Urban correction for the hydrological conditioning of the TanDEM-X DEM for the HydroSHEDS v2 database

The HydroSHEDS database provides global hydrographic data for hydrological applications. The second, refined version of the database is improved by using the highresolution TanDEM-X digital elevation model (DEM). In order to derive hydrologic data from the terrain, during the socalled pre-conditioning, the DEM is edited and ancillary layers are calculated. Prior steps of the editing include, among others like void and outlier correction and the derivation of a coastline and water body mask, an urban correction. When river networks are derived from a DEM, visible artificial structures can divert the streams as they intercept the natural course of the riverbed. Therefore, during the last step of the pre-conditioning, the urban correction aims to reduce such diversions caused by built-up structures

The new hydrographic HydroSHEDS database derived from the TanDEM-X DEM

Water-related applications such as hydrology, hydrodynamics, and flood inundation modelling crucially require fundamental hydrographic knowledge and monitoring as well as the tools and data that support mapping and analysis of natural river and drainage characteristics. Since its introduction in 2008, HydroSHEDS is a well-established database providing seamless hydrographic information to support hydro-ecological research and applications on a multitude of scales by offering standardized spatial units for hydrological assessments. Although being widely used, the Shuttle Radar Topography Mission (SRTM)-based version 1 of HydroSHEDS has important limitations, in particular in areas above 60° N latitude. A steadily increasing availability and accuracy of remote sensing data promotes the development of a second and refined version of HydroSHEDS, which is based on the globally consistent and highly accurate TanDEM-X dataset. In light of this, HydroSHEDS v2 is currently created in collaboration between the German Aerospace Center (DLR), McGill University, Confluvio Consulting and the World Wildlife Fund. Within the HydroSHEDS workflow, the pre-conditioning comprises multiple editing and correction steps to prepare the TanDEM-X DEM for hydrological applications. Compared to HydroSHEDS v1, the resulting hydrologically conditioned DEM ensures a more accurate derivation of HydroSHEDS v2 core products such as flow directions, river courses and catchment boundaries. By providing even clearer and more complete views of Earth’s waterways, the HydroSHEDS geospatial framework serves various management and decisionmaking applications beyond scientific research including aquatic ecosystem services, human health impacts and conservation planning

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

Monitoreo de servicios ecosistémicos en un observatorio de cafetales agroforestales. Recomendaciones para el sector cafetalero

Ocho años de estudio de la ecofisiología del café, a través de experimentación y de modelación y el monitoreo de los servicios del ecosistema (SE) en una gran finca cafetalera en Costa Rica, revelaron varias recomendaciones prácticas para los agricultores y los formuladores de políticas. El sistema de cultivo estudiado dentro de nuestro observatorio colaborativo (Coffee-Flux), corresponde a un sistema agroforestal (SAF) a base de café bajo la sombra de grandes árboles de Erythrina poeppigiana (16% de la cubierta del dosel). Una gran cantidad de SE y limitantes dependen de las propiedades locales del suelo (en este caso Andisoles), especialmente de la erosión/infiltración, el agua/carbono y la capacidad de almacenamiento de nutrientes. Por lo tanto, para la evaluación de SE, el tipo de suelo es crucial. Una densidad adecuada de árboles de sombra (bastante baja aquí por la condición de libre crecimiento), redujo la severidad de las enfermedades de las hojas con la posibilidad de reducir el uso de plaguicidas y fungicidas. Un inventario simple del área basal en el collar de las plantas de café permitió estimar la biomasa subterránea y la edad promedio de la plantación, para juzgar su valor de mercado y decidir cuándo reemplazarla. Las fincas de café probablemente estén mucho más cerca de la neutralidad de C que lo indicado en el protocolo actual de C-neutralidad, que solo considera árboles de sombra, no los cafetos ni el suelo. Se proponen evaluaciones más completas, que ncluyen árboles, café, hojarasca, suelo y raíces en el balance C del SAF. Los árboles de sombra ofrecen muchos SE si se gestionan adecuadamente en el contexto local. En comparación con las condiciones a pleno sol, los árboles de sombra pueden (i) reducir la erosión laminar en un factor de 2; (ii) aumentar la fijación de N y el % de N reciclado en el sistema, reduciendo así los requisitos de fertilizantes; (iii) reducir la severidad de enfermedades de las hojas; (iv) aumentar el secuestro de C; (v) mejorar el microclima y (vi) reducir sustancialmente los efectos del cambio climático. En nuestro estudio de caso, no se encontró ningún efecto negativo sobre el rendimiento del café

