Identification and interpretation of tectonic features from ERTS-1 imagery: Southwestern North America and the Red Sea area

The author has identified the following significant results. The ERTS-1 imagery was utilized to study major fault and tectonic lines and their intersections in southwestern North America. A system of transverse shear faults was recognized in the California Coast Ranges, the Sierra Nevada, the Great Basin, and Mexico. They are interpreted as expressions of a major left-lateral shear which predated the San Andreas system, the opening of the Gulf of California and Basin and Range rift development. Tectonic models for Basin and Range, Coast Ranges, and Texas-Parras shears were developed. Geological structures and Precambrian metamorphic trend lines of schistosity were studied across the Red Sea rift

Analysis of tectonic features in US southwest from Skylab photographs

The author has identified the following significant results. Skylab photographs were utilized to study faults and tectonic lines in selected areas of the U.S. Southwest. Emphasis was on elements of the Texas Zone in the Mojave Desert and the tectonic intersection in southern Nevada. Transverse faults believed to represent the continuation of the Texas Zone were found to be anomalous in strike. This suggests that the Mojave Desert block was rotated counterclockwise as a unit with the Sierra Nevada. Left-lateral strike-slip faults in Lake Mead area are interpreted as elements of the Wasatch tectonic zone; their anomalous trend indicates that the Lake Mead area has rotated clockwise with the Colorado Plateau. A tectonic model relating major fault zones to fragmentation and rotation of crustal blocks was developed. Detailed correlation of the high resolution S190B metric camera photographs with U-2 photographs and geologic maps demonstrates the feasibility of utilizing S190B photographs for the identification of geomorphic features associated with recent and active faults and for the assessment of seismic hazards

Tectonic analysis of Baja California and Parras shear belt in Mexico

The author has identified the following significant results. Geological correlation of terrain across the Gulf of California using ERTS-1 imagery revealed significant similarities between Isla Tiburon, Isla Angel de la Guarda, and the San Carlos Range in mainland Mexico. ERTS-1 imagery was used to check the validity of the existence of major trans-Baja fault zones. ERTS-1 imagery also shows that high albedo sediments similar to known late Tertiary marine sediments are widespread in southern and middle Baja and extend in places to the eastern side of the Peninsula. Major faults in northern Mexico and across the border in the United States were mapped, and ample evidence was found that the Parras and parts of the Texas lineament are belts of major transverse shear faults in areas outside the supposed limit of the Texas and Parras lineaments. A fundamental concept which may help explain many complexities in the tectonic development is beginning to emerge: The southwestern part of North America was torn by massive left-lateral shear of transverse trend (east-west) during the compressive stage of the late Mesozoic and early Cenozoic. This tectonic style has changed into tensional rifting (Basin and Range) and right-lateral shear later in the Cenozoic and Quaternary

Der bedeckungsveränderliche P Cygni-Stern R 81 (B2.5 Ia-0) in der Großen Magellanschen Wolke

Anhand einer langen, kontinuierlichen Zeitserie simultaner hochauflösender FEROS-Spektren und photometrischer Daten im Strömgrensystem wurde der bedeckungsveränderliche P Cygni-Stern R 81 (HDE 269128, HIP 24080) des Spektraltyps B2.5 Ia-0 in der Großen Magellanschen Wolke untersucht. Das System hat eine Bahnperiode von 74.566 Tagen. Die mittlere Lichtkurve zeigt zwei Bedeckungsminima, einen Helligkeitsanstieg nach der Bedeckung des Hypergiganten und eine langsam abfallende Helligkeit zwischen den beiden Bedeckungen. Eine spektrale Signatur des Begleiters wurde nicht gefunden. An die Radialgeschwindigkeitskurve des Hypergiganten und die Lichtkurve wurde ein Modell angepasst, welches den Hypergiganten, den Begleiter, eine Scheibe um letzteren und einen heißen Fleck auf dem Rand der Scheibe annimmt. Mit diesem Modell konnte die Lichtkurve bis auf das Helligkeitsmaximum nach dem Hauptminimum reproduziert werden. Der Begleiter ist komplett von der Scheibe verhüllt. Die physikalische Ursache des Fleckes ist jedoch aufgrund seiner Position nicht klar. Mit dem Modell wurden die Massen des Hypergiganten bzw. des Begleiters zu M_1=15 M_sun respektive M_2=4 M_sun bestimmt. Diese Absolutwerte sind wegen Zweifel an der Gültigkeit des Modells jedoch als vorläufig zu betrachten. Das System ist eng und exzentrisch (e=0.405). Der Hypergigant und die Scheibe füllen beide ihre Roche-Volumina nahezu aus. Neben Anzeichen für Massenaus- oder -überfluss wurden bei dem Hypergiganten Linienprofilvariationen mit einer Periode von 10.98 Tagen, die wahrscheinlich durch nichtradiale Pulsationen verursacht werden, beobachtet

Characterization of the woody biomass feedstock potential resulting from California's drought.

