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In recent years, the midlatitudes are characterized by more intense heatwaves in summer and sometimes severe cold spells in winter that might emanate from changes in atmospheric circulation, including synoptic‐scale and planetary wave activity in the midlatitudes. In this study, we investigate the heat and momentum exchange between the mean flow and atmospheric waves in the North Atlantic sector and adjacent continents by means of the physically consistent Eliassen–Palm flux diagnostics applied to reanalysis and forced climate model data. In the long‐term mean, momentum is transferred from the mean flow to atmospheric waves in the northwest Atlantic region, where cyclogenesis prevails. Further downstream over Europe, eddy fluxes return momentum to the mean flow, sustaining the jet stream against friction. A global climate model is able to reproduce this pattern with high accuracy. Atmospheric variability related to atmospheric wave activity is much more expressed at the intraseasonal rather than the interannual time‐scale. Over the last 40 years, reanalyses reveal a northward shift of the jet stream and a weakening of intraseasonal weather variability related to synoptic‐scale and planetary wave activity. This pertains to the winter and summer seasons, especially over central Europe, and correlates with changes in the North Atlantic Oscillation as well as regional temperature and precipitation. A very similar phenomenon is found in a climate model simulation with business‐as‐usual scenario, suggesting an anthropogenic trigger in the weakening of intraseasonal weather variability in the midlatitudes.
The alarming increase in the magnitude and spatiotemporal patterns of changes in composition, structure and function of forest ecosystems during recent years calls for enhanced cross-border mitigation and adaption measures, which strongly entail intensified research to understand the underlying processes in the ecosystems as well as their dynamics. Remote sensing data and methods are nowadays the main complementary sources of synoptic, up-to-date and objective information to support field observations in forest ecology. In particular, analysis of three-dimensional (3D) remote sensing data is regarded as an appropriate complement, since they are hypothesized to resemble the 3D character of most forest attributes. Following their use in various small-scale forest structural analyses over the past two decades, these sources of data are now on their way to be integrated in novel applications in fields like citizen science, environmental impact assessment, forest fire analysis, and biodiversity assessment in remote areas. These and a number of other novel applications provide valuable material for the Forests special issue “3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function”, which shows the promising future of these technologies and improves our understanding of the potentials and challenges of 3D remote sensing in practical forest ecology worldwide.
Estimating penetration-related X-band InSAR elevation bias: a study over the Greenland ice sheet
(2019)
Accelerating melt on the Greenland ice sheet leads to dramatic changes at a global scale. Especially in the last decades, not only the monitoring, but also the quantification of these changes has gained considerably in importance. In this context, Interferometric Synthetic Aperture Radar (InSAR) systems complement existing data sources by their capability to acquire 3D information at high spatial resolution over large areas independent of weather conditions and illumination. However, penetration of the SAR signals into the snow and ice surface leads to a bias in measured height, which has to be corrected to obtain accurate elevation data. Therefore, this study purposes an easy transferable pixel-based approach for X-band penetration-related elevation bias estimation based on single-pass interferometric coherence and backscatter intensity which was performed at two test sites on the Northern Greenland ice sheet. In particular, the penetration bias was estimated using a multiple linear regression model based on TanDEM-X InSAR data and IceBridge laser-altimeter measurements to correct TanDEM-X Digital Elevation Model (DEM) scenes. Validation efforts yielded good agreement between observations and estimations with a coefficient of determination of R\(^2\) = 68% and an RMSE of 0.68 m. Furthermore, the study demonstrates the benefits of X-band penetration bias estimation within the application context of ice sheet elevation change detection.
Invasive plant species are major threats to biodiversity. They can be identified and monitored by means of high spatial resolution remote sensing imagery. This study aimed to test the potential of multiple very high-resolution (VHR) optical multispectral and stereo imageries (VHRSI) at spatial resolutions of 1.5 and 5 m to quantify the presence of the invasive lantana (Lantana camara L.) and predict its distribution at large spatial scale using medium-resolution fractional cover analysis. We created initial training data for fractional cover analysis by classifying smaller extent VHR data (SPOT-6 and RapidEye) along with three dimensional (3D) VHRSI derived digital surface model (DSM) datasets. We modelled the statistical relationship between fractional cover and spectral reflectance for a VHR subset of the study area located in the Himalayan region of India, and finally predicted the fractional cover of lantana based on the spectral reflectance of Landsat-8 imagery of a larger spatial extent. We classified SPOT-6 and RapidEye data and used the outputs as training data to create continuous field layers of Landsat-8 imagery. The area outside the overlapping region was predicted by fractional cover analysis due to the larger extent of Landsat-8 imagery compared with VHR datasets. Results showed clear discrimination of understory lantana from upperstory vegetation with 87.38% (for SPOT-6), and 85.27% (for RapidEye) overall accuracy due to the presence of additional VHRSI derived DSM information. Independent validation for lantana fractional cover estimated root-mean-square errors (RMSE) of 11.8% (for RapidEye) and 7.22% (for SPOT-6), and R\(^2\) values of 0.85 and 0.92 for RapidEye (5 m) and SPOT-6 (1.5 m), respectively. Results suggested an increase in predictive accuracy of lantana within forest areas along with increase in the spatial resolution for the same Landsat-8 imagery. The variance explained at 1.5 m spatial resolution to predict lantana was 64.37%, whereas it decreased by up to 37.96% in the case of 5 m spatial resolution data. This study revealed the high potential of combining small extent VHR and VHRSI- derived 3D optical data with larger extent, freely available satellite data for identification and mapping of invasive species in mountainous forests and remote regions.
Peatlands located on slopes (herein called slope bogs) are typical landscape units in the Hunsrueck, a low mountain range in Southwestern Germany. The pathways of the water feeding the slope bogs have not yet been documented and analyzed. The identification of the different mechanisms allowing these peatlands to originate and survive requires a better understanding of the subsurface lithology and hydrogeology. Hence, we applied a multi-method approach to two case study sites in order to characterize the subsurface lithology and to image the variable spatio-temporal hydrological conditions. The combination of Electrical Resistivity Tomography (ERT) and an ERT-Monitoring and Ground Penetrating Radar (GPR), in conjunction with direct methods and data (borehole drilling and meteorological data), allowed us to gain deeper insights into the subsurface characteristics and dynamics of the peatlands and their catchment area. The precipitation influences the hydrology of the peatlands as well as the interflow in the subsurface. Especially, the geoelectrical monitoring data, in combination with the precipitation and temperature data, indicate that there are several forces driving the hydrology and hydrogeology of the peatlands. While the water content of the uppermost layers changes with the weather conditions, the bottom layer seems to be more stable and changes to a lesser extent. At the selected case study sites, small differences in subsurface properties can have a huge impact on the subsurface hydrogeology and the water paths. Based on the collected data, conceptual models have been deduced for the two case study sites.
Via providing various ecosystem services, the old-growth Hyrcanian forests play a crucial role in the environment and anthropogenic aspects of Iran and beyond. The amount of growing stock volume (GSV) is a forest biophysical parameter with great importance in issues like economy, environmental protection, and adaptation to climate change. Thus, accurate and unbiased estimation of GSV is also crucial to be pursued across the Hyrcanian. Our goal was to investigate the potential of ALOS-2 and Sentinel-1's polarimetric features in combination with Sentinel-2 multi-spectral features for the GSV estimation in a portion of heterogeneously-structured and mountainous Hyrcanian forests. We used five different kernels by the support vector regression (nu-SVR) for the GSV estimation. Because each kernel differently models the parameters, we separately selected features for each kernel by a binary genetic algorithm (GA). We simultaneously optimized R\(^2\) and RMSE in a suggested GA fitness function. We calculated R\(^2\), RMSE to evaluate the models. We additionally calculated the standard deviation of validation metrics to estimate the model's stability. Also for models over-fitting or under-fitting analysis, we used mean difference (MD) index. The results suggested the use of polynomial kernel as the final model. Despite multiple methodical challenges raised from the composition and structure of the study site, we conclude that the combined use of polarimetric features (both dual and full) with spectral bands and indices can improve the GSV estimation over mixed broadleaf forests. This was partially supported by the use of proposed evaluation criterion within the GA, which helped to avoid the curse of dimensionality for the applied SVR and lowest over estimation or under estimation.
Advances in remote inventory and analysis of forest resources during the last decade have reached a level to be now considered as a crucial complement, if not a surrogate, to the long-existing field-based methods. This is mostly reflected in not only the use of multiple-band new active and passive remote sensing data for forest inventory, but also in the methodic and algorithmic developments and/or adoptions that aim at maximizing the predictive or calibration performances, thereby minimizing both random and systematic errors, in particular for multi-scale spatial domains. With this in mind, this editorial note wraps up the recently-published Remote Sensing special issue “Remote Sensing-Based Forest Inventories from Landscape to Global Scale”, which hosted a set of state-of-the-art experiments on remotely sensed inventory of forest resources conducted by a number of prominent researchers worldwide.
Human health is known to be affected by the physical environment. Various environmental influences have been identified to benefit or challenge people's physical condition. Their heterogeneous distribution in space results in unequal burdens depending on the place of living. In addition, since societal groups tend to also show patterns of segregation, this leads to unequal exposures depending on social status. In this context, environmental justice research examines how certain social groups are more affected by such exposures. Yet, analyses of this per se spatial phenomenon are oftentimes criticized for using “essentially aspatial” data or methods which neglect local spatial patterns by aggregating environmental conditions over large areas. Recent technological and methodological developments in satellite remote sensing have proven to provide highly detailed information on environmental conditions. This narrative review therefore discusses known influences of the urban environment on human health and presents spatial data and applications for analyzing these influences. Furthermore, it is discussed how geographic data are used in general and in the interdisciplinary research field of environmental justice in particular. These considerations include the modifiable areal unit problem and ecological fallacy. In this review we argue that modern earth observation data can represent an important data source for research on environmental justice and health. Especially due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics. As a future perspective, ongoing earth observation missions, as well as processing architectures, ensure data availability and applicability of ’big earth data’ for future environmental justice analyses.
