scholarly journals High-resolution inventory to capture glacier disintegration in the Austrian Silvretta

2021 ◽  
Author(s):  
Andrea Fischer ◽  
Bernd Seiser ◽  
Kay Helfricht ◽  
Martin Stocker-Waldhuber
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Ice Age ◽  
Surface Elevation ◽  
Glacier Changes ◽  
Wide Range ◽  
Elevation Data ◽  
Glacier Ice ◽  
Geodetic Mass Balance

Abstract. Eastern Alpine glaciers have been receding since the LIA maximum, but the majority of glacier margins could be delineated unambiguously for the last Austrian glacier inventories. Even debris-covered termini, changes in slope, colour or the position of englacial streams enabled at least an in situ survey of glacier outlines. Today the outlines of totally debris-covered glacier ice are fuzzy and raise the theoretical discussion if these glaciogenic features are still glaciers and should be part of the respective inventory – or part of an inventory of transient cryogenic landforms. A new high-resolution glacier inventory (area and surface elevation) was compiled for the years 2017 and 2018 to quantify glacier changes for the Austrian Silvretta region in full. Glacier outlines were mapped manually, based on orthophotos and elevation models and patterns of volume change of 1 to 0.5 m spatial resolution. The vertical accuracy of the DEMs generated from 6 to 8 LiDAR points per m2 is in the order of centimetres. calculated in relation to the previous inventories dating from 2004/2006 (LiDAR), 2002, 1969 (photogrammetry) and to the Little Ice Age maximum extent (moraines). Between 2004/06 and 2017/2018, the 46 glaciers of the Austrian Silvretta lost −29 ± 4 % of their area and now cover 13.1 ± 0.4 km2. This is only 32 ± 2 % of their LIA extent of 40.9 ± 4.1 km2. The area change rate increased from −0.6 %/year (1969–2002) to −2.4 %/year (2004/06–2017/18). The annual geodetic mass balance showed a loss increasing from −0.2 ± 0.1 m w.e./year (1969–2002) to –0.8 m ±0.1 w.e./year (2004/06–2017/18) with an interim peak in 2002–2004/06 at −1.5 ± 0.7 m w.e./year. Identifying the glacier outlines offers a wide range of possible interpretations of former glaciers that have evolved into small and now totally debris-covered cryogenic geomorphological structures. Only the patterns and amounts of volume changes allow us to estimate the area of the buried glacier remnants. To keep track of the buried ice and its fate, and to distinguish increasing debris cover from ice loss, we recommend inventory repeat frequencies of three to five years and surface elevation data with a spatial resolution of one metre.

scholarly journals High-resolution inventory to capture glacier disintegration in the Austrian Silvretta

2021 ◽  
Vol 15 (10) ◽  
pp. 4637-4654
Author(s):  
Andrea Fischer ◽  
Gabriele Schwaizer ◽  
Bernd Seiser ◽  
Kay Helfricht ◽  
Martin Stocker-Waldhuber
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Volume Change ◽  
Ice Age ◽  
Glacier Inventory ◽  
Current State ◽  
Digital Elevation ◽  
Wide Range ◽  
Elevation Data ◽  
Geodetic Mass Balance