Regional tree die-off events generate large quantities of standing dead wood, raising concern over catastrophic wildfire and other hazards. Governmental responses to tree die-off have often focused on incentivizing biomass energy production that utilizes standing dead trees removed for safety concerns. However, the full distribution of potential woody bioenergy feedstock after tree die-off has not been evaluated due to the complexities of surveying and precisely measuring large forested areas. In this paper, we present a novel method for estimating standing dead biomass at a fine spatial resolution that combines aerial survey data with forest structure maps. Using this method, we quantify biomass generated by the unprecedented tree die-off that occurred in California following a 4-year drought and widespread pest outbreaks. The results are used to estimate feasibly recoverable feedstock for energy production. We find that approximately 95.1 million bone-dry tons (BDT) of dead biomass resulted from 2012-2017 mortality, with a lower bound of 26.2 million BDT. In other words, of the aboveground live tree biomass in 2012, ~1.3-4.8% died by 2017. Of the standing dead biomass, 29% meets minimum constraints for potential cost-effective bioenergy feedstock. This proportion drops to as low as 15% in the most affected areas due to terrain slope, wilderness status, and other factors, highlighting the need to complement disposal via biomass energy with other strategies to mitigate the risks of the tree mortality crisis, which is likely to only become more severe over time due to climate change

Deep Learning Based Exposure Analysis of LandslideProne Areas in Medellín, Colombia

In the last century, Medellín grew into one of Colombia's largest cities. Today, the city continues to grow primarily due to the influx of internally displaced people (IDP’s), who have been forced to leave their homes at the country side due to natural disasters or drug-related violence. Since the internally displaced are mostly lowincome farmers and peasants, they are migrating to the larger cities in search of greater security and jobs. In Medellín, the new residents mostly settle informally on the steep slopes to the east and west of the city. Due to limited space and steep topography, such settlements are often built in areas with medium and high probability of landslides. However, not only free land area within the municipal boundaries are exploited by the build-up of new settlements, but also free land beyond the border of the municipality, which causes the city to grow into the rural area. The study therefore seeks to find out how many residents are prone to potential landslide activity in the context of the pattern of migration. To analyze the exposure, the population is disaggregated down to the individual building block level. Such an approach requires precise building footprints to locate the population in relation to landslide-prone areas. Although the city has a cadaster including building footprints, it is more imprecise and incomplete towards the outskirts of the city, where landslide susceptibility is most pronounced. The incompleteness is due to the high population dynamics, which makes it quite difficult to maintain an up-to-date cadaster. But since Medellín's geospatial data service provides an orthophoto from 2019, a deep learning-based building extraction is applied to generate a more comprehensive building footprint dataset. This will be the main data source for the exposure analysis. The respective deep learning architecture is a U-Net has been refined with the EfficientNetB2 as a backbone and eventually fine-tuned. It could show very accurate results, while still facing some challenges, like the field-of.view of the image tiles, that is sometimes too small for the vast rooftop landscapes, which leads to misclassifications. The exposure analysis of population exposed to landslide hazard could prove the importance of having a more up-to-date data basis. While the number of residents living in formal settlements is not to different from the cadaster and the deeplearning derived building footprints, those numbers of residents of the informal settlements are much higher in the more actual deep learning derived dataset. A strong increase could also be found in the population exposed to medium and high landslide hazard. Further analyses facilitate the impression, that the poorer and the more vulnerable population has distinctively higher exposure to considerable landslide hazard, when using the deep-learning derived dataset. These findings show the strength of remote sensing techniques in order to retrieve actual building footprint data, that is clearly important for the estimation of potential consequences of landslide-prone areas

A high volume sampling system for isotope determination of volatile halocarbons and hydrocarbons

The isotopic composition of volatile organic compounds (VOCs) can provide valuable information on their sources and fate not deducible from mixing ratios alone. In particular the reported carbon stable isotope ratios of chloromethane and bromomethane from different sources cover a δ13C-range of almost 100‰ making isotope ratios a very promising tool for studying the biogeochemistry of these compounds. So far, the determination of the isotopic composition of C1 and C2 halocarbons others than chloromethane is hampered by their low mixing ratios. In order to determine the carbon isotopic composition of C1 and C2 halocarbons with mixing ratios as low as 1 pptv (i) a field suitable cryogenic high volume sampling system and (ii) a chromatographic set up for processing these samples have been developed and validated. The sampling system was tested at two different sampling sites, an urban and a coastal location in Northern Germany. The average δ13C-values for bromomethane at the urban site were −42.9 ± 1.1‰ and agreed well with previously published results. But at the coastal site bromomethane was substantially enriched in 13C by almost 10‰. Less pronounced differences were observed for chlorodifluoromethane, 1,1,1-trichloroethane and chloromethane. We suggest that these differences are related to the turnover of these compounds in ocean surface waters. Furthermore we report first carbon isotope ratios for iodomethane (−40.4‰ to −79.8‰), bromoform (−13.8‰ to 22.9‰), and other halocarbons