Towards the global HydroSHEDS-X dataset: DEM pre-processing for the derivation of rivers and catchments

The increased availability and accuracy of recent remote sensing data accelerates the development of data products for hydrological modelling. Most hydrological models rely on the accurate representation of the Earth’s terrestrial surface including all waterways from small mountain streams to great lowland rivers in order to compute discharge. In light of this, the creation of the HydroSHEDS-X database, which is currently developed in an international collaborative project between the German Aerospace Center (DLR), McGill University, Confluvio Consulting, and the World Wildlife Fund, represents a new source for global digital hydrographic information. HydroSHEDS-X is the second version of the well-established HydroSHEDS database, which is freely available at https://hydrosheds.org. While the first version was derived from the digital elevation model (DEM) of the Shuttle Radar Topography Mission (SRTM), the foundation of HydroSHEDS-X are the elevation data of the TanDEM-X mission (TerraSAR-X add-on for Digital Elevation Measurement), which was created in partnership between the German Aerospace Center (DLR) and Airbus. HydroSHEDS-X benefits from the higher resolution of the underlying TanDEM-X DEM given its resolution of 0.4 arc-seconds worldwide including regions with latitudes higher than 60° North, which are not covered by the SRTM DEM. Details of this high-resolution DEM are preserved in the HydroSHEDS-X dataset by applying enhanced pre-processing techniques. This pre-processing of the elevation data comprises DEM infills for invalid and unreliable areas, an automatic coastline delineation with manual quality control, the generation of an open water mask, and the reduction that are caused by distortions of vegetation and settlements. The pre-processed DEM is further treated at a resolution of 3 arc-seconds to obtain a hydrologically conditioned DEM. Derived from this hydrologically conditioned version of the DEM, the HydroSHEDS-X core products comprise flow direction and flow accumulation maps as gridded datasets. The core products are complemented with secondary information on river networks, lake shorelines, catchment boundaries, and their hydro-environmental attributes in vector format. Finally, the database is completed with associated products. Available in standardized spatial units and at multiple scales starting from a resolution of 3 arc-seconds, HydroSHEDS-X is fully compatible with its original version and thus provides a consistent and easy-to-use database for hydrological applications from local to global scale. The main release of HydroSHEDS-X is scheduled for 2022 under a free license

Neue Projekte im DLR Neustrelitz – Motivation für zukünftige Archivierung

Presentation of new Projects of DLR Neustrelitz and their resulting requirements for archiving of large data massiv

Improved hydrologic conditioning of the TanDEM-X dataset for HydroSHEDS v2.

HydroSHEDS is a well-established database containing global hydrographic information. Although being widely used, the SRTM-based version 1 of HydroSHEDS has important limitations, in particular in areas above 60° N latitude. The coverage of this region is of low quality because no underpinning SRTM elevation data were available. As most hydrological models require topographic information and hydrographic data in terms of stream networks or catchment boundaries, the increased availability of accurate remote sensing data promotes the development of a second and refined version of the HydroSHEDS database. For this reason, HydroSHEDS v2 is currently created in collaboration between the German Aerospace Center (DLR), McGill University, Confluvio Consulting and the World Wildlife Fund. Foundation of HydroSHEDS v2 is the digital elevation model (DEM) of the TanDEM-X mission (TerraSAR-X add-on for Digital Elevation Measurement). This 0.4 arc-second resolution DEM with global coverage of land surfaces was created in partnership between DLR and Airbus Defence and Space. Enhanced pre-processing techniques are applied to preserve details of the high-resolution DEM in its hydrologically conditioned version. These pre-processing steps include an infill of invalid and unreliable elevation values, an automatic coastline delineation refined with manual corrections, an AI-based water detection algorithm, and a modification of elevation data in urban and vegetated areas for improved evaluation of the flow of water. Additionally, experiences and preliminary results from processing the water body mask at global scale are outlined. The hydrologically pre-conditioned DEM and the water body mask derived from the TanDEM-X dataset are in the subsequent steps further processed with refined hydrological optimization and correction algorithms to derive flow direction and flow accumulation maps. These gridded datasets are the core products of HydroSHEDS v2 and will be complemented with secondary information on river networks, lake shorelines, catchment boundaries, and their hydro-environmental attributes in vector format. The main release of HydroSHEDS v2 is scheduled for 2023 under a free license

