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. / Die arktische Tundra ist mit circa 5,5 % der Landoberfläche eines der letzten großen verbliebenen fast unberührten Ökosysteme unserer Erde. Nur die Fernerkundung ist in der Lage, benötigte Informationen über Struktur und Zustand dieses Ökosystems großräumig und in regelmäßigen Zeitabständen zur Verfügung zu stellen. Aber fast alle natürlichen Oberflächen zeigen individuelle anisotrope Reflexionsverhaltensweisen, welche durch die bidirektionale Reflektanzverteilungsfunktion (englisch: BRDF) beschrieben werden können. Dieser Effekt kann zu erheblichen Veränderungen im gemessenen Reflexionsgrad der Oberfläche in Abhängigkeit von den solaren Beleuchtung- und Blickrichtungsgeometrien führen. Zielstellung dieser Arbeit ist die hyperspektrale und spektro-direktionale Charakterisierung der Oberflächenreflexion wichtiger und repräsentativer arktischer Pflanzengesellschaften in Sibirien und Alaska, als Grundlage für die Extraktion von Vegetationsparametern und die Normalisierung von BRDF-Effekten in Off-Nadir und multi-temporalen Fernerkundungsdaten. In Vorbereitung auf die bevorstehende nationale EnMAP Satellitenmission ist ein Grundverständnis der BRDF-Effekte in der arktischen Tundra von wesentlicher Bedeutung für die Erstellung von hochqualitativen, konsistenten und damit vergleichbaren Datensätzen. Die in dieser Arbeit genutzten Daten beruhen auf geländespektroskopische und geländespektro-goniometrische Untersuchungen von repräsentativen Messflächen in Sibirien und Alaska. Die Entwicklung eines leichten, transportablen und einfach anzuwendenden Geländespektro-Goniometers, welches dennoch zuverlässig Daten liefert, war die erste Aufgabe. Hierfür habe ich ein Gerät mit der Bezeichnung ManTIS („Manual Transportable Instrument platform for ground-based Spectro-directional observations“) entwickelt. Die Ergebnisse der geländespektro-radiometrischen Messungen entlang wichtiger ökologischer Gradienten (regionales Klima, pH-Wert des Bodens, Bodenfeuchte, Toposequenz) zeigen, dass die Pflanzengesellschaften sich anhand ihrer Nadir-Reflektanzen unterscheiden lassen. Insbesondere die Möglichkeit der Differenzierung im sichtbaren (VIS) blauen und roten Wellenlängenbereich. Die Nah-Infrarot (NIR) Schulter und das NIR-Reflektanzplateau sind trotz ihrer niedrigeren Reflektanzwerte eine wertvolle Informationsquelle, die genutzt werden kann um die Pflanzengesellschaften entsprechend ihrer Biomasse und der Vegetationsstruktur voneinander zu unterscheiden. Im Allgemeinen zeigen die verschiedenen Pflanzengesellschaften der Tundra: (i) eine niedrige maximale NIR-Reflektanz; (ii) ein schwaches oder nicht sichtbares lokales Reflektanzmaximum im grünen VIS-Spektrum; (iii) einen schmalen „red-edge“ Bereich zwischen dem roten und NIR-Wellenlängenbereich und (iv) kein deutliches NIR-Reflektanzplateau. Diese gemeinsamen Nadir-Reflektanzeigenschaften sind entscheidend für das Verständnis der Variabilität der BRDF-Effekte in der arktischen Tundra. Keine der untersuchten Pflanzengesellschaften wies isotrope Reflektanzeigenschaften auf. Im Allgemeinen zeigt Tundravegetation: (i) die höchsten BRDF-Effekte in der solaren Hauptebene; (ii) die maximalen Reflexionsgrade in den rückwärts gerichteten Blickrichtungen; (iii) höhere Grade an Anisotropie im VIS-Spektrum als im NIR-Spektrum und (iv) schüsselförmige Reflexionsgradverteilungen in den längeren Wellenlängenbereichen (>700 nm). Die Analyse des Einflusses von hohen Sonnenzenitwinkeln auf die Anisotropie der Rückstrahlung zeigt, dass sich mit zunehmenden Sonnenzenitwinkeln die Anisotropie-Eigenschaften in azimutal-symmetrische schüsselförmige Reflexionsgradverteilungen ändern. Auch ergeben die spektro-direktionalen Analysen, dass Fernerkundungsprodukte wie der NDVI oder die relative Absorptionstiefe stark von BRDF-Effekten beeinflusst werden. Die anisotropen Eigenschaften der Fernerkundungsprodukte können sich erheblich von den beobachteten BRDF-Effekten in den ursprünglichen Reflektanzdaten unterscheiden. Auch lässt sich aus den Ergebnissen ableiten, dass der NDVI relativ gesehen die blickrichtungsabhängigen BRDF-Effekte minimieren kann. Für die untersuchten Pflanzengesellschaften der Tundra weichen die Off-Nadir NDVI-Werte nie mehr als 10 % von den Nadir-NDVI-Werten ab. Im Resümee dieser Studie wird nachgewiesen, dass Änderungen in der Sonnen-Objekt-Sensor-Geometrie direkt zu Reflektanzveränderungen in den Fernerkundungsdaten von arktischen Pflanzengesellschaften der Tundra entsprechend ihrer objekt-spezifischen BRDF-Charakteristiken führen. Da die verschiedenen Arten der Tundravegetation nur kleine, aber signifikante Unterschiede in der Oberflächenreflektanz zeigen, ist es wichtig die spektro-direktionalen Reflexionseigenschaften bei der Entwicklung von Algorithmen für Fernerkundungsprodukte zu berücksichtigen.