Abstract. A new high-resolution glacier inventory captures the rapid decay of the glaciers in the Austrian Silvretta for the years 2017 and 2018. Identifying the glacier outlines offers a wide range of possible interpretations of glaciers that have evolved into small and now totally debris-covered cryogenic structures. In previous inventories, a high proportion of active bare ice allowed a clear delineation of the glacier margins even by optical imagery. In contrast, in the current state of the glacier only the patterns and amounts of volume change allow us to estimate the area of the buried glacier remnants. We mapped the glacier outlines manually based on lidar elevation models and patterns of volume change at 1 to 0.5 m spatial resolution. The vertical accuracy of the digital elevation models (DEMs) generated from six to eight lidar points per square metre is of the order of centimetres. Between 2004/2006 and 2017/2018, the 46 glaciers of the Austrian Silvretta lost −29 ± 4 % of their area and now cover 13.1 ± 0.4 km2. This is only 32 ± 2 % of their Little Ice Age (LIA) extent of 40.9 ± 4.1 km2. The area change rate increased from 0.6 %/yr (1969–2002) to −2.4 %/yr (2004/2006–2017/2018). The Sentinel-2-based glacier inventory of 2018 deviates by just 1 % of the area. The annual geodetic mass balance referring to the area at the beginning of the period showed a loss increasing from −0.2 ± 0.1 m w.e./yr (1969–2002) to −0.8 ± 0.1 m w.e./yr (2004/2006–2017/2018) with an interim peak in 2002–2004/2006 of −1.5 ± 0.7 m w.e./yr. To keep track of the buried ice and its fate and to distinguish increasing debris cover from ice loss, we recommend inventory repeat frequencies of 3 to 5 years and surface elevation data with a spatial resolution of 1 m.

scholarly journals Urban Distributed Acoustic Sensing Using In-Situ Fibre Beneath Bern, Switzerland

2020 ◽  
Author(s):  
Krystyna Smolinski ◽  
Patrick Paitz ◽  
Daniel Bowden ◽  
Pascal Edme ◽  
Felix Kugler ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Seismic Waves ◽  
Velocity Structure ◽  
Road Traffic ◽  
Hazard Analysis ◽  
Noise Sources ◽  
Acoustic Sensing ◽  
Wide Range ◽  
Distributed Acoustic Sensing

<p>Anticipating the risks natural hazards pose to an urban environment requires an understanding of the shallow Earth structure of the region. While urban infrastructure often hinders the deployment of a traditional seismic array, Distributed Acoustic Sensing (DAS) technology facilitates the use of existing telecommunication fibre-optic cables for seismic observation, with spatial resolution down to the metre scale.</p><p>Through collaboration with the SWITCH foundation, we were able to use existing, in-situ fibres beneath Bern, Switzerland for seismic data acquisition over two weeks, covering a distance of 6 km with a spatial resolution of 2 m. This allowed for not only real-time visualisation of anthropogenic noise sources (e.g. road traffic), but also of the propagation of resulting seismic waves.</p><p>Data is analysed in the time and frequency domain to explore the range of signals captured and to assess the consistency of data quality along the cable. The local velocity structure can be constrained using both noise correlations and deterministic signals excited by traffic.</p><p>Initial results reveal the ability of DAS to capture signals over a wide range of frequencies and distances, and show promise for utilising urban DAS data to perform urban seismic tomography and hazard analysis.</p>

scholarly journals High-Resolution Sea Surface Temperature and Salinity in the Global Ocean from Raw Satellite Data

2019 ◽  
Vol 11 (19) ◽  
pp. 2191 ◽  
Author(s):  
Encarni Medina-Lopez ◽  
Leonardo Ureña-Fuentes
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Satellite Data ◽  
Google Earth ◽  
Sea Surface ◽  
Global Ocean ◽  
The Neural Network ◽  
Wide Range ◽  
Sentinel 2

The aim of this work is to obtain high-resolution values of sea surface salinity (SSS) and temperature (SST) in the global ocean by using raw satellite data (i.e., without any band data pre-processing or atmospheric correction). Sentinel-2 Level 1-C Top of Atmosphere (TOA) reflectance data is used to obtain accurate SSS and SST information. A deep neural network is built to link the band information with in situ data from different buoys, vessels, drifters, and other platforms around the world. The neural network used in this paper includes shortcuts, providing an improved performance compared with the equivalent feed-forward architecture. The in situ information used as input for the network has been obtained from the Copernicus Marine In situ Service. Sentinel-2 platform-centred band data has been processed using Google Earth Engine in areas of 100 m × 100 m. Accurate salinity values are estimated for the first time independently of temperature. Salinity results rely only on direct satellite observations, although it presented a clear dependency on temperature ranges. Results show the neural network has good interpolation and extrapolation capabilities. Test results present correlation coefficients of 82 % and 84 % for salinity and temperature, respectively. The most common error for both SST and SSS is 0.4 ∘ C and 0 . 4 PSU. The sensitivity analysis shows that outliers are present in areas where the number of observations is very low. The network is finally applied over a complete Sentinel-2 tile, presenting sensible patterns for river-sea interaction, as well as seasonal variations. The methodology presented here is relevant for detailed coastal and oceanographic applications, reducing the time for data pre-processing, and it is applicable to a wide range of satellites, as the information is directly obtained from TOA data.