Influence of Treadmill Design on Gait: Does Treadmill Size Affect Muscle Activation Amplitude? A Musculoskeletal Calculation With Individualized Input Parameters of Gait Analysis

With increasing age, gait changes often occur, leading to mobility problems and thus a higher risk of falling. Interest in training at home or at retirement homes has led to the development of “mobile treadmills.” A difference in treadmill surface length may influence walking parameters (i.e., step length) and therefore may affect muscle activation. This led to the question: Does the treadmill size affect the muscle activation, i.e., with the length of the walking surface. The study aimed to investigate the influence of treadmill size, i.e., length of the walking surface, on gait pattern and to determine differences in the amplitude of muscle activation using a participant-specific musculoskeletal model (AnyBody Technology A/S, Aalborg, Denmark). For a prospective, randomized study gait parameters were collected from 47 healthy participants (aged 50.19 ± 20.58 years) while walking on two different treadmills, a small mobile treadmill (walking surface length 100 cm) and a conventional treadmill (walking surface length 150 cm), at their preferred speed, 2 km/h, and 4 km/h. Muscle activation amplitude patterns were similar between treadmills (M. gastrocnemius medialis: rmean = 0.94, M. gastrocnemius lateralis: rmean = 0.92, M. gluteus medius rmean = 0.90, M. gluteus minimus rmean = 0.94). However, the gait analysis showed a decreased preferred velocity (p < 0.001, z = 4.54), reduced stride length (preferred velocity: p = 0.03, z = −2.17; 2 km/h: p = 0.36, z = 2.10; 4 km/h: p = 0.006, z = 2.76), shorter stride time (2 km/h: p < 0.001, z = 4.65; 4 km/h: p < 0.001, z = 4.15), and higher cadence (2 km/h: p < 0.001, z = −4.20; 4 km/h: p = 0.029, z = −2.18) on the mobile treadmill than on the conventional treadmill. Our observations suggest that the treadmill design (e.g., a 50 cm difference in walking surface length) may not influence muscle activity amplitude during walking. However, the design of the treadmill may influence gait characteristics (e.g., stride length, cadence) of walking

Searching for reliable components of Anchoring and Adjustment

In this study, we try to map people's adjustment from anchors

The new hydrographic HydroSHEDS database derived from the TanDEM-X DEM.

The HydroSHEDS database provides seamless hydrographic data to support hydro-ecological research and applications on a regional to global scale. A steadily increasing availability and accuracy of remote sensing data promotes the development of a second and refined version of HydroSHEDS, which is based on the TanDEM-X dataset. To derive hydrographic information from the topographic data, the TanDEM-X digital elevation model (DEM) requires editing, which is summarized in the so-called hydrologic pre-conditioning. The processing steps include an infill of voids and outliers in the DEM and the delineation of a global high-resolution coastline. Furthermore, a global water mask is generated to edit rough and noisy appearing open water surfaces in the DEM. An urban correction layer is calculated to reduce distortions in river flow paths due to built-up areas. Within the HydroSHEDS workflow, the pre-conditioning will be complemented with refined hydrological optimization and correction algorithms. Compared to HydroSHEDS v1, the resulting hydrologically conditioned DEM ensures a more accurate derivation of flow direction and flow accumulation maps