550 Geowissenschaften
Refine
Has Fulltext
- yes (190) (remove)
Year of publication
Document Type
- Doctoral Thesis (97)
- Postprint (45)
- Article (20)
- Master's Thesis (9)
- Monograph/Edited Volume (5)
- Conference Proceeding (5)
- Report (4)
- Bachelor Thesis (3)
- Habilitation Thesis (1)
- Other (1)
Keywords
- climate change (18)
- Klimawandel (12)
- Modellierung (10)
- Hydrologie (7)
- Hochwasser (6)
- Klimaanpassung (6)
- vulnerability (6)
- hydrology (5)
- uncertainty (5)
- GIS (4)
Institute
- Institut für Umweltwissenschaften und Geographie (190) (remove)
Vor dem Hintergrund der Auffassung, dass ethnische Minderheiten eine Form so-zialer Organisation darstellen, verfolgt die Studie – unter Berücksichtigung der Mehr-deutigkeit des Raumbegriffs – das Ziel, anhand von Beispielen aus Rumänien ein Konzept zu entwickeln, mit dem sich die aktuelle Beziehung von Ethnizität und Raum im Transformationsprozess adäquat analysieren und beschreiben lässt.
Schwarz-Rot-Geil
(2018)
Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0.1)
(2019)
Quantitative precipitation nowcasting (QPN) has become an essential technique in various application contexts, such as early warning or urban sewage control. A common heuristic prediction approach is to track the motion of precipitation features from a sequence of weather radar images and then to displace the precipitation field to the imminent future (minutes to hours) based on that motion, assuming that the intensity of the features remains constant (“Lagrangian persistence”). In that context, “optical flow” has become one of the most popular tracking techniques. Yet the present landscape of computational QPN models still struggles with producing open software implementations. Focusing on this gap, we have developed and extensively benchmarked a stack of models based on different optical flow algorithms for the tracking step and a set of parsimonious extrapolation procedures based on image warping and advection. We demonstrate that these models provide skillful predictions comparable with or even superior to state-of-the-art operational software. Our software library (“rainymotion”) for precipitation nowcasting is written in the Python programming language and openly available at GitHub (https://github.com/hydrogo/rainymotion, Ayzel et al., 2019). That way, the library may serve as a tool for providing fast, free, and transparent solutions that could serve as a benchmark for further model development and hypothesis testing – a benchmark that is far more advanced than the conventional benchmark of Eulerian persistence commonly used in QPN verification experiments.
Planetary research is often user-based and requires considerable skill, time, and effort. Unfortunately, self-defined boundary conditions, definitions, and rules are often not documented or not easy to comprehend due to the complexity of research. This makes a comparison to other studies, or an extension of the already existing research, complicated. Comparisons are often distorted, because results rely on different, not well defined, or even unknown boundary conditions. The purpose of this research is to develop a standardized analysis method for planetary surfaces, which is adaptable to several research topics. The method provides a consistent quality of results. This also includes achieving reliable and comparable results and reducing the time and effort of conducting such studies. A standardized analysis method is provided by automated analysis tools that focus on statistical parameters. Specific key parameters and boundary conditions are defined for the tool application. The analysis relies on a database in which all key parameters are stored. These databases can be easily updated and adapted to various research questions. This increases the flexibility, reproducibility, and comparability of the research. However, the quality of the database and reliability of definitions directly influence the results. To ensure a high quality of results, the rules and definitions need to be well defined and based on previously conducted case studies. The tools then produce parameters, which are obtained by defined geostatistical techniques (measurements, calculations, classifications). The idea of an automated statistical analysis is tested to proof benefits but also potential problems of this method. In this study, I adapt automated tools for floor-fractured craters (FFCs) on Mars. These impact craters show a variety of surface features, occurring in different Martian environments, and having different fracturing origins. They provide a complex morphological and geological field of application. 433 FFCs are classified by the analysis tools due to their fracturing process. Spatial data, environmental context, and crater interior data are analyzed to distinguish between the processes involved in floor fracturing. Related geologic processes, such as glacial and fluvial activity, are too similar to be separately classified by the automated tools. Glacial and fluvial fracturing processes are merged together for the classification. The automated tools provide probability values for each origin model. To guarantee the quality and reliability of the results, classification tools need to achieve an origin probability above 50 %. This analysis method shows that 15 % of the FFCs are fractured by intrusive volcanism, 20 % by tectonic activity, and 43 % by water & ice related processes. In total, 75 % of the FFCs are classified to an origin type. This can be explained by a combination of origin models, superposition or erosion of key parameters, or an unknown fracturing model. Those features have to be manually analyzed in detail. Another possibility would be the improvement of key parameters and rules for the classification. This research shows that it is possible to conduct an automated statistical analysis of morphologic and geologic features based on analysis tools. Analysis tools provide additional information to the user and are therefore considered assistance systems.