scholarly journals Accelerating retreat and high-elevation thinning of glaciers in central Spitsbergen

2016 ◽  
Vol 10 (3) ◽  
pp. 1317-1329 ◽  
Author(s):  
Jakub Małecki
Keyword(s):  
Little Ice Age ◽  
High Elevation ◽  
Comprehensive Analysis ◽  
Ice Age ◽  
The Arctic ◽  
Digital Elevation ◽  
Glacier Changes ◽  
The Mean ◽  
Geodetic Mass Balance ◽  
The 1960S

Abstract. Svalbard is a heavily glacier-covered archipelago in the Arctic. Dickson Land (DL), in the central part of the largest island, Spitsbergen, is relatively arid and, as a result, glaciers there are relatively small and restricted mostly to valleys and cirques. This study presents a comprehensive analysis of glacier changes in DL based on inventories compiled from topographic maps and digital elevation models for the Little Ice Age (LIA) maximum, the 1960s, 1990, and 2009/2011. Total glacier area has decreased by  ∼ 38 % since the LIA maximum, and front retreat increased over the study period. Recently, most of the local glaciers have been consistently thinning in all elevation bands, in contrast to larger Svalbard ice masses which remain closer to balance. The mean 1990–2009/2011 geodetic mass balance of glaciers in DL is among the most negative from the Svalbard regional means known from the literature.

Combining in situ observations and high resolution VENμS data to monitor temperate deciduous shrub and tree phenology

2020 ◽  
Author(s):  
Alison Donnelly ◽  
Rong Yu
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Carbon Budget ◽  
Vegetation Index ◽  
Return Time ◽  
Small Scale ◽  
Spatial Coverage ◽  
Temperate Deciduous

<p>Direct in situ phenological observations of co-located trees and shrubs help characterize the phenological profile of ecosystems, such as, temperate deciduous forests. Accurate determination of the start and end of the growing season is necessary to define the active carbon uptake period for use in reliable carbon budget calculations. However, due to the resource intensive nature of recording in situ phenology the spatial coverage of sampling is often limited. In recent decades, the use of freely available satellite-derived phenology products to monitor ‘green-up’ at the landscape scale have become commonplace. Although these data sets are widely available they either have (i) high temporal resolution but low spatial resolution, such as, MODIS (daily return time; 250m) or (ii) low temporal resolution but high spatial resolution, such as, Landsat (16-day return time; 30m). However, the recently (2017) launched VENμS (Vegetation and Environment monitoring on a New Micro-Satellite) satellite combines both high temporal (two-day return time) and spatial (5-10m) resolution at a local scale thus providing an opportunity for small scale comparison of a range of phenometrics. The next challenge is to determine what in situ phenophase corresponds to the satellite-derived phenology. Our study site is a temperate deciduous woodlot on the campus of the University of Wisconsin-Milwaukee, USA, where we monitored in situ phenology on a range of (5) native (N) and (3) non-native invasive (NNI) shrub species, and (6) tree species for a 3-year period (2017-2019) to determine the timing and duration of key spring (bud-open, leaf-out, full-leaf unfolded) and autumn (leaf color, leaf fall) phenophases. The monitoring campaign coincided with the 2-day return time of VENμS to enable direct comparison with the satellite data. The shrubs leafed out before the trees and the NNIs, in particular, remained green well into the autumn season when the trees were leafless. The next step will be to determine what exact in situ phenophses correspond to NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived start, peak and end of season from MODIS and VENμS data. In addition, we will determine if VENμS can detect differences in phenological profile between N and NNI shrubs at seasonal extremes. We anticipate that the high resolution VENμS data will increase the accuracy of phenological determination which could help improve carbon budget determination and inform forest management and conservation plans.</p>

