ICESat-2 (IS2) by NASA is an Earth-observing satellite that measures high-resolution surface elevation. The IS2's ATL07 and ATL10 sea ice elevation and freeboard products of 10m-200m segments which aggregated 150 signal photons from the raw ATL03 (geolocated photon) data. These aggregated products can potentially overestimate local sea surface height, thus underestimating the calculations of freeboard (sea ice height above sea surface). To achieve a higher resolution of sea surface height and freeboard information, in this work we utilize a 2m window to resample the ATL03 data. Then, we classify these 2m segments into thick sea ice, thin ice, and open water using deep learning methods (Long short-term memory and Multi-layer perceptron models). To obtain labeled training data for our deep learning models, we use segmented Sentinel-2 (S2) multi-spectral imagery overlapping with IS2 tracks in space and time to auto-label IS2 data, followed by some manual corrections in the regions of transition between different ice/water types or cloudy regions. We employ a parallel workflow for this auto-labeling using PySpark to scale, and we achieve 9-fold data loading and 16.25-fold map-reduce speedup. To train our models, we employ a Horovod-based distributed deep-learning workflow on a DGX A100 8 GPU cluster, achieving a 7.25-fold speedup. Next, we calculate the local sea surface heights based on the open water segments. Finally, we scale the freeboard calculation using the derived local sea level and achieve 8.54-fold data loading and 15.7-fold map-reduce speedup. Compared with the ATL07 (local sea level) and ATL10 (freeboard) data products, our results show higher resolutions and accuracy (96.56%).

The observation of the advancing and retreating pattern of polar sea ice cover stands as a vital indicator of global warming. This research aims to develop a robust, effective, and scalable system for classifying polar sea ice as thick/snow-covered, young/thin, or open water using Sentinel-2 (S2) images. Since the S2 satellite is actively capturing high-resolution imagery over the earth's surface, there are lots of images that need to be classified. One major obstacle is the absence of labeled S2 training data (images) to act as the ground truth. We demonstrate a scalable and accurate method for segmenting and automatically labeling S2 images using carefully determined color thresholds. We employ a parallel workflow using PySpark to scale and achieve 9-fold data loading and 16-fold map-reduce speedup on auto-labeling S2 images based on thin cloud and shadow-filtered color-based segmentation to generate label data. The auto-labeled data generated from this process are then employed to train a U-Net machine learning model, resulting in good classification accuracy. As training the U-Net classification model is computationally heavy and time-consuming, we distribute the U-Net model training to scale it over 8 GPUs using the Horovod framework over a DGX cluster with a 7.21x speedup without affecting the accuracy of the model. Using the Antarctic's Ross Sea region as an example, the U-Net model trained on auto-labeled data achieves a classification accuracy of 98.97% for auto-labeled training datasets when the thin clouds and shadows from the S2 images are filtered out.

Global warming is an urgent issue that is generating catastrophic environmental changes, such as the melting of sea ice and glaciers, particularly in the polar regions. The melting pattern and retreat of polar sea ice cover is an essential indicator of global warming. The Sentinel-2 satellite (S2) captures high-resolution optical imagery over the polar regions. This research aims at developing a robust and effective system for classifying polar sea ice as thick or snow-covered, young or thin, or open water using S2 images. A key challenge is the lack of labeled S2 training data to serve as the ground truth. We demonstrate a method with high precision to segment and automatically label the S2 images based on suitably determined color thresholds and employ these auto-labeled data to train a U-Net machine model (a fully convolutional neural network), yielding good classification accuracy. Evaluation results over S2 data from the polar summer season in the Ross Sea region of the Antarctic show that the U-Net model trained on auto-labeled data has an accuracy of 90.18% over the original S2 images, whereas the U-Net model trained on manually labeled data has an accuracy of 91.39%. Filtering out the thin clouds and shadows from the S2 images further improves U-Net's accuracy, respectively, to 98.97% for auto-labeled and 98.40% for manually labeled training datasets.

Promising more accurate predictions in an era of rapid climate change, a new tool is harnessing deep learning to help better forecast Arctic sea ice conditions months into the future. As described in a paper published in the science journal Nature Communications Thursday, the new AI tool, dubbed IceNet, could lead to improved early-warning systems to protect Arctic wildlife and coastal communities. Created by an international team of researchers led by the British Antarctic Survey and the Alan Turing Institute, IceNet tackles a challenge that has long vexed scientists. "The Arctic is a region on the frontline of climate change and has seen substantial warming over the last 40 years," explained lead author Tom Andersson, a data scientist at the BAS AI Lab, in a statement. "IceNet has the potential to fill an urgent gap in forecasting sea ice for Arctic sustainability efforts and runs thousands of times faster than traditional methods," he added.

Google says its artificial intelligence has taught itself to'translate between languages that it doesn't even know' 'Zero-shot translation' can translate between languages it doesn't know Deep-learning researchers developed Google Neural Machine Translation GNMT developