scholarly journals Assessing the Glacier Boundaries in the Qinghai-Tibetan Plateau of China by Multi-Temporal Coherence Estimation with Sentinel-1A InSAR

2019 ◽  
Vol 11 (4) ◽  
pp. 392
Author(s):  
Yueling Shi ◽  
Guoxiang Liu ◽  
Xiaowen Wang ◽  
Qiao Liu ◽  
Rui Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Mean Value ◽  
Sar Images ◽  
Temperature And Precipitation ◽  
Alpine Glaciers ◽  
Wet Snow ◽  
Multi Temporal ◽  
The Mean ◽  
Coherence Estimation ◽  
Coherence Level

The sensitivity of synthetic aperture radar (SAR) coherence has been applied in delineating the boundaries of alpine glaciers because it is nearly unaffected by cloud coverage and can collect data day and night. However, very limited work with application of SAR data has been performed for the alpine glaciers in the Qinghai-Tibetan Plateau (QTP) of China. In this study, we attempted to investigate the change of coherence level in alpine glacier zone and access the glacier boundaries in the QTP using time series of Sentinel-1A SAR images. The DaDongkemadi Glacier (DDG) in the central QTP was selected as the study area with land cover mainly classified into wet snow, ice, river outwash and soil land. We utilized 45 Sentinel-1A C-band SAR images collected during October of 2014 through January of 2018 over the DDG to generate time series of interferometric coherence maps, and to further extract the DDG boundaries. Based on the spatiotemporal analysis of coherence values in the selected sampling areas, we first determined the threshold as 0.7 for distinguishing among different ground targets and then extracted the DDG boundaries through threshold-based segmentation and edge detection. The validation was performed by comparing the DDG boundaries extracted from the coherence maps with those extracted from the Sentinel-2B optical image. The testing results show that the wet snow and ice present a relatively low level of coherence (about 0.5), while the river outwash and the soil land present a higher level of coherence (0.8–1.0). It was found that the coherence maps spanning between June and September (i.e., the glacier ablation period) are the most suitable for identifying the snow- and ice-covered areas. When compared with the boundary detected using optical image, the mean value of Jaccard similarity coefficient for the total areas within the DDG boundaries derived from the coherence maps selected around July, August and September reached up to 0.9010. In contrast, the mean value from the coherence maps selected around December was relatively lower (0.8862). However, the coherence maps around December were the most suitable for distinguishing the ice from the river outwash around the DDG terminus, as the river outwash areas could hardly be differentiated from the ice-covered areas from June through September. The correlation analysis performed by using the meteorological data (i.e., air temperature and precipitation records) suggests that the air temperature and precipitation have a more significant influence on the coherence level of the ice and river outwash than the wet snow and soil land. The proposed method, applied efficiently in this study, shows the potential of multi-temporal coherence estimation from the Sentinel-1A mission to access the boundaries of alpine glaciers on a larger scale in the QTP.

scholarly journals Irrigation Mapping Using Sentinel-1 Time Series at Field Scale

2018 ◽  
Vol 10 (9) ◽  
pp. 1495 ◽  
Author(s):  
Qi Gao ◽  
Mehrez Zribi ◽  
Maria Escorihuela ◽  
Nicolas Baghdadi ◽  
Pere Segui
Keyword(s):  
Time Series ◽  
Weather Conditions ◽  
Mean Value ◽  
Support Vector ◽  
Irrigated Crops ◽  
The Mean ◽  
Sar Data ◽  
Ground Truthing ◽  
Agricultural Site

The recently launched Sentinel-1 satellite with a Synthetic Aperture Radar (SAR) sensor onboard offers a powerful tool for irrigation monitoring under various weather conditions, with high spatial and temporal resolution. This research discusses the potential of different metrics calculated from the Sentinel-1 time series for mapping irrigated fields. A methodology for irrigation mapping using SAR data is proposed. The study is performed using VV (vertical–vertical) and VH (vertical–horizontal) polarizations over an agricultural site in Urgell, Catalunya (Spain). With field segmentation information from SIGPAC (the Geographic Information System for Agricultural Parcels), the backscatter intensities are averaged within each field. From the Sentinel-1 time series for each field, the statistics and metrics, including the mean value, the variance of the signal, the correlation length, and the fractal dimension, are analyzed. With the Support Vector Machine (SVM), the classification of irrigated crops, irrigated trees, and non-irrigated fields is performed with the metrics vector. The results derived from the SVM are validated with ground truthing from SIGPAC over the whole study area, with a good overall accuracy of 81.08%. Random Forest (RF) machine classification is also tested in this study, which gives an accuracy of around 82.2% when setting the tree depth at three. The methodology is based only on SAR data, which makes it applicable to all areas, even with frequent cloud cover, but this method may be less robust when irrigation is less dominated to soil moisture change.

scholarly journals Uncovering Interaction Between The Loops Of Autonomic Regulation Of Blood Circulation From Long Time Series