The gum arabic belt in Sudan plays a significant role in environmental, social and economical aspects. The belt has suffered from deforestation and degradation due to natural hazards and human activities. This research was conducted in North Kordofan State, which is affected by modifications in conditions and composition of vegetation cover trends in the gum arabic belt as in the rest of the Sahelian Sudan zone. The application of remote sensing, geographical information system and satellites imageries with multi-temporal and spatial analysis of land use land cover provides the land managers with current and improved data for the purposes of effective management of natural resources in the gum arabic belt. This research investigated the possibility of identification, monitoring and mapping of the land use land cover changes and dynamics in the gum arabic belt during the last 35 years. Also a newly approach of object-based classification was applied for image classification. Additionally, the study elaborated the integration of conventional forest inventory with satellite imagery for Acacia senegal stands. The study used imageries from different satellites (Landsat and ASTER) and multi-temporal dates (MSS 1972, TM 1985, ETM+ 1999 and ASTER 2007) acquired in dry season (November). The imageries were geo-referenced and radiometrically corrected by using ENVI-FLAASH software. Image classification (pixel-based and object-based), post-classification change detection, 2x2 and 3x3 pixel windows and accuracy assessment were applied. A total of 47 field samples were inventoried for Acacia senegal tree’s variables in Elhemmaria forest. Three areas were selected and distributed along the gum arabic belt. Regression method analysis was applied to study the relationship between forest attributes and the ASTER imagery. Application of multi-temporal remote sensing data in gum arabic belt demonstrated successfully the identification and mapping of land use land cover into five main classes. Also NDVI categorisation provided a consistent method for land use land cover stratification and mapping. Forest dominated by Acacia senegal class was separated covering an area of 21% and 24% in the year 2007 for areas A and B, respectively. The land use land cover structure in the gum arabic belt has obvious changes and reciprocal conversions between the classes indicating the trends and conditions caused by the human interventions as well as ecological impacts on Acacia senegal trees. The study revealed a drastic loss of Acacia senegal cover by 25% during the period of 1972 to 2007.The results of the study revealed to a significant correlation (p ≤ 0.05) between the ASTER bands (VNIR) and vegetation indices (NDVI, SAVI, RVI) with stand density, volume, crown area and basal area of Acacia senegal trees. The derived 2x2 and 3x3 pixel windows methods successfully extracted the spectral reflectance of Acacia senegal trees from ASTER imagery. Four equations were developed and could be widely used and applied for monitoring the stand density, volume, basal area and crown area of Acacia senegal trees in the gum arabic belt considering the similarity between the selected areas. The pixel-based approach performed slightly better than the object-based approach in land use land cover classification in the gum arabic belt. The study come out with some valuable recommendations and comments which could contribute positively in using remotely sensed imagery and GIS techniques to explore management tools of Acacia senegal stands in order to maintain the tree component in the farming and the land use systems in the gum arabic belt.