Studies on the unsustainable use of groundwater resources are still considered incipient since it is frequently a poorly understood and managed, devalued and inadequately protected natural resource. Groundwater Recharge (GWR) is one of the most challenging elements to estimate since it can rarely be measured directly and cannot easily be derived from existing data. To overcome these limitations, many hydro(geo)logists have combined different approaches to estimate large-scale GWR, namely: remote sensing products, such as IMERG product; Water Budget Equation, also in combination with hydrological models, and; Geographic Information System (GIS), using estimation formulas. For intermediary-scale GWR estimation, there exist: Non-invasive Cosmic-Ray Neutron Sensing (CRNS); wireless networks from local soil probes; and soil hydrological models, such as HYDRUS. Accordingly, this PhD thesis aims, on the one hand, to demonstrate a GIS-based model coupling for estimating the GWR distribution on a large scale in tropical wet basins. On the other hand, it aims to use the time series from CRNS and invasive soil moisture probes to inversely calibrate the soil hydraulic properties, and based on this, estimating the intermediary-scale GWR using a soil hydrological model. For such purpose, two tropical wet basins located in a complex sedimentary aquifer in the coastal Northeast region of Brazil were selected. These are the João Pessoa Case Study Area and the Guaraíra Experimental Basin. Several satellite products in the first area were used as input to the GIS-based water budget equation model for estimating the water balance components and GWR in 2016 and 2017. In addition, the point-scale measurement and CRNS data were used in the second area to determine the soil hydraulic properties, and to estimate the GWR in the 2017-2018 and 2018-2019 hydrological years. The resulting values of GWR on large- and intermediary-scale were then compared and validated by the estimates obtained by groundwater table fluctuations. The GWR rates for IMERG- and rain-gauge-based scenarios showed similar coefficients between 68% and 89%, similar mean errors between 30% and 34%, and slightly-different bias between -13% and 11%. The results of GWR rates for soil probes and CRNS soil moisture scenarios ranged from -5.87 to -61.81 cm yr-1, which corresponds to 5% and 38% of the precipitation. The calculations of the mean GWR rates on large-scale, based on remote sensing data, and on intermediary-scale, based on CRNS data, held similar results for the Podzol soil type, namely 17.87% and 17% of the precipitation. It is then concluded that the proposed methodologies allowed for estimating realistically the GWR over the study areas, which can be a ground-breaking step towards improving the water management and decision-making in the Northeast of Brazil.
