated from the adjacent humid, low-elevation regions along their flanks and forelands. These high-altitude interiors of orogens are often characterized by low relief and coalesced sedimentary basins, commonly referred to as plateaus, tectono-geomorphic entities that result from the complex interactions between mantle-driven geological and tectonic conditions and superposed atmospheric and hydrological processes. The efficiency of these processes and the fate of orogenic plateaus is therefore closely tied to the balance of constructive and destructive processes – tectonic uplift and erosion, respectively. In numerous geological studies it has been shown that mountain ranges are delicate systems that can be obliterated by an imbalance of these underlying forces. As such, Cenozoic mountain ranges might not persist on long geological timescales and will be destroyed by erosion or tectonic collapse. Advancing headward erosion of river systems that drain the flanks of the orogen may ultimately sever the internal drainage conditions and the maintenance of storage of sediments within the plateau, leading to destruction of plateau morphology and connectivity with the foreland. Orogenic collapse may be associated with the changeover from a compressional stress field with regional shortening and topographic growth, to a tensional stress field with regional extensional deformation and ensuing incision of the plateau. While the latter case is well-expressed by active extensional faults in the interior parts of the Tibetan Plateau and the Himalaya, for example, the former has been attributed to have breached the internally drained areas of the high-elevation sectors of the Iranian Plateau.
In the case of the Andes of South America and their internally drained Altiplano-Puna Plateau, signs of both processes have been previously described. However, in the orogenic collapse scenario the nature of the extensional structures had been primarily investigated in the northern and southern terminations of the plateau; in some cases, the extensional faults were even regarded to be inactive. After a shallow earthquake in 2020 within the Eastern Cordillera of Argentina that was associated with extensional deformation, the state of active deformation and the character of the stress field in the central parts of the plateau received renewed interest to explain a series of extensional structures in the northernmost sectors of the plateau in north-western Argentina. This study addresses (1) the issue of tectonic orogenic collapse of the Andes and the destruction of plateau morphology by studying the fill and erosion history of the central eastern Andean Plateau using sedimentological and geochronological data and (2) the kinematics, timing and magnitude of extensional structures that form well-expressed fault scarps in sediments of the regional San Juan del Oro surface, which is an integral part of the Andean Plateau and adjacent morphotectonic provinces to the east.
Importantly, sediment properties and depositional ages document that the San Juan del Oro Surface was not part of the internally-drained Andean Plateau, but rather associated with a foreland-directed drainage system, which was modified by the Andean orogeny and that became successively incorporated into the orogen by the eastward-migration of the Andean deformation front during late Miocene – Pliocene time. Structural and geomorphic observations within the plateau indicate that extensional processes must have been repeatedly active between the late Miocene and Holocene supporting the notion of plateau-wide extensional processes, potentially associated with Mw ~ 7 earthquakes. The close relationship between extensional joints and fault orientations underscores that 3 was oriented horizontally in NW-SE direction and 1 was vertical. This unambiguously documents that the observed deformation is related to gravitational forces that drive the orogenic collapse of the plateau. Applied geochronological analyses suggest that normal faulting in the northern Puna was active at about 3 Ma, based on paired cosmogenic nuclide dating of sediment fill units. Possibly due to regional normal faulting the drainage system within the plateau was modified, promoting fluvial incision.
Extreme flooding displaces an average of 12 million people every year. Marginalized populations in low-income countries are in particular at high risk, but also industrialized countries are susceptible to displacement and its inherent societal impacts. The risk of being displaced results from a complex interaction of flood hazard, population exposed in the floodplains, and socio-economic vulnerability. Ongoing global warming changes the intensity, frequency, and duration of flood hazards, undermining existing protection measures. Meanwhile, settlements in attractive yet hazardous flood-prone areas have led to a higher degree of population exposure. Finally, the vulnerability to displacement is altered by demographic and social change, shifting economic power, urbanization, and technological development. These risk components have been investigated intensively in the context of loss of life and economic damage, however, only little is known about the risk of displacement under global change.
