Gradual build up and episodic character of glacier velocity preceding and during the surge of a Karakorum glacier enabled by open-access image-processing

2020 ◽  
Author(s):  
Ian Delaney ◽  
Saif Aati ◽  
Flavian Beaud ◽  
Shan Gremion ◽  
Surendra Adhikari ◽  
...  
Keyword(s):  
Open Access ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Lake Formation ◽  
Glacier Dynamics ◽  
Current Availability ◽  
Spatio Temporal ◽  
Glacier Velocity ◽  
Glacier Flow

<p>Glacier surging provides a unique opportunity to examine rapid changes in glacier sliding that occur when some glaciers alternate between slower-than-normal (quiescence) and faster-than-normal (surge) velocities. On surging glaciers, mechanical instabilities within the glacier set off a regime of fast glacier flow, which causes these glaciers to accelerate and advance. The precise processes that cause a surging remain uncertain and likely vary between glaciers. However, the uptake of studies on glacier surging over the past decade continues to yield invaluable insights in glacier dynamics. In this study, we combine optical remote sensing and numerical modeling to examine the recent surge of Shishper glacier, in the Pakistani Karakorum. This glacier started surging in 2018, showed a dramatic terminus advance that reached rates of several meters per day. In the process, it dammed the adjacent valley, forming a lake which drained in June 2019 flooding the downstream valley, damaging the Karakorum Highway and threatening nearby communities. We leverage a high spatio-temporal resolution dataset of glacier velocities, using roughly 100 open-access images, across the Landsat-8 and Sentinel-2 record, thus encompassing the quiescence (2013-2018) and surge (2018-2019) phases. We created the dataset in an updated and nearly automated workflow by using the COSI-Corr software package to calculate displacements between images combined with a unique algorithm to filter data and remove artifacts. The result consists in high-resolution velocity maps with resolution with time intervals as short as five days. Such dataset provide a complete time-series of the spatio-temporal evolution of ice-surface velocities during a surge. One of the most notable finding is that the surge onset occurs progressively. In the two years leading up to the surge, spring speed-ups became increasingly larger in than the long-term median. We further identify three periods with  surge velocities far higher than the long-term median that likely coincide with hydrological events. Two periods occur in the spring (2018 and 2019) and the third corresponds with the lake formation in the winter of 2018-2019. Finally, we establish that the surge termination coincided with the lake drainage at the end of June 2019. The current availability of open-access imagery and  glacier topography allow us to  make an increased quantity of observations and thus better quantify glacier dynamics.</p>

scholarly journals Spatio-temporal variations in glacier surface velocity in the Himalayas

2021 ◽  
Author(s):  
Yu Zhou ◽  
Jianlong Chen ◽  
Xiao Cheng
Keyword(s):  
Mass Loss ◽  
Temporal Variations ◽  
Surface Velocity ◽  
Glacier Surface ◽  
Environmental Forcing ◽  
Landsat 7 ◽  
Spatio Temporal ◽  
Velocity Changes ◽  
Glacier Velocity ◽  
Glacier Flow

Abstract. Glacier evolution with time provides important information about climate variability. Here we investigate glacier surface velocity in the Himalayas and analyse the patterns of glacier flow. We collect 220 scenes of Landsat-7 panchromatic images between 1999 and 2000, and Sentinel-2 panchromatic images between 2017 and 2018, to calculate surface velocities of 36,722 glaciers during these two periods. We then derive velocity changes between 1999 and 2018, based on which we perform a detailed analysis of motion of each individual glacier, and noted that the changes are spatially heterogeneous. Of all the glaciers, 32 % have speeded up, 24.5 % have slowed down, and the rest 43.5 % remained stable. The amplitude of glacier slowdown, as a result of glacier mass loss, is remarkably larger than that of speedup. At regional scales, we found that glacier surface velocity in winter has uniformly decreased in the western part of the Himalayas between 1999 and 2018, whilst increased in the eastern part; this contrasting difference may be associated with decadal changes in accumulation and/or melting under different climatic regimes. We also found that the overall trend of surface velocity exhibits seasonal variability: summer velocity changes are positively correlated with mass loss, whereas winter velocity changes show a negative correlation. Our study suggests that glacier velocity changes in the Himalayas are more spatially and temporally heterogeneous than previously thought, emphasising complex interactions between glacier dynamics and environmental forcing.

scholarly journals Automated detection and temporal monitoring of crevasses using remote sensing and their implications for glacier dynamics

2016 ◽  
Vol 57 (71) ◽  
pp. 81-91 ◽  
Author(s):  
Anshuman Bhardwaj ◽  
Lydia Sam ◽  
Shaktiman Singh ◽  
Rajesh Kumar
Keyword(s):  
Flow Characteristics ◽  
Surface Velocity ◽  
Average Error ◽  
Landsat 8 ◽  
Differential Gps ◽  
Swir Band ◽  
Glacier Dynamics ◽  
Glacier Flow ◽  
Shortwave Infrared ◽  
Gps Observations