Im Landschaftszustand und in der Landschaftsentwicklung kommen funktionale Beziehungen zwischen dem naturbedingten Energie-, Wasser- und Stoffhaushalt einerseits und den Auswirkungen der Landnutzung andererseits zum Ausdruck. Gegenwärtig verändert der globale Anstieg der bodennahen Temperaturen vielerorts den landschaftlichen Energie-, Wasser- und Stoffhaushalt, wobei besonders in Trockengebieten zu erwarten ist, dass dieser Trend in Verbindung mit einer unangepassten Landnutzung das Regenerationsvermögen der Vegetation einschränkt und zur Zerstörung der Bodendecke führt. Für die Mongolei und für benachbarte Gebiete Asiens sind in Szenarien zur globalen Erwärmung hohe Werte des Temperaturanstiegs prognostiziert worden. Eine globale Einschätzung der anthropogen induzierten Bodendegradation hat diese Region als stark oder extrem stark betroffen eingestuft. Vor diesem Hintergrund wurde im Uvs-Nuur-Becken, das im Nordwesten der Mongolei und damit in einer der trockensten Regionen des Landes gelegen ist, untersucht, wie sich der globale Temperaturanstieg auf der lokalen und regionalen Ebene widerspiegelt und wie der Landschaftshaushalt dabei verändert wird. Die Auswirkungen des sommerlichen Witterungsverlaufes auf den Landschaftszustand sind 1997 bis 1999 an einem Transsekt erfasst worden, das sich zwischen dem Kharkhiraa-Gebirge am Westrand des Beckens und dem See Uvs Nuur im Beckeninneren von den Polsterfluren und Matten der alpinen Stufe über die Gebirgswaldsteppe, die Trockensteppe bis zur Halbwüste erstreckt. An neun Messpunkten wurden witterungsklimatische Daten in Verbindung mit Merkmalen der Vegetation, des Bodens und der Bodenfeuchte aufgenommen. Die im Sommer 1998 gewonnenen Messwerte wurden mit Hilfe einer Clusteranalyse gebündelt und verdichtet. Auf dieser Grundlage konnten landschaftliche Zustandsformen inhaltlich gekennzeichnet, zeitlich eingeordnet und durch Zeit-Verhaltens-Modelle (Stacks) abgebildet werden. Aus den Zeit-Verhaltens-Modellen wird ersichtlich, dass man Zustandsformen, in denen die Hitze und die Trockenheit des Sommers 1998 besonders stark zum Ausdruck kommen, an allen Messpunkten beobachten kann, nimmt man die Station auf dem fast 3.000 m hohen Gipfel des Khukh Uul sowie die grundwasserbeeinflusste Station in unmittelbarer Seenähe aus. In ihrer extremen Form sind Trockenperioden jedoch nur im Beckeninneren und am Fuß der Randgebirge, also in der Halbwüste, in der Trockensteppe und in der Wiesensteppe aufgetreten. Im Bergwald sowie im Bereich der alpinen Matten und Polsterfluren fehlen sie. Am stärksten sind die grundwasserfreien Bereiche der Halbwüste von der Hitze und Niederschlagsarmut des Sommers 1998 betroffen. An vier Fünfteln der Tage des Beobachtungszeitraumes herrscht an diesem Messpunkt extreme Trockenheit. Es fällt entweder gar kein Niederschlag oder nur so wenig, dass der seit dem Frühjahr erschöpfte Bodenwasservorrat nicht aufgefüllt wird. Das Verhältnis zwischen Niederschlag und potenzieller Verdunstung liegt hier bei 1:12. In der Halbwüste zeichnet sich eine fortschreitende Desertifikation ab, zumal hier eine nichtangepasste Weidenutzung dominiert, in der Ziegen eine immer größere Rolle spielen. Dies gilt insbesondere für Bereiche in Siedlungsnähe. Örtlich ist auch der Bestand der Trockensteppe gefährdet, die sich an die Halbwüste zum Beckenrand hin anschließt. Hier ist nicht nur die Viehdichte am höchsten, sondern hier werden auch die meisten unbefestigten Fahrwege wild angelegt und die Bodendecke damit zerstört. Dies kann im Endeffekt zu einem Übergreifen von Prozessen der Desertifikation führen. Aus methodischer Sicht zeigt sich, dass die Kennzeichnung landschaftlicher Zustandsformen durch Zeit-Verhaltens-Modelle die Ermittlung der Auswirkungen von Witterung und Klima auf den Landschaftszustand erleichtert, da sie deren Aussage konzentriert. Zur Interpretation der Ergebnisse ist jedoch ein Rückgriff auf die beschreibende Darstellung der Messwerte notwendig. Die im westlichen Uvs-Nuur-Becken und seinen Randgebirgen angewandte Verfahrensweise ermöglicht es, globale Aussagen zur globalen Erwärmung der Kontinente regional oder lokal zu überprüfen und zu untersetzen."