This thesis aims to improve our understanding of flood-induced displacement risk under global climate change and socio-economic change. This objective is tackled by addressing the following three research questions. First, by focusing on the choice of input data, how well can a global flood modeling chain reproduce flood hazards of historic events that lead to displacement? Second, what are the socio-economic characteristics that shape the vulnerability to displacement? Finally, to what degree has climate change potentially contributed to recent flood-induced displacement events?
To answer the first question, a global flood modeling chain is evaluated by comparing simulated flood extent with satellite-derived inundation information for eight major flood events. A focus is set on the sensitivity to different combinations of the underlying climate reanalysis datasets and global hydrological models which serve as an input for the global hydraulic model. An evaluation scheme of performance scores shows that simulated flood extent is mostly overestimated without the consideration of flood protection and only for a few events dependent on the choice of global hydrological models. Results are more sensitive to the underlying climate forcing, with two datasets differing substantially from a third one. In contrast, the incorporation of flood protection standards results in an underestimation of flood extent, pointing to potential deficiencies in the protection level estimates or the flood frequency distribution within the modeling chain.
Following the analysis of a physical flood hazard model, the socio-economic drivers of vulnerability to displacement are investigated in the next step. For this purpose, a satellite- based, global collection of flood footprints is linked with two disaster inventories to match societal impacts with the corresponding flood hazard. For each event the number of affected population, assets, and critical infrastructure, as well as socio-economic indicators are computed. The resulting datasets are made publicly available and contain 335 displacement events and 695 mortality/damage events. Based on this new data product, event-specific displacement vulnerabilities are determined and multiple (national) dependencies with the socio-economic predictors are derived. The results suggest that economic prosperity only partially shapes vulnerability to displacement; urbanization, infant mortality rate, the share of elderly, population density and critical infrastructure exhibit a stronger functional relationship, suggesting that higher levels of development are generally associated with lower vulnerability.
Besides examining the contextual drivers of vulnerability, the role of climate change in the context of human displacement is also being explored. An impact attribution approach is applied on the example of Cyclone Idai and associated extreme coastal flooding in Mozambique. A combination of coastal flood modeling and satellite imagery is used to construct factual and counterfactual flood events. This storyline-type attribution method allows investigating the isolated or combined effects of sea level rise and the intensification of cyclone wind speeds on coastal flooding. The results suggest that displacement risk has increased by 3.1 to 3.5% due to the total effects of climate change on coastal flooding, with the effects of increasing wind speed being the dominant factor.
In conclusion, this thesis highlights the potentials and challenges of modeling flood- induced displacement risk. While this work explores the sensitivity of global flood modeling to the choice of input data, new questions arise on how to effectively improve the reproduction of flood return periods and the representation of protection levels. It is also demonstrated that disentangling displacement vulnerabilities is feasible, with the results providing useful information for risk assessments, effective humanitarian aid, and disaster relief. The impact attribution study is a first step in assessing the effects of global warming on displacement risk, leading to new research challenges, e.g., coupling fluvial and coastal flood models or the attribution of other hazard types and displacement events. This thesis is one of the first to address flood-induced displacement risk from a global perspective. The findings motivate for further development of the global flood modeling chain to improve our understanding of displacement vulnerability and the effects of global warming.
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.
Geomorphology seeks to characterize the forms, rates, and magnitudes of sediment and water transport that sculpt landscapes. This is generally referred to as earth surface processes, which incorporates the influence of biologic (e.g., vegetation), climatic (e.g., rainfall), and tectonic (e.g., mountain uplift) factors in dictating the transport of water and eroded material. In mountains, high relief and steep slopes combine with strong gradients in rainfall and vegetation to create dynamic expressions of earth surface processes. This same rugged topography presents challenges in data collection and process measurement, where traditional techniques involving detailed observations or physical sampling are difficult to apply at the scale of entire catchments. Herein lies the utility of remote sensing. Remote sensing is defined as any measurement that does not disturb the natural environment, typically via acquisition of images in the visible- to radio-wavelength range of the electromagnetic spectrum. Remote sensing is an especially attractive option for measuring earth surface processes, because large areal measurements can be acquired at much lower cost and effort than traditional methods. These measurements cover not only topographic form, but also climatic and environmental metrics, which are all intertwined in the study of earth surface processes. This dissertation uses remote sensing data ranging from handheld camera-based photo surveying to spaceborne satellite observations to measure the expressions, rates, and magnitudes of earth surface processes in high-mountain catchments of the Eastern Central Andes in Northwest Argentina. This work probes the limits and caveats of remote sensing data and techniques applied to geomorphic research questions, and presents important progress at this disciplinary intersection.
Remote sensing technology, such as airborne, mobile, or terrestrial laser scanning, and photogrammetric techniques, are fundamental approaches for efficient, automatic creation of digital representations of spatial environments. For example, they allow us to generate 3D point clouds of landscapes, cities, infrastructure networks, and sites. As essential and universal category of geodata, 3D point clouds are used and processed by a growing number of applications, services, and systems such as in the domains of urban planning, landscape architecture, environmental monitoring, disaster management, virtual geographic environments as well as for spatial analysis and simulation.
While the acquisition processes for 3D point clouds become more and more reliable and widely-used, applications and systems are faced with more and more 3D point cloud data. In addition, 3D point clouds, by their very nature, are raw data, i.e., they do not contain any structural or semantics information. Many processing strategies common to GIS such as deriving polygon-based 3D models generally do not scale for billions of points. GIS typically reduce data density and precision of 3D point clouds to cope with the sheer amount of data, but that results in a significant loss of valuable information at the same time.
This thesis proposes concepts and techniques designed to efficiently store and process massive 3D point clouds. To this end, object-class segmentation approaches are presented to attribute semantics to 3D point clouds, used, for example, to identify building, vegetation, and ground structures and, thus, to enable processing, analyzing, and visualizing 3D point clouds in a more effective and efficient way. Similarly, change detection and updating strategies for 3D point clouds are introduced that allow for reducing storage requirements and incrementally updating 3D point cloud databases. In addition, this thesis presents out-of-core, real-time rendering techniques used to interactively explore 3D point clouds and related analysis results. All techniques have been implemented based on specialized spatial data structures, out-of-core algorithms, and GPU-based processing schemas to cope with massive 3D point clouds having billions of points.
All proposed techniques have been evaluated and demonstrated their applicability to the field of geospatial applications and systems, in particular for tasks such as classification, processing, and visualization. Case studies for 3D point clouds of entire cities with up to 80 billion points show that the presented approaches open up new ways to manage and apply large-scale, dense, and time-variant 3D point clouds as required by a rapidly growing number of applications and systems.
Permafrost is warming globally, which leads to widespread permafrost thaw and impacts the surrounding landscapes, ecosystems and infrastructure. Especially ice-rich permafrost is vulnerable to rapid and abrupt thaw, resulting from the melting of excess ground ice. Local remote sensing studies have detected increasing rates of abrupt permafrost disturbances, such as thermokarst lake change and drainage, coastal erosion and RTS in the last two decades. All of which indicate an acceleration of permafrost degradation.
In particular retrogressive thaw slumps (RTS) are abrupt disturbances that expand by up to several meters each year and impact local and regional topographic gradients, hydrological pathways, sediment and nutrient mobilisation into aquatic systems, and increased permafrost carbon mobilisation. The feedback between abrupt permafrost thaw and the carbon cycle is a crucial component of the Earth system and a relevant driver in global climate models. However, an assessment of RTS at high temporal resolution to determine the dynamic thaw processes and identify the main thaw drivers as well as a continental-scale assessment across diverse permafrost regions are still lacking.
In northern high latitudes optical remote sensing is restricted by environmental factors and frequent cloud coverage. This decreases image availability and thus constrains the application of automated algorithms for time series disturbance detection for large-scale abrupt permafrost disturbances at high temporal resolution. Since models and observations suggest that abrupt permafrost disturbances will intensify, we require disturbance products at continental-scale, which allow for meaningful integration into Earth system models.
The main aim of this dissertation therefore, is to enhance our knowledge on the spatial extent and temporal dynamics of abrupt permafrost disturbances in a large-scale assessment. To address this, three research objectives were posed:
1. Assess the comparability and compatibility of Landsat-8 and Sentinel-2 data for a combined use in multi-spectral analysis in northern high latitudes.
2. Adapt an image mosaicking method for Landsat and Sentinel-2 data to create combined mosaics of high quality as input for high temporal disturbance assessments in northern high latitudes.
3. Automatically map retrogressive thaw slumps on the landscape-scale and assess their high temporal thaw dynamics.
We assessed the comparability of Landsat-8 and Sentinel-2 imagery by spectral comparison of corresponding bands. Based on overlapping same-day acquisitions of Landsat-8 and Sentinel-2 we derived spectral bandpass adjustment coefficients for North Siberia to adjust Sentinel-2 reflectance values to resemble Landsat-8 and harmonise the two data sets. Furthermore, we adapted a workflow to combine Landsat and Sentinel-2 images to create homogeneous and gap-free annual mosaics. We determined the number of images and cloud-free pixels, the spatial coverage and the quality of the mosaic with spectral comparisons to demonstrate the relevance of the Landsat+Sentinel-2 mosaics. Lastly, we adapted the automatic disturbance detection algorithm LandTrendr for large-scale RTS identification and mapping at high temporal resolution. For this, we modified the temporal segmentation algorithm for annual gradual and abrupt disturbance detection to incorporate the annual Landsat+Sentinel-2 mosaics. We further parametrised the temporal segmentation and spectral filtering for optimised RTS detection, conducted further spatial masking and filtering, and implemented a binary object classification algorithm with machine-learning to derive RTS from the LandTrendr disturbance output. We applied the algorithm to North Siberia, covering an area of 8.1 x 106 km2.
The spectral band comparison between same-day Landsat-8 and Sentinel-2 acquisitions already showed an overall good fit between both satellite products. However, applying the acquired spectral bandpass coefficients for adjustment of Sentinel-2 reflectance values, resulted in a near-perfect alignment between the same-day images. It can therefore be concluded that the spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to those of Landsat-8 in North Siberia.
The number of available cloud-free images increased steadily between 1999 and 2019, especially intensified after 2016 with the addition of Sentinel-2 images. This signifies a highly improved input database for the mosaicking workflow. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas, while Landsat-only mosaics contained data-gaps for the same years. The spectral comparison of input images and Landsat+Sentinel-2 mosaic showed a high correlation between the input images and the mosaic bands, testifying mosaicking results of high quality. Our results show that especially the mosaic coverage for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining data from both Landsat and Sentinel-2 sensors we reliably created input mosaics at high spatial resolution for comprehensive time series analyses.
This research presents the first automatically derived assessment of RTS distribution and temporal dynamics at continental-scale. In total, we identified 50,895 RTS, primarily located in ice-rich permafrost regions, as well as a steady increase in RTS-affected areas between 2001 and 2019 across North Siberia. From 2016 onward the RTS area increased more abruptly, indicating heightened thaw slump dynamics in this period. Overall, the RTS-affected area increased by 331 % within the observation period. Contrary to this, five focus sites show spatiotemporal variability in their annual RTS dynamics, alternating between periods of increased and decreased RTS development. This suggests a close relationship to varying thaw drivers. The majority of identified RTS was active from 2000 onward and only a small proportion initiated during the assessment period. This highlights that the increase in RTS-affected area was mainly caused by enlarging existing RTS and not by newly initiated RTS.