Development of Wet Environmental TEM (Wet-ETEM) for In Situ Studies of Liquid-Catalyst Reactions on the Nanoscale

2002 ◽  
Vol 8 (1) ◽  
pp. 21-28 ◽  
Author(s):  
Pratibha L. Gai
Keyword(s):  
Biological Sciences ◽  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
High Resolution ◽  
Transmission Electron ◽  
Wide Range ◽  
Environmental Tem ◽  
Nanoscale Imaging ◽  
Solution Gas

We present the development of in situ wet environmental transmission electron microscopy (Wet-ETEM) for direct probing of controlled liquid–catalyst reactions at operating temperatures on the nanoscale. The first nanoscale imaging and electron diffraction of dynamic liquid hydrogenation and polymerization reactions in the manufacture of polyamides reported here opens up new opportunities for high resolution studies of a wide range of solution–solid and solution–gas–solid reactions in the chemical and biological sciences.

scholarly journals Sensitivity of ensemble Lagrangian reconstructions to assimilated wind time step resolution

2009 ◽  
Vol 9 (2) ◽  
pp. 8619-8633
Author(s):  
I. Pisso ◽  
V. Marécal ◽  
B. Legras ◽  
G. Berthet
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Time Resolution ◽  
Wind Fields ◽  
Time Step ◽  
Coarse Resolution ◽  
Temporal And Spatial ◽  
Atmospheric Tracers

Abstract. The aim of this study is to define the optimal temporal and spatial resolution required for accurate offline diffusive Lagrangian reconstructions of high resolution in-situ tracers measurements based on meteorological wind fields and on coarse resolution 3-D tracer distributions. Increasing the time resolution of the advecting winds from three to one hour intervals has a modest impact on diffusive reconstructions in the case studied. This result is discussed in terms of the effect on the geometry of transported clouds of points in order to set out a method to assess the effect of meteorological flow on the transport of atmospheric tracers.

scholarly journals New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture

2020 ◽  
Vol 12 (7) ◽  
pp. 1119 ◽  
Author(s):  
Jovan Kovačević ◽  
Željko Cvijetinović ◽  
Nikola Stančić ◽  
Nenad Brodić ◽  
Dragan Mihajlović
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Random Forest ◽  
Spatial Resolution ◽  
Surface Soil ◽  
Initial Step ◽  
Surface Soil Moisture ◽  
In Situ Data ◽  
Random Forest Models

ESA CCI SM products have provided remotely-sensed surface soil moisture (SSM) content with the best spatial and temporal coverage thus far, although its output spatial resolution of 25 km is too coarse for many regional and local applications. The downscaling methodology presented in this paper improves ESA CCI SM spatial resolution to 1 km using two-step approach. The first step is used as a data engineering tool and its output is used as an input for the Random forest model in the second step. In addition to improvements in terms of spatial resolution, the approach also considers the problem of data gaps. The filling of these gaps is the initial step of the procedure, which in the end produces a continuous product in both temporal and spatial domains. The methodology uses combined active and passive ESA CCI SM products in addition to in situ soil moisture observations and the set of auxiliary downscaling predictors. The research tested several variants of Random forest models to determine the best combination of ESA CCI SM products. The conclusion is that synergic use of all ESA CCI SM products together with the auxiliary datasets in the downscaling procedure provides better results than using just one type of ESA CCI SM product alone. The methodology was applied for obtaining SSM maps for the area of California, USA during 2016. The accuracy of tested models was validated using five-fold cross-validation against in situ data and the best variation of model achieved RMSE, R2 and MAE of 0.0518 m3/m3, 0.7312 and 0.0374 m3/m3, respectively. The methodology proved to be useful for generating high-resolution SSM products, although additional improvements are necessary.