Projected climate changes for the 21st century may cause great uncertainties on the hydrology of a river basin. This study explored the impacts of climate change on the water balance and hydrological regime of the Jhelum River Basin using the Soil and Water Assessment Tool (SWAT). Two downscaling methods (SDSM, Statistical Downscaling Model and LARS-WG, Long Ashton Research Station Weather Generator), three Global Circulation Models (GCMs), and two representative concentration pathways (RCP4.5 and RCP8.5) for three future periods (2030s, 2050s, and 2090s) were used to assess the climate change impacts on flow regimes. The results exhibited that both downscaling methods suggested an increase in annual streamflow over the river basin. There is generally an increasing trend of winter and autumn discharge, whereas it is complicated for summer and spring to conclude if the trend is increasing or decreasing depending on the downscaling methods. Therefore, the uncertainty associated with the downscaling of climate simulation needs to consider, for the best estimate, the impact of climate change, with its uncertainty, on a particular basin. The study also resulted that water yield and evapotranspiration in the eastern part of the basin (sub-basins at high elevation) would be most affected by climate change. The outcomes of this study would be useful for providing guidance in water management and planning for the river basin under climate change.
Diese Arbeit stellt die Ergebnisse der stratigraphischen und tektonischen Aufnahme des Blattes 5827 Maßbach vor. Sie erfolgte im Rahmen der geologischen Landesaufnahme von Bayern 1:25.000 sowie im Auftrag des Bayerischen Landesamts für Umwelt und beruht auf einer geologischen Detailkartierung im Maßstab 1:10.000. Die wesentlichen Ergebnisse sind folglich in der Geologischen Karte 1:25.000 und in der Strukturkarte 1:50.000 dargestellt.
Zur Aufgabenstellung gehörten ebenfalls eine moderne Erfassung und Darstellung der Schichtenfolge unter stratigraphischen und faziellen Gesichtspunkten sowie die Aufnahme und Interpretation geologischer Strukturen und deren Einbindung in den regionalen Rahmen (Anlage 7). Dieser Arbeit kommt somit nicht nur akademisches Interesse zu. Vielmehr ist sie auch für angewandte Fachbereiche wesentlich: u.a. für Hydrogeologie, Geothermie oder für Fragen der Raumplanung.
Das Kartenblatt 5827 Maßbach liegt im nordöstlichen Unterfranken im Norden Bayerns. Die nächstgrößere Stadt, südlich des Blattgebietes, ist Schweinfurt. Das Gebiet zeigt einen Ausschnitt des südwestdeutschen Schichtstufenlandes innerhalb der Südwestdeutschen Großscholle sensu CARLÉ (1955). Geomorphologen rechnen es der Hochfläche der „Schweinfurter Rhön“ zu. Ein naturräumlicher Überblick über Geographie, Geologie, Hydrogeologie, Rohstoffgeologie und Bodenkunde sowie ein erdgeschichtlicher Abriss werden im ersten Teil der Arbeit (S. 2–15) gegeben.
Die Kartierung erfolgte als Lesesteinkartierung; denn die Aufschlussverhältnisse waren schlecht. Auch existieren nur wenige auswertbare Bohrungen. Vor diesem Hintergrund stellt der zweite Teil der Arbeit die zu Tage ausstreichende mesozoische Schichtenfolge vor (S.16–76). Die Schichtenfolge gehört ausschließlich in die Trias, reicht vom Unteren Muschelkalk bis zum Unteren Gipskeuper und umfasst etwa 270 bis 280 Meter. Hinzu kommen verschiedene quartäre Sedimente geringer Mächtigkeit.
Der dritte Teil der Arbeit (S. 77–95) befasst sich mit den Lagerungsverhältnissen und der tektonischen Zergliederung des Gebietes. Das tektonische Relief auf Blatt 5827 Maßbach misst etwa 260–270 m. Prägendes Element ist der Kissingen–Haßfurter Sattel, dessen Sattelachse das Blattgebiet von NW nach SE quert. Im SW–Quadranten ist die in Südwestdeutschland bedeutsame Kissingen–Haßfurter–Störungszone wirksam
Im regionalen Rahmen verbinden sich eine Vielzahl von nachgewiesenen tektonischen Elementen zu sich überlagernden tektonischen Strukturen. Deren Ausgestaltung verlief mehrphasig und sie erhielten ihre heute bestehende Form wohl durch die Fernwirkung der alpidischen Orogenese. Die Anlage der tektonischen Hauptelemente hingegen reicht wahrscheinlich bis in die ausgehende variszidische Gebirgsbildung zurück. Die zusammen-fassende Analyse und Darstellung der Ergebnisse führt in dieser Arbeit zur Einarbeitung des Blattes 5827 Maßbach in den regionalen stratigraphischen wie tektonischen Rahmen der umliegenden Blätter der GK 25.