Serodetection of Ehrlichia canis amongst dogs in central Namibia

Ehrlichia canis is a major pathogen in dogs throughout Africa, yet it has not been reported in Namibia. The aim of this study was to determine the seroprevalence of canine ehrlichiosis in central Namibia using the ImmunoComb assay (Biogal, Galed Laboratories). The study included 76 dogs that presented to the Rhino Park Veterinary Clinic in the north-western suburb of Khomasdal, Windhoek, Namibia, as well as 30 stray dogs from the Windhoek branch of the Society for the Prevention of Cruelty to Animals. Of the 106 dogs tested, 53.8% were seropositive at titres > 1:80. Dogs that presented with symptoms of E. canis infection had a significantly higher seroprevalence (86.6%) compared with apparently healthy dogs (41.6%) (P = 0.00). Location of habitation was significant (P < 0.017), with a high percentage of dogs exposed to E. canis living in the northern or north-western part of Windhoek. As the first study to serologically establish E. canis as a major pathogen in dogs in central Namibia, it is notable that the highest proportion of seropositive dogs came from low-income areas. Further investigation is necessary to describe the ecology of this important tick-borne pathogen of companion animals in Namibia.Peer reviewedEntomology and Plant Patholog

Performance evaluation of Sentinel-1 derived DEMs using Copernicus DEM and ICESat-2

Digital elevation models (DEMs) hold a key role as the main input data for a large variety of applications as they provide an accurate representation of the Earth’s surface and its corresponding topographic parameters. Scientific applications require current, reliable and precise elevation information to be implemented in research to generate correct and valuable results. The performance and accuracy of DEMs must therefore be subject to quality assessment. Synthetic Aperture Radar (SAR) principles and methodology allow the generation of DEMs independent from day light and cloud coverage which act as a massively limiting interference factor in optical imagery. In 2014, a C-band radar mission Sentinel-1 launched within the Copernicus Programme of the European Space Agency (ESA), providing open access to radar data of regular global coverage (Braun 2021). The capabilities of DEM derivation from Sentinel-1 imagery are limited by parameters like slope and vegetation coverage as well as by the mission design itself as the large temporal baseline of two or more Sentinel-1 acquisitions hinders the stability of the interferometric phase and degrades the coherence. One crucial step in the analysis of SAR data and therefore optimizing its potential for DEM generation is the preprocessing of suitable interferometric data pairs, a complex workflow which includes coregistration, interferogram formation, phase unwrapping and terrain correction (Braun 2021). Within the scope of the TanDEM-X mission by the German Aerospace Center (DLR), consisting of two satellites (Terra-SAR-X and Tandem-X), a global DEM was generated from bistatic X-Band interferometric SAR products acquired between December 2010 and January 2015 (Rizzoli 2017). The TanDEM-X mission is the original source of the radar data from which the Copernicus DEM (COP-DEM) by ESA was derived. The COP-DEM is available in varying resolutions with the 30m resolution COP-DEM being openly accessible. The Ice, Cloud and land Elevation Satellite-2 (ICESat-2) mission by National Aeronautics and Space Administration (NASA) provides openly accessible data since October 2018. ICESat-2 data is a continuous, equally distributed, high resolution reference dataset and allows to independently evaluate the performance of SAR-derived DEMs. An Advanced Topographic Laser Altimeter System (ATLAS) on board of ICESat-2 fires shots of photons in 532nm wavelength separated into six beams arranged in three pairs. Each pair consists of a strong and a weak beam with an energy ratio of 4:1 (Neuenschwander und Pitts 2019). Terrain and canopy heights retrievals are stored in the ATL08 data product of ICESat-2 and computed for fixed 12x100m land segments in which a valid height value is given if a threshold of 50 signal photons is met in order to reliably represent the land surface within the segment. ICEsat-2 provides a large variety of parameters and flags to filter the data adapted to the needs of the research purpose. In this paper, we will generate several DEMs derived from Sentinel-1 data and perform a quality and accuracy evaluation. As reference data, we will use highly accurate ICESat-2 data points and two reference DEMs, TanDEM-X in 10m resolution and Copernicus DEM in 30m resolution. The main focus of this study is the correct processing and application of various parameter filter techniques of ICESat-2 data to provide accurate height reference data for the accuracy assessment of SAR-derived DEMs and the evaluation on DEM quality in consideration of different land cover types and topographic conditions regarding study sites from different continents

Comparative phase imaging of live cells by digital holographic microscopy and transport of intensity equation methods

We describe a microscopic setup implementing phase imaging by digital holographic microscopy (DHM) and transport of intensity equation (TIE) methods, which allows the results of both measurements to be quantitatively compared for either live cell or static samples. Digital holographic microscopy is a well-established method that provides robust phase reconstructions, but requires a sophisticated interferometric imaging system. TIE, on the other hand, is directly compatible with bright-field microscopy, but is more susceptible to noise artifacts. We present results comparing DHM and TIE on a custom-built microscope system that allows both techniques to be used on the same cells in rapid succession, thus permitting the comparison of the accuracy of both methods