Short-term spatial and temporal patterns of suspended sediment transfer in proglacial channels, small River Glacier, Canada

Abstract. Rising sea levels and increased surface melting of the Greenland ice sheet have heightened the need for direct observations of meltwater release from the ice edge to ocean. Buoyant sediment plumes that develop in fjords downstream of outlet glaciers are controlled by numerous factors, including meltwater runoff. Here, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery is used to average surface suspended sediment concentration (SSC) in fjords around ~80% of Greenland from 2000–2009. Spatial and temporal patterns in SSC are compared with positive-degree-days (PDD), a proxy for surface melting, from the Polar MM5 regional climate model. Over this decade significant geographic covariance occurred between ice sheet PDD and fjord SSC, with outlet type (land- vs. marine-terminating glaciers) also important. In general, high SSC is associated with high PDD and/or a high proportion of land-terminating glaciers. Unlike previous site-specific studies of the Watson River plume at Kangerlussuaq, temporal covariance is low, suggesting that plume dimensions best capture interannual runoff dynamics whereas SSC allows assessment of long-term conditions across much broader fjord environments around the ice sheet. Remote sensing of both plume charactersitics thus offers a viable approach for observing spatial and temporal patterns of meltwater release exiting the Greenland ice sheet to the global ocean.

Download Full-text

Capturing Spatial and Temporal Patterns for Facial Landmark Tracking through Adversarial Learning

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2019/142 ◽

2019 ◽

Cited By ~ 1

Author(s):

Shi Yin ◽

Shangfei Wang ◽

Guozhu Peng ◽

Xiaoping Chen ◽

Bowen Pan

Keyword(s):

Short Term Memory ◽

Temporal Patterns ◽

Ground Truth ◽

Spatial And Temporal Patterns ◽

Short Term ◽

Adversarial Learning ◽

Facial Landmark ◽

Landmark Tracking ◽

Memory Network ◽

Long Short Term Memory

The spatial and temporal patterns inherent in facial feature points are crucial for facial landmark tracking, but have not been thoroughly explored yet. In this paper, we propose a novel deep adversarial framework to explore the shape and temporal dependencies from both appearance level and target label level. The proposed deep adversarial framework consists of a deep landmark tracker and a discriminator. The deep landmark tracker is composed of a stacked Hourglass network as well as a convolutional neural network and a long short-term memory network, and thus implicitly capture spatial and temporal patterns from facial appearance for facial landmark tracking. The discriminator is adopted to distinguish the tracked facial landmarks from ground truth ones. It explicitly models shape and temporal dependencies existing in ground truth facial landmarks through another convolutional neural network and another long short-term memory network. The deep landmark tracker and the discriminator compete with each other. Through adversarial learning, the proposed deep adversarial landmark tracking approach leverages inherent spatial and temporal patterns to facilitate facial landmark tracking from both appearance level and target label level. Experimental results on two benchmark databases demonstrate the superiority of the proposed approach to state-of-the-art work.

Download Full-text

Hydrologic controls on coastal suspended sediment plumes around the Greenland Ice Sheet

The Cryosphere ◽

10.5194/tc-6-1-2012 ◽

2012 ◽

Vol 6 (1) ◽

pp. 1-19 ◽

Cited By ~ 32

Author(s):

V. W. Chu ◽

L. C. Smith ◽

A. K. Rennermalm ◽

R. R. Forster ◽

J. E. Box

Keyword(s):

Suspended Sediment ◽

Climate Model ◽

Regional Climate ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Temporal Patterns ◽

Sediment Concentration ◽

Surface Melting ◽

Global Ocean ◽

Spatial And Temporal Patterns

Abstract. Rising sea levels and increased surface melting of the Greenland ice sheet have heightened the need for direct observations of meltwater release from the ice edge to ocean. Buoyant sediment plumes that develop in fjords downstream of outlet glaciers are controlled by numerous factors, including meltwater runoff. Here, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery is used to average surface suspended sediment concentration (SSC) in fjords around ∼80% of Greenland from 2000–2009. Spatial and temporal patterns in SSC are compared with positive-degree-days (PDD), a proxy for surface melting, from the Polar MM5 regional climate model. Over this decade significant geographic covariance occurred between ice sheet PDD and fjord SSC, with outlet type (land- vs. marine-terminating glaciers) also important. In general, high SSC is associated with high PDD and/or a high proportion of land-terminating glaciers. Unlike previous site-specific studies of the Watson River plume at Kangerlussuaq, temporal covariance is low, suggesting that plume dimensions best capture interannual runoff dynamics whereas SSC allows assessment of meltwater signals across much broader fjord environments around the ice sheet. Remote sensing of both plume characteristics thus offers a viable approach for observing spatial and temporal patterns of meltwater release from the Greenland ice sheet to the global ocean.

Download Full-text