Exploring elections features from a geographical perspective is the focus of this study. Its primary objective is to develop a scientific approach based on geoinformation technology (GIT) that promotes deeper understanding how geographical settings affect the spatial and temporal variations of voting behaviour and election outcomes. For this purpose, the five parliamentary elections (1991-2005) following the political turnaround in 1990 in the South East European reform country Albania have been selected as a case study. Elections, like other social phenomena that do not develop uniformly over a territory, inherit a spatial dimension. Despite of fact that elections have been researched by various scientific disciplines ranging from political science to geography, studies that incorporate their spatial dimension are still limited in number and approaches. Consequently, the methodologies needed to generate an integrated knowledge on many facets that constitute election features are lacking. This study addresses characteristics and interactions of the essential elements involved in an election process. Thus, the baseline of the approach presented here is the exploration of relations between three entities: electorate (political and sociodemographic features), election process (electoral system and code) and place (environment where voters reside). To express this interaction the concept of electoral pattern is introduced. Electoral patterns are defined by the study as the final view of election results, chiefly in tabular and/or map form, generated by the complex interaction of social, economic, juridical, and spatial features of the electorate, which has occurred at a specific time and in a particular geographical location. GIT methods of geoanalysis and geovisualization are used to investigate the characteristics of electoral patterns in their spatial and temporal distribution. Aggregate-level data modelled in map form were used to analyse and visualize the spatial distribution of election patterns components and relations. The spatial dimension of the study is addressed in the following three main relations: One, the relation between place and electorate and its expression through the social, demographic and economic features of the electorate resulting in the profile of the electorate’s context; second, the electorate-election interaction which forms the baseline to explore the perspective of local contextual effects in voting behaviour and election results; third, the relation between geographical location and election outcomes reflecting the implication of determining constituency boundaries on election results. To address the above relations, three types of variables: geo, independent and dependent, have been elaborated and two models have been created. The Data Model, developed in a GIS environment, facilitates structuring of election data in order to perform spatial analysis. The peculiarity of electoral patterns – a multidimensional array that contains information on three variables, stored in data layers of dissimilar spatial units of reference and scales of value measurement – prohibit spatial analysis based on the original source data. To perform a joint spatial analysis it is therefore mandatory to restructure the spatial units of reference while preserving their semantic content. In this operation, all relevant electoral as well as socio-demographic data referenced to different administrative spatial entities are re-referenced to uniform grid cells as virtual spatial units of reference. Depending on the scale of data acquisition and map presentation, a cell width of 0.5 km has been determined. The resulting fine grid forms the basis of subsequent data analyses and correlations. Conversion of the original vector data layers into target raster layers allows for unification of spatial units, at the same time retaining the existing level of detail of the data (variables, uniform distribution over space). This in turn facilitates the integration of the variables studied and the performance of GIS-based spatial analysis. In addition, conversion to raster format makes it possible to assign new values to the original data, which are based on a common scale eliminating existing differences in scale of measurement. Raster format operations of the type described are well-established data analysis techniques in GIT, yet they have rarely been employed to process and analyse electoral data. The Geovisualization Model, developed in a cartographic environment, complements the Data Model. As an analog graphic model it facilitates efficient communication and exploration of geographical information through cartographic visualization. Based on this model, 52 choropleth maps have been generated. They represent the outcome of the GIS-based electoral data analysis. The analog map form allows for in-depth visual analysis and interpretation of the distribution and correlation of the electoral data studied. For researchers, decision makers and a wider public the maps provide easy-to-access information on and promote easy-to-understand insight into the spatial dimension, regional variation and resulting structures of the electoral patterns defined.