2020 ◽  
Vol 9 (4) ◽  
Author(s):  
Viktoriia V. Skazkina ◽  
Anatoly S. Karavaev ◽  
Ekaterina I. Borovkova ◽  
Margarita A. Simonyan ◽  
Mikhail D. Prokhorov ◽  
...  
Keyword(s):  
Time Series ◽  
Hormonal Regulation ◽  
Blood Circulation ◽  
Phase Synchronization ◽  
Mean Value ◽  
Recording Time ◽  
Long Time Series ◽  
Total Percentage ◽  
Long Time ◽  
The Mean

The purpose of this work is to study the interaction between the autonomic regulatory loops of blood circulation from long time series. Methods ― We simultaneously recorded four-hour signals of electrocardiogram and photoplethysmogram from the ear and finger of ten healthy adults. We determined the intervals of phase synchronization of the studied regulatory loops and analyzed the dependence of their length on the recording time. The deviations of the total percentage of phase synchronization (index S) from its mean value were estimated in moving non-overlapping windows. Results ― For studied signals we found no significant correlation between the length of synchronization epoch and the time of its beginning. A sharp increase in the deviation of the index S from its mean was shown at the end of the experiment. Conclusion ― The increase in the deviation from the mean at the end of our records is most likely associated more with psychosomatic influences than with hormonal regulation or immobilization stress.

Monthly-mean residual flows through the Dover Strait, 1949–1972

1978 ◽  
Vol 58 (4) ◽  
pp. 965-973 ◽  
Author(s):  
D. Prandle
Keyword(s):  
Time Series ◽  
North Sea ◽  
Marine Biology ◽  
Small Variation ◽  
Mean Value ◽  
Residual Flow ◽  
Mean Flow ◽  
The North ◽  
The North Sea ◽  
The Mean

An estimate is made of the mean value of residual flow through the Dover Strait for each month over the 24–year period from 1949 to 1972. The estimates are based on results from a modelling investigation by Prandle (1978) where it was shown that the residual flow consists of three components, (a) a tidal residual, (b), a wind-driven residual and (c) a flow due to a long-term gradient in mean sea level. The components (a) and (c) are assumed to be constant and the value of (b) is deduced using wind data recorded by Dutch Light Vessels located in the southern North Sea.The mean flow over the whole period amounts to 155 × 103 m3 s–1 into the North Sea with a maximum value of 364 x 103 m3 s–1 and a minimum of – 15 × 103 m3 s–1 (out of the North Sea). One notable feature of the complete time series is the surprisingly small variation in the annual mean flows; perhaps this stability in the annual flow is of significance to the marine biology of the area.The validity of the computed time series is established by reference to comparable data including a 9–year record, from cross-channel submarine cables, of the potential induced by the flow of water through the Earth's magnetic field. Additional comparisons are also made with the results of a previous study of daily-mean flows.

scholarly journals Slow drag in wet-snow avalanche flow

2010 ◽  
Vol 56 (198) ◽  
pp. 587-592 ◽  
Author(s):  
B. Sovilla ◽  
M. Kern ◽  
M. Schaer
Keyword(s):  
Mean Value ◽  
Immersion Depth ◽  
Snow Avalanches ◽  
Pressure Time ◽  
Large Fluctuations ◽  
Load Cells ◽  
Snow Pressure ◽  
Wet Snow ◽  
Avalanche Flow ◽  
The Mean

AbstractWe report impact pressures exerted by three wet-snow avalanches on a pylon equipped with piezoelectric load cells. These pressures were considerably higher than those predicted by conventional avalanche engineering guidelines. The time-averaged pressure linearly increased with the immersion depth of the load cells and it was about eight times larger than the hydrostatic snow pressure. At the same immersion depth, the pressures were very similar for all three avalanches and no dependency between avalanche velocity and pressure was apparent. The pressure time series were characterized by large fluctuations. For all immersion depths and for all avalanches, the standard deviations of the fluctuations were, on average, about 20% of the mean value. We compare our observations with results of slow-drag granular experiments, where similar behavior has been explained by formation and destruction of chain structures due to jamming of granular material around the pylon, and we propose the same mechanism as a possible microscale interpretation of our observations.

scholarly journals Climate sensitivity estimates – sensitivity to radiative forcing time series and observational data

2018 ◽  
Vol 9 (2) ◽  
pp. 879-894 ◽  
Author(s):  
Ragnhild Bieltvedt Skeie ◽  
Terje Berntsen ◽  
Magne Aldrin ◽  
Marit Holden ◽  
Gunnar Myhre
Keyword(s):  
Time Series ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Heat Content ◽  
Deep Ocean ◽  
Mean Value ◽  
Transient Climate Response ◽  
Surface Temperature Change ◽  
Near Surface ◽  
The Mean

Abstract. Inferred effective climate sensitivity (ECSinf) is estimated using a method combining radiative forcing (RF) time series and several series of observed ocean heat content (OHC) and near-surface temperature change in a Bayesian framework using a simple energy balance model and a stochastic model. The model is updated compared to our previous analysis by using recent forcing estimates from IPCC, including OHC data for the deep ocean, and extending the time series to 2014. In our main analysis, the mean value of the estimated ECSinf is 2.0 ∘C, with a median value of 1.9 ∘C and a 90 % credible interval (CI) of 1.2–3.1 ∘C. The mean estimate has recently been shown to be consistent with the higher values for the equilibrium climate sensitivity estimated by climate models. The transient climate response (TCR) is estimated to have a mean value of 1.4 ∘C (90 % CI 0.9–2.0 ∘C), and in our main analysis the posterior aerosol effective radiative forcing is similar to the range provided by the IPCC. We show a strong sensitivity of the estimated ECSinf to the choice of a priori RF time series, excluding pre-1950 data and the treatment of OHC data. Sensitivity analysis performed by merging the upper (0–700 m) and the deep-ocean OHC or using only one OHC dataset (instead of four in the main analysis) both give an enhancement of the mean ECSinf by about 50 % from our best estimate.

scholarly journals Use of Sentinel-1 radar observations to evaluate snowmelt dynamics in alpine regions

2019 ◽  
Author(s):  
Carlo Marin ◽  
Giacomo Bertoldi ◽  
Valentina Premier ◽  
Mattia Callegari ◽  
Christian Brida ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Melting Process ◽  
Liquid Water Content ◽  
Sar Images ◽  
Distributed Information ◽  
Snow Modeling ◽  
Alpine Regions ◽  
Wet Snow ◽  
Spatially Distributed ◽  
Multi Temporal

Abstract. Knowing the timing and the evolution of the snow melting process is very important, since it allows the prediction of: i) the snow melt onset; ii) the snow gliding and wet-snow avalanches; iii) the release of snow contaminants and iv) the runoff onset. The snowmelt can be monitored by jointly measuring snowpack parameters such as the snow water equivalent (SWE) or the amount of free liquid water content (LWC). However, continuous measurements of SWE and LWC are rare and difficult to be obtained. On the other hand, active microwave sensors such as the Synthetic Aperture Radar (SAR) mounted on board of satellites, are highly sensitive to LWC of the snowpack and can provide spatially distributed information with a high resolution. Moreover, with the introduction of Sentinel-1, SAR images are regularly acquired every 6 days over several places in the world. In this paper we analyze the correlation between the multi-temporal SAR backscattering and the snowmelt dynamics. We compared Sentinel-1 backscattering with snow properties derived from in situ observations and process-based snow modeling simulations for five alpine test sites in Italy, Germany and Switzerland considering two hydrological years. We found that the multi-temporal SAR measurements allow the identification of the three melting phases that characterize the melting process i.e., moistening, ripening and runoff. In detail, we found that the C-band SAR backscattering decreases as soon as the snow starts containing water, and that the backscattering increases as soon as SWE starts decreasing, which corresponds to the release of meltwater from the snowpack. We discuss the possible reasons of this increase, which are not directly correlated to the SWE decrease, but to the different snow conditions, which change the backscattering mechanisms. Finally, we show a spatially-distributed application of the identification of the runoff onset from SAR images for a mountain catchment, i.e., the Zugspitze catchment in Germany. Results allow to better understand the spatial and temporal evolution of melting dynamics in mountain regions. The presented investigation could have relevant applications for monitoring and predicting the snowmelt progress over large regions.

Long-period modulated superstructures in Pd-12.5 at.%Ce and Pd-15 at.%Ce alloys

1990 ◽  
Vol 48 (4) ◽  
pp. 164-165
Author(s):  
Noriyuki Kuwano ◽  
Masaru Itakura ◽  
Kensuke Oki
Keyword(s):  
Electron Microscopy ◽  
Mean Value ◽  
Heavy Elements ◽  
Arc Furnace ◽  
X Ray ◽  
Long Period ◽  
Ultra High Purity ◽  
Heat Treated ◽  
Atomic Scattering ◽  
The Mean

Pd-Ce alloys exhibit various anomalies in physical properties due to mixed valences of Ce, and the anomalies are thought to be strongly related with the crystal structures. Since Pd and Ce are both heavy elements, relative magnitudes of (fcc-fpd) are so small compared with <f> that superlattice reflections, even if any, sometimes cannot be detected in conventional x-ray powder patterns, where fee and fpd are atomic scattering factors of Ce and Pd, and <f> the mean value in the crystal. However, superlattices in Pd-Ce alloys can be analyzed by electron microscopy, thanks to the high detectability of electron diffraction. In this work, we investigated modulated superstructures in alloys with 12.5 and 15.0 at.%Ce.Ingots of Pd-Ce alloys were prepared in an arc furnace under atmosphere of ultra high purity argon. The disc specimens cut out from the ingots were heat-treated in vacuum and electrothinned to electron transparency by a jet method.

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