Overall, this research showed the advantages of combining Landsat and Sentinel-2 data in northern high latitudes and the improvements in spatial and temporal coverage of combined annual mosaics. The mosaics build the database for automated disturbance detection to reliably map RTS and other abrupt permafrost disturbances at continental-scale. The assessment at high temporal resolution further testifies the increasing impact of abrupt permafrost disturbances and likewise emphasises the spatio-temporal variability of thaw dynamics across landscapes. Obtaining such consistent disturbance products is necessary to parametrise regional and global climate change models, for enabling an improved representation of the permafrost thaw feedback.
In the high mountains of Asia, glaciers cover an area of approximately 115,000 km² and constitute one of the largest continental ice accumulations outside Greenland and Antarctica. Their sensitivity to climate change makes them valuable palaeoclimate archives, but also vulnerable to current and predicted Global Warming. This is a pressing problem as snow and glacial melt waters are important sources for agriculture and power supply of densely populated regions in south, east, and central Asia. Successful prediction of the glacial response to climate change in Asia and mitigation of the socioeconomic impacts requires profound knowledge of the climatic controls and the dynamics of Asian glaciers. However, due to their remoteness and difficult accessibility, ground-based studies are rare, as well as temporally and spatially limited. We therefore lack basic information on the vast majority of these glaciers. In this thesis, I employ different methods to assess the dynamics of Asian glaciers on multiple time scales. First, I tested a method for precise satellite-based measurement of glacier-surface velocities and conducted a comprehensive and regional survey of glacial flow and terminus dynamics of Asian glaciers between 2000 and 2008. This novel and unprecedented dataset provides unique insights into the contrasting topographic and climatic controls of glacial flow velocities across the Asian highlands. The data document disparate recent glacial behavior between the Karakoram and the Himalaya, which I attribute to the competing influence of the mid-latitude westerlies during winter and the Indian monsoon during summer. Second, I tested whether such climate-related longitudinal differences in glacial behavior also prevail on longer time scales, and potentially account for observed regionally asynchronous glacial advances. I used cosmogenic nuclide surface exposure dating of erratic boulders on moraines to obtain a glacial chronology for the upper Tons Valley, situated in the headwaters of the Ganges River. This area is located in the transition zone from monsoonal to westerly moisture supply and therefore ideal to examine the influence of these two atmospheric circulation regimes on glacial advances. The new glacial chronology documents multiple glacial oscillations during the last glacial termination and during the Holocene, suggesting largely synchronous glacial changes in the western Himalayan region that are related to gradual glacial-interglacial temperature oscillations with superimposed monsoonal precipitation changes of higher frequency. In a third step, I combine results from short-term satellite-based climate records and surface velocity-derived ice-flux estimates, with topographic analyses to deduce the erosional impact of glaciations on long-term landscape evolution in the Himalayan-Tibetan realm. The results provide evidence for the long-term effects of pronounced east-west differences in glaciation and glacial erosion, depending on climatic and topographic factors. Contrary to common belief the data suggest that monsoonal climate in the central Himalaya weakens glacial erosion at high elevations, helping to maintain a steep southern orographic barrier that protects the Tibetan Plateau from lateral destruction. The results of this thesis highlight how climatic and topographic gradients across the high mountains of Asia affect glacier dynamics on time scales ranging from 10^0 to 10^6 years. Glacial response times to climate changes are tightly linked to properties such as debris cover and surface slope, which are controlled by the topographic setting, and which need to be taken into account when reconstructing mountainous palaeoclimate from glacial histories or assessing the future evolution of Asian glaciers. Conversely, the regional topographic differences of glacial landscapes in Asia are partly controlled by climatic gradients and the long-term influence of glaciers on the topographic evolution of the orogenic system.