Coupling machine learning with high resolution satellite imagery to estimate spatiotemporal changes of salinity in water bodies

2020 ◽  
Author(s):  
Majid Bayati ◽  
Mohammad Danesh-Yazdi
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Water Quality ◽  
Artificial Neural Networks ◽  
High Resolution ◽  
Satellite Imagery ◽  
Water Bodies ◽  
Wide Range ◽  
High Resolution Satellite Imagery

<p>The spatiotemporal dynamics of salinity in hypersaline lakes is strongly dependent on the rate of water flow feeding the lake, evaporation rate, and the phenomena of precipitation and dissolution. Although in-situ observations are most reliable in quantifying water quality variables, the spatiotemporal distribution of such data are typically limited or cannot be readily extrapolated for long-term projections. Alternatively, remotely-sensed imagery has facilitated less expensive and stronger ability to estimate water quality over a wide range of spatiotemporal resolutions. This study introduces a machine learning model that leverages in-situ measurements and high-resolution satellite imagery to estimate the salinity concentration in water bodies. To this end, 123 points were sampled in April and July of 2019 across the Lake Urmia surface covering the wide range of salinity fluctuations. Among the artificial neural networks, ANFIS, and linear regression tools examined to determine the relationship between salinity and surface reflectance, artificial neural networks yielded the best accuracy evidenced by R<sup>2</sup> = 0.94 and RMSE = 6.8%. The results show that the seasonal change of salinity is linearly correlated with the volume of water feeding the lake, witnessing that dilution imposes a stronger control on the salinity than bed salt dissolution. The impact of disturbance in the lake circulation due to the causeway is also evident from the sharp changes of salinity around the bridge piers near spring when the mixing of fresh and hypersaline water from the southern and northern parts, respectively, takes place. The results of this study prove the promising potential of machine learning tools fed multi-spectral satellite information to map other water quality metrics than salinity as well.</p>

Investigation of cerebrospinal fluid flow in the cerebral aqueduct using high-resolution phase contrast measurements at 7T MRI

2017 ◽  
Vol 59 (8) ◽  
pp. 988-996 ◽  
Author(s):  
Karin Markenroth Bloch ◽  
Johannes Töger ◽  
Freddy Ståhlberg
Keyword(s):  
Cerebrospinal Fluid ◽  
High Resolution ◽  
Spatial Resolution ◽  
Maximum Velocity ◽  
Cerebral Aqueduct ◽  
Mean Flow ◽  
Csf Flow ◽  
Flow Measurements ◽  
Non Invasive ◽  
Wide Range

Background The cerebral aqueduct is a central conduit for cerebrospinal fluid (CSF), and non-invasive quantification of CSF flow in the aqueduct may be an important tool for diagnosis and follow-up of treatment. Magnetic resonance (MR) methods at clinical field strengths are limited by low spatial resolution. Purpose To investigate the feasibility of high-resolution through-plane MR flow measurements (2D-PC) in the cerebral aqueduct at high field strength (7T). Material and Methods 2D-PC measurements in the aqueduct were performed in nine healthy individuals at 7T. Measurement accuracy was determined using a phantom. Aqueduct area, mean velocity, maximum velocity, minimum velocity, net flow, and mean flow were determined using in-plane resolutions 0.8 × 0.8, 0.5 × 0.5, 0.3 × 0.3, and 0.2 × 0.2 mm2. Feasibility criteria were defined based on scan time and spatial and temporal resolution. Results Phantom validation of 2D-PC MR showed good accuracy. In vivo, stroke volume was −8.2 ± 4.4, −4.7 ± 2.8, −6.0 ± 3.8, and −3.7 ± 2.1 µL for 0.8 × 0.8, 0.5 × 0.5, 0.3 × 0.3, and 0.2 × 0.2 mm2, respectively. The scan with 0.3 × 0.3 mm2 resolution fulfilled the feasibility criteria for a wide range of heart rates and aqueduct diameters. Conclusion 7T MR enables non-invasive quantification of CSF flow and velocity in the cerebral aqueduct with high spatial resolution.

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