Due to a high population growth (approx. 2.5 % p.a) the food-sector in Syria is facing in-creasing problems. An enormous increase in population results in increased demand for food. This has adversely affected the socio-economic and ecological development in the country. Intensive use of various natural resources has led to significant changes in land use pattern, especially due to use of inappropriate methods in the agricultural sector. The increasing anthropogenic pressure on the sensitive ecological structure of the respective area causes environmental damages, in particular degradation of soil characteristics. In the semi-arid and arid eco-climatic zones vast areas are facing desertification. Soil erosion through water represents the main form of land degradation in the north-west of Syria. Particularly vulnerable are the soils with a shallow or no vegetation cover, such as the soils found in the Mediterranean hills, where olives are cultivated. For this research the Afrin region, located in the northwest of Syria, was selected as study area, in order to analyse and assess the extent of degradation. For estimation of erosion the relevant parameters of the “Universal Soil Loss Equation USLE” were used. These para-meters were adapted and integrated through remote sensing and GIS. LANDSAT TM and ASTER satellite imagery of the investigated area were used for this purpose. Data were acquired at the end of the dry season. In order to achieve an accurate evaluation and high-quality comparison of multi-temporal satellite data, imagery was firstly geometrically and atmospherically corrected and then analysed. The vegetation coverage and its current de-gradation level were investigated by spectral mixture analysis (SMA). The digital elevation model (DEM) derived from ASTER data was utilized to generate the slope gradient (S) and the slope length (L). In addition to the laboratory analysis, grain size index (GSI) and SMA were used for the characterization and mapping of soil erodibility. Land-use/land-cover classification and change detection were determined by using pixel-based classification procedures (maximum likelihood classification) and post classification methods respectively. Required samples for land cover classification of the remotely sensed data were collected during the field work, in addition to the soil samples for soil analysis. The results of this study show that advanced methods of remote sensing and GIS provide powerful tools not only for a better understanding of the land use changes, but also for an accurate assessment of land degradation and desertification. This knowledge, in turn, con-tributes highly towards developing effective and appropriate management strategies for sustainable use and conservation of natural resources in the north-west of Syria

Phänologie, die Lehre der periodisch wiederkehrenden Entwicklungserscheinungen in der Natur, hat sich in den letzten Jahrzehnten zu einem wichtigen Teilgebiet der Klimaforschung entwickelt. Einer der Haupteffekte der globalen Erwärmung ist die Veränderung der Wachstumsmuster und Fortpflanzungsgewohnheiten von Pflanzen, und somit veränderte Phänologie. Um die Auswirkungen der Klimaveränderung auf wildwachsende sowie Kulturpflanzen vorherzusagen, werden phänologische Modelle angewendet, verbessert und validiert. Dabei ist Wissen über den aktuellen Stand der Vegetation notwendig, welches aus Beobachtungen und fernerkundliche Messungen gewonnen wird. Die hier präsentierte Arbeit befasst sich mit dem Verständnis der Zusammenhänge zwischen fernerkundlichen Messungen und phänologischen Stadien und somit den Herausforderungen der modernen phänologischen Forschung: Der Vorhersage der Phänologie durch Modellierungsansätze, der Beobachtung der Phänologie mit optischen boden- und satellitengestützten Sensoren und der Validierung phänologischer Produkte. / Phenology, the study of recurring life cycle events of plants and animals has emerged as an important part of climate change research within the last decades. One of the main effects of global warming on vegetation is altered phenology, since plants have to modify their growth patterns and reproduction habits as reaction to changing environmental conditions. Forecasting phenology, thus phenological modelling, is a timely challenge given the necessity to predict the impact of global warming on wild-growing species and agricultural crops. However, assessing the present state of vegetation, thus phenological monitoring, is essential to update and validate model results. An improved comprehension of the relationships between plant phenology and remotely sensed products is crucial to interpret these results. Consequently, the presented thesis deals with the main challenges faced in modern phenology research, covering phenological forecasting with a modelling approach, satellite-based phenology extraction, and near-surface long-term monitoring of phenology.

Imaging photoplethysmography (iPPG) has attracted much attention over the last years. The vast majority of works focuses on methods to reliably extract the heart rate from videos. Only a few works addressed iPPGs ability to exploit spatio-temporal perfusion pattern to derive further diagnostic statements. This work directs at the spatio-temporal analysis of blood perfusion from videos. We present a novel algorithm that bases on the two-dimensional representation of the blood pulsation (perfusion map). The basic idea behind the proposed algorithm consists of a pairwise estimation of time delays between photoplethysmographic signals of spatially separated regions. The probabilistic approach yields a parameter denoted as perfusion speed. We compare the perfusion speed versus two parameters, which assess the strength of blood pulsation (perfusion strength and signal to noise ratio). Preliminary results using video data with different physiological stimuli (cold pressure test, cold face test) show that all measures are in fluenced by those stimuli (some of them with statistical certainty). The perfusion speed turned out to be more sensitive than the other measures in some cases. However, our results also show that the intraindividual stability and interindividual comparability of all used measures remain critical points. This work proves the general feasibility of employing the perfusion speed as novel iPPG quantity. Future studies will address open points like the handling of ballistocardiographic effects and will try to deepen the understanding of the predominant physiological mechanisms and their relation to the algorithmic performance.

The field of earth observation (EO) has seen tremendous development over recent time owing to the increasing quality of the sensor technology and the increasing number of operational satellites launched by several space organizations and companies around the world. Traditionally, the satellite data is analyzed by only considering the spectral characteristics measured at a pixel. The spatial relations and context were often ignored. With the advent of very high resolution satellite sensors providing a spatial resolution of ≤ 5m, the shortfalls of traditional pixel-based image processing techniques became evident. The need to identify new methods then led to focusing on the so called object-based image analysis (OBIA) methodologies. Unlike the pixel-based methods, the object-based methods which are based on segmenting the image into homogeneous regions use the shape, texture and context associated with the patterns thus providing an improved basis for image analysis. The remote sensing data normally has to be processed in a different way to that of the other types of images. In the geographic sense OBIA is referred to as Geographic Object-Based Image Analysis (GEOBIA), where the GEO pseudo prefix emphasizes the geographic components. This thesis will provide an overview of the principles of GEOBIA, describe some fundamentally new contributions to OBIA in the geographical context and, finally, summarize the current status with ideas for future developments.

Im Rahmen von UPNS4D+ wird von mir der Teilbereich der automatisierten untertägigen Detektion von Gangerzlagerstätten und seltenen Erden bearbeitet. Dies erfolgt mittels eines Multisensoransatzes, der aus einer Hyperspektralkamera, einer RGB-Kamera und einem Laserscanner besteht. Die Grundlagen für die Kombination von hyperspektraler Bildverarbeitung und einer RGB-Kamera sind in der Industrie im Bereich von automatisierten Sortieranlagen zu finden. Im Bereich der Fernerkundung ist der Einsatz hyperspektraler Bilder für die Detektion geologischer Merkmale seit einigen Jahrzehnten üblich. Hier kann im Rahmen meiner Forschung gezeigt werden, dass mittels hyperspektraler Bilder Pyrit unter Tage detektiert werden kann. / In my research I work on a system which detects automatically the ore and rare earth element in a mine. This is part of UPNS4D+. For the detection I use a multi sensor system which consists of a hyperspectral camera, a RGB camera and a Laser scanner. Basics of this combination can be found in the industry. The combination of a RGB camera and a hyperspectral camera enables an automatic sorting of for example waste materials. Landsat satellites in the 1970 uses spectral information in order to detect the geology of the surface. I have tested the hyperspectral imaging in the Reiche Zeche and I can now show that Pyrite can be detected.

Mineralstaub und Seesalz sind der Masse nach die häufigsten Aerosoltypen und dominieren den natürlichen Aerosolanteil. Die vorliegende Arbeit untersucht, wie deren optische Eigenschaften durch atmosphärische Prozesse verändert werden. Im Rahmen der vorliegenden Arbeit wurde ein Drei-Wellenlängen-Polarisationslidar entwickelt, um ferntransportierten Wüstenstaub zu untersuchen. Die der Arbeit zugrunde liegenden Messungen wurden im Rahmen der SALTRACE-Kampagne (Experiment zum Ferntransport von Aerosolen aus der Sahara und Aerosol-Wolken-Wechselwirkung) auf Barbados (13º N, 59º W) in den Jahren 2013 und 2014 durchgeführt. Die Lidarmessungen in Barbados ergaben, dass der Saharastaub nach einem Transportweg von 5000 km über den Atlantik im Mittel (21 Fälle) ein lineares Partikeldepolarisationsverhältnis von 0.25 ± 0.03 bei 355 nm, 0.28 ± 0.02 bei 532 nm und 0.23 ± 0.02 bei 1064 nm aufweist. Im Vergleich mit vorangegangen Messungen in Marokko und auf den Kapverden wurde kein signifikanter Unterschied der Werte bei 355 und 532 nm festgestellt. Lediglich die Abnahme des Depolarisationsverhälnisses bei 1064 nm zwischen Marokko und Barbados deutet auf einen Verlust der größeren Staubpartikel hin, ein Ergebnis, das von flugzeuggetragenen in-situ-Messungen bekräftigt wurde. Die optischen Eigenschaften von marinen Aerosolpartikeln wurden in Abhängigkeit der relativen Feuchte (RH) gemessen. Zu diesem Ziel wurden die Polarisations- und Wasserdampfmessungen des Lidars mit den Temperaturprofilen der Radiosonde kombiniert. Der Phasenübergang von sphärischen Seesalzpartikeln bei hoher relativer Feuchte zu nichtsphärischen (würfelartigen) Seesalzkristallen bei geringer relativer Feuchte (<50% RH) konnte durch einen starken Anstieg des Partikeldepolarisationsverhältnisses von 0.02 auf 0.12, 0.15 und 0.10 bei 355, 532 und 1064 nm beobachtet werden. Die Bestimmung der Wachstumsfaktoren des Extinktionskoeffizienten bei einem Anstieg der relativen Feuchte von 40% auf 80% ergab 1.94 ± 0.94, 3.70 ± 1.14 und 5.37 ± 1.66 bei 355, 532 und 1064 nm. Die ausschließlich marin geprägten Luftmassen über Barbados Ende Februar 2014 während der SALTRACE-Winterkampagne boten ideale Messbedingungen. Als weiterer Beitrag zur Charakterisierung der optischen Eigenschaften atmosphärischer Aerosole wurde im Rahmen dieser Arbeit zum ersten Mal der Extinktionskoeffizient und das Lidarverhältnis bei 1064 nm gemessen. Die neue Technik basiert auf der Rotations- Ramanstreuung bei 1064 nm und wurde in einer Zirruswolke getestet, da dort der Extinktionskoeffizient im beobachteten Bereich wellenlängenunabhängig ist.:1 Introduction 2 Observations at Barbados 2.1 Meteorological situation at Barbados 2.2 SALTRACE campaign 3 Lidar technique 3.1 BERTHA lidar system 3.2 Mueller-Stokes formalism 3.3 Lidar equation 3.4 Particle backscatter coefficient 3.5 Extinction coefficient 3.6 Linear depolarization ratio 4 Results and Discussion 2 4.1 First publication: Triple-wavelength depolarization-ratio profiling of Saharan dust over Barbados during SALTRACE in 2013 and 2014 4.2 Second publication: Dry versus wet marine particle optical properties: RH dependence of depolarization ratio, backscatter, and extinction from multiwavelength lidar measurements during SALTRACE 4.3 Third publication: 1064 nm rotational Raman lidar for particle extinction and lidar-ratio profiling: cirrus case study 5 Summary and Conclusions / Mineral dust and sea salt are the most abundant aerosol types (by mass) dominating the natural aerosol load. The present thesis investigates how their optical properties change due to atmospheric processes. In the framework of this thesis, a triple-wavelength polarization lidar was developed for studies of desert dust after long-range transport. The measurements included in this thesis were performed in the framework of the Saharan Aerosol Long-Range Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) at Barbados (13º N, 59º W) in 2013 and 2014. In the Saharan dust plumes over Barbados after an atmospheric transport of 5000 km across the Atlantic an average (21 cases) particle linear depolarization ratio of 0.25 ± 0.03 at 355 nm, 0.28 ± 0.02 at 532 nm, and 0.23 ± 0.02 at 1064 nm was measured. When comparing these results to values of previous observations in Morocco and Cabo Verde, no significant change in the depolarization ratio at 355 and 532 nm of Saharan dust was detected. A decrease in the depolarization ratio at 1064 nm between Morocco and Barbados points to a loss of the larger dust particles, a result that was corroborated by air-borne in situ observations. The optical properties of marine aerosol particles were measured under changing ambient relative humidity (RH). For this purpose the polarization and vapor measurements of the lidar were combined with the temperature profile of the radiosonde. The phase transition from spherical sea salt particles under humid conditions to non-spherical (cubic-like) sea salt crystals under dry conditions (<50% RH) could be observed. A strong increase in the particle depolarization ratio from values around 0.02 to values of 0.12 at 355 nm, 0.15 at 532 nm and 0.10 at 1064 nm for cubic-like marine particles was found. A particle extinction enhancement factor of 1.94 ± 0.94, 3.70 ± 1.14 and 5.37 ± 1.66 at 355, 532 and 1064 nm was observed under pristine marine conditions for an increase in RH from 40% to 80%. The measurements were performed while pure marine conditions prevailed at Barbados during the SALTRACE winter campaign at the end of February 2014. In the framework of this thesis, as a further contribution to the characterization of the optical properties of atmospheric aerosols, the extinction coefficient and the lidar ratio at 1064 nm were measured for the first time. The new technique is based on rotational Raman scattering at 1064 nm. The new method was tested in a cirrus cloud taking advantage of the wavelength independence (in the 355 – 1064 nm range) of the extinction coefficient.:1 Introduction 2 Observations at Barbados 2.1 Meteorological situation at Barbados 2.2 SALTRACE campaign 3 Lidar technique 3.1 BERTHA lidar system 3.2 Mueller-Stokes formalism 3.3 Lidar equation 3.4 Particle backscatter coefficient 3.5 Extinction coefficient 3.6 Linear depolarization ratio 4 Results and Discussion 2 4.1 First publication: Triple-wavelength depolarization-ratio profiling of Saharan dust over Barbados during SALTRACE in 2013 and 2014 4.2 Second publication: Dry versus wet marine particle optical properties: RH dependence of depolarization ratio, backscatter, and extinction from multiwavelength lidar measurements during SALTRACE 4.3 Third publication: 1064 nm rotational Raman lidar for particle extinction and lidar-ratio profiling: cirrus case study 5 Summary and Conclusions

The significance of the polar regions for the Earth’s climate system and their observed amplified response to climate change indicate the necessity for high temporal and spatial coverage for the monitoring of the reflective properties of snow surfaces and their influencing factors. Therefore, the specific surface area (SSA, as a proxy for snow grain size) and the hemispherical directional reflectance factor (HDRF) of snow were measured for a 2-month period in central Antarctica (Kohnen research station) during austral summer 2013/14. The SSA data were retrieved on the basis of ground-based spectral surface albedo measurements collected by the COmpact RAdiation measurement System (CORAS) and airborne observations with the Spectral Modular Airborne Radiation measurement sysTem (SMART). The snow grain size and pollution amount (SGSP) algorithm, originally developed to analyze spaceborne reflectance measurements by the MODerate Resolution Imaging Spectroradiometer (MODIS), was modified in order to reduce the impact of the solar zenith angle on the retrieval results and to cover measurements in overcast conditions. Spectral ratios of surface albedo at 1280 and 1100 nm wavelength were used to reduce the retrieval uncertainty. The retrieval was applied to the ground-based and airborne observations and validated against optical in situ observations of SSA utilizing an IceCube device. The SSA retrieved from CORAS observations varied between 29 and 96 m2 kg-1. Snowfall events caused distinct relative maxima of the SSA which were followed by a gradual decrease in SSA due to snow metamorphism and wind-induced transport of freshly fallen ice crystals. The ability of the modified algorithm to include measurements in overcast conditions improved the data coverage, in particular at times when precipitation events occurred and the SSA changed quickly. SSA retrieved from measurements with CORAS and MODIS agree with the in situ observations within the ranges given by the measurement uncertainties. However, SSA retrieved from the airborne SMART data underestimated the ground-based results. The spatial variability of SSA in Dronning Maud Land ranged in the same order of magnitude as the temporal variability revealing differences between coastal areas and regions in interior Antarctica. The validation presented in this study provided an unique test bed for retrievals of SSA under Antarctic conditions where in situ data are scarce and can be used for testing prognostic snowpack models in Antarctic conditions. The HDRF of snow was derived from airborne measurements of a digital 180° fish-eye camera for a variety of conditions with different surface roughness, snow grain size, and solar zenith angle. The camera provides radiance measurements with high angular resolution utilizing detailed radiometric and geometric calibrations. The comparison between smooth and rough surfaces (sastrugi) showed significant differences in the HDRF of snow, which are superimposed on the diurnal cycle. By inverting a semi-empirical kernel-driven model for the bidirectional reflectance distribution function (BRDF), the snow HDRF was parameterized with respect to surface roughness, snow grain size, and solar zenith angle. This allows a direct comparison of the HDRF measurements with BRDF products from satellite remote sensing.

Due to a high population growth (approx. 2.5 % p.a) the food-sector in Syria is facing in-creasing problems. An enormous increase in population results in increased demand for food. This has adversely affected the socio-economic and ecological development in the country. Intensive use of various natural resources has led to significant changes in land use pattern, especially due to use of inappropriate methods in the agricultural sector. The increasing anthropogenic pressure on the sensitive ecological structure of the respective area causes environmental damages, in particular degradation of soil characteristics. In the semi-arid and arid eco-climatic zones vast areas are facing desertification. Soil erosion through water represents the main form of land degradation in the north-west of Syria. Particularly vulnerable are the soils with a shallow or no vegetation cover, such as the soils found in the Mediterranean hills, where olives are cultivated. For this research the Afrin region, located in the northwest of Syria, was selected as study area, in order to analyse and assess the extent of degradation. For estimation of erosion the relevant parameters of the “Universal Soil Loss Equation USLE” were used. These para-meters were adapted and integrated through remote sensing and GIS. LANDSAT TM and ASTER satellite imagery of the investigated area were used for this purpose. Data were acquired at the end of the dry season. In order to achieve an accurate evaluation and high-quality comparison of multi-temporal satellite data, imagery was firstly geometrically and atmospherically corrected and then analysed. The vegetation coverage and its current de-gradation level were investigated by spectral mixture analysis (SMA). The digital elevation model (DEM) derived from ASTER data was utilized to generate the slope gradient (S) and the slope length (L). In addition to the laboratory analysis, grain size index (GSI) and SMA were used for the characterization and mapping of soil erodibility. Land-use/land-cover classification and change detection were determined by using pixel-based classification procedures (maximum likelihood classification) and post classification methods respectively. Required samples for land cover classification of the remotely sensed data were collected during the field work, in addition to the soil samples for soil analysis. The results of this study show that advanced methods of remote sensing and GIS provide powerful tools not only for a better understanding of the land use changes, but also for an accurate assessment of land degradation and desertification. This knowledge, in turn, con-tributes highly towards developing effective and appropriate management strategies for sustainable use and conservation of natural resources in the north-west of Syria