AbstractDetailed studies on temporal changes of crevasses and their linkage with glacier dynamics are scarce in the Himalayan context. Observations of temporally changing surficial crevasse patterns and their orientations are suggestive of the processes that determine seasonal glacier flow characteristics. In the present study, on a Himalayan valley glacier, changing crevasse patterns and orientations were detected and mapped on Landsat 8 images in an automated procedure using the ratio of Thermal Infrared Sensor (TIRS) band 10 to Optical Land Imager (OLI) shortwave infrared (SWIR) band 6. The ratio was capable of mapping even crevasses falling under mountain shadows. Differential GPS observations suggested an average error of 3.65% and root-mean-square error of 6.32m in crevasse lengths. A year-round observation of these crevasses, coupled with field-based surface velocity measurements, provided some interesting interpretations of seasonal glacier dynamics.

scholarly journals Interannual and Seasonal Variability of Glacier Surface Velocity in the Parlung Zangbo Basin, Tibetan Plateau

2020 ◽  
Vol 13 (1) ◽  
pp. 80
Author(s):  
Jing Zhang ◽  
Li Jia ◽  
Massimo Menenti ◽  
Shaoting Ren
Keyword(s):  
Seasonal Variability ◽  
Global Climate ◽  
Meteorological Data ◽  
Transverse Velocity ◽  
Surface Velocity ◽  
Landsat 8 ◽  
Velocity Change ◽  
Glacier Surface ◽  
Glacier Velocity ◽  
Glacier Flow

Monitoring glacier flow is vital to understand the response of mountain glaciers to environmental forcing in the context of global climate change. Seasonal and interannual variability of surface velocity in the temperate glaciers of the Parlung Zangbo Basin (PZB) has attracted significant attention. Detailed patterns in glacier surface velocity and its seasonal variability in the PZB are still uncertain, however. We utilized Landsat-8 (L8) OLI data to investigate in detail the variability of glacier velocity in the PZB by applying the normalized image cross-correlation method. On the basis of satellite images acquired from 2013 to 2020, we present a map of time-averaged glacier surface velocity and examined four typical glaciers (Yanong, Parlung No.4, Xueyougu, and Azha) in the PZB. Next, we explored the driving factors of surface velocity and of its variability. The results show that the glacier centerline velocity increased slightly in 2017–2020. The analysis of meteorological data at two weather stations on the outskirts of the glacier area provided some indications of increased precipitation during winter-spring. Such increase likely had an impact on ice mass accumulation in the up-stream portion of the glacier. The accumulated ice mass could have caused seasonal velocity changes in response to mass imbalance during 2017–2020. Besides, there was a clear winter-spring speedup of 40% in the upper glacier region, while a summer speedup occurred at the glacier tongue. The seasonal and interannual velocity variability was captured by the transverse velocity profiles in the four selected glaciers. The observed spatial pattern and seasonal variability in glacier surface velocity suggests that the winter-spring snow might be a driver of glacier flow in the central and upper portions of glaciers. Furthermore, the variations in glacier surface velocity are likely related to topographic setting and basal slip caused by the percolation of rainfall. The findings on glacier velocity suggest that the transfer of winter-spring accumulated ice triggered by mass conservation seems to be the main driver of changes in glacier velocity. The reasons that influence the seasonal surface velocity change need further investigation.

Random Forest (RF) and Artificial Neural Network (ANN) Algorithms for LULC Mapping

2020 ◽  
Vol 38 (4A) ◽  
pp. 510-514
Author(s):  
Tay H. Shihab ◽  
Amjed N. Al-Hameedawi ◽  
Ammar M. Hamza
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Artificial Neural Network ◽  
Random Forest ◽  
Satellite Image ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Data Set ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

In this paper to make use of complementary potential in the mapping of LULC spatial data is acquired from LandSat 8 OLI sensor images are taken in 2019.  They have been rectified, enhanced and then classified according to Random forest (RF) and artificial neural network (ANN) methods. Optical remote sensing images have been used to get information on the status of LULC classification, and extraction details. The classification of both satellite image types is used to extract features and to analyse LULC of the study area. The results of the classification showed that the artificial neural network method outperforms the random forest method. The required image processing has been made for Optical Remote Sensing Data to be used in LULC mapping, include the geometric correction, Image Enhancements, The overall accuracy when using the ANN methods 0.91 and the kappa accuracy was found 0.89 for the training data set. While the overall accuracy and the kappa accuracy of the test dataset were found 0.89 and 0.87 respectively.

The Conceptual Framework: Growth, Institutions, and Social Orders

2018 ◽  
Author(s):  
Andrea Lorenzo Capussela
Keyword(s):  
Open Access ◽  
Conceptual Framework ◽  
Social Order ◽  
Institutional Economics ◽  
Theoretical Framework ◽  
Institutional Reforms ◽  
Reversible Process ◽  
Main Determinant ◽  
Social Orders

This chapter lays out one part of the theoretical framework of the book, drawn from institutional economics. This literature maintains that institutions are the main determinant of long-term growth, and that to remain ‘appropriate’ institutions must evolve in synchrony with an economy’s progress through the stages of its development. Their evolution depends on a society’s openness to political creative destruction. Limited-access social orders tend to constrain it, to safeguard elites’ rents, and typically undermine progressive institutional reforms, breaking that synchrony. The transition from that social order to the open-access one is an endogenous and reversible process, in which inefficient institutions, which allow elites to extract rents, coexist with appropriate ones, which constrain their power and make it contestable. The hypothesis is advanced that Italy has not yet completed this transition, and that the tension between its efficient and inefficient institutions can endogenously generate shocks, which open opportunities for equilibrium shifts.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

scholarly journals Consistent Long-Term Monthly Coastal Wetland Vegetation Monitoring Using a Virtual Satellite Constellation

2021 ◽  
Vol 13 (3) ◽  
pp. 438
Author(s):  
Subrina Tahsin ◽  
Stephen C. Medeiros ◽  
Arvind Singh
Keyword(s):  
Vegetation Index ◽  
Coastal Wetland ◽  
Thermal Emission ◽  
Mean Squared Error ◽  
Wetland Vegetation ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Vegetation Monitoring ◽  
Time Space

Long-term monthly coastal wetland vegetation monitoring is the key to quantifying the effects of natural and anthropogenic events, such as severe storms, as well as assessing restoration efforts. Remote sensing data products such as Normalized Difference Vegetation Index (NDVI), alongside emerging data analysis techniques, have enabled broader investigations into their dynamics at monthly to decadal time scales. However, NDVI data suffer from cloud contamination making periods within the time series sparse and often unusable during meteorologically active seasons. This paper proposes a virtual constellation for NDVI consisting of the red and near-infrared bands of Landsat 8 Operational Land Imager, Sentinel-2A Multi-Spectral Instrument, and Advanced Spaceborne Thermal Emission and Reflection Radiometer. The virtual constellation uses time-space-spectrum relationships from 2014 to 2018 and a random forest to produce synthetic NDVI imagery rectified to Landsat 8 format. Over the sample coverage area near Apalachicola, Florida, USA, the synthetic NDVI showed good visual coherence with observed Landsat 8 NDVI. Comparisons between the synthetic and observed NDVI showed Root Mean Squared Error and Coefficient of Determination (R2) values of 0.0020 sr−1 and 0.88, respectively. The results suggest that the virtual constellation was able to mitigate NDVI data loss due to clouds and may have the potential to do the same for other data. The ability to participate in a virtual constellation for a useful end product such as NDVI adds value to existing satellite missions and provides economic justification for future projects.

Seabird bycatch vulnerability in pelagic longline fisheries based on modelling of a long-term dataset

2021 ◽  
pp. 1-16
Author(s):  
CAN ZHOU ◽  
NIGEL BROTHERS
Keyword(s):  
Capture Event ◽  
Retrieval Rate ◽  
Competitive Environments ◽  
Global Concern ◽  
Competitive Species ◽  
Spatio Temporal ◽  
Longline Fisheries ◽  
Pelagic Longline

Summary The incidental mortality of seabirds in fisheries remains a serious global concern. Obtaining unbiased and accurate estimates of bycatch rates is a priority for seabird bycatch mitigation and demographic research. For measuring the capture risk of seabird interactions in fisheries, the rate of carcass retrieval from hauled gear is commonly used. However, reliability can be limited by a lack of direct capture observations and the substantial pre-haul bycatch losses known to occur, meaning incidence of seabird bycatch is underestimated. To solve this problem, a new measure (bycatch vulnerability) that links an observed interaction directly to the underlying capture event is proposed to represent the capture risk of fishery interactions by seabirds. The new measure is not affected by subsequent bycatch loss. To illustrate how to estimate and analyse bycatch vulnerability, a case study based on a long-term dataset of seabird interactions and capture confirmation is provided. Bayesian modelling and hypothesis testing were conducted to identify important bycatch risk factors. Competition was found to play a central role in determining seabird bycatch vulnerability. More competitive environments were riskier for seabirds, and larger and thus more competitive species were more at risk than smaller sized and less competitive species. Species foraging behaviour also played a role. On the other hand, no additional effect of physical oceanic condition and spatio-temporal factors on bycatch vulnerability was detected. Bycatch vulnerability is recommended as a replacement for the commonly used bycatch rate or carcass retrieval rate to measure the capture risk of an interaction. Combined with a normalized contact rate, bycatch vulnerability offers an unbiased estimate of seabird bycatch rate in pelagic longline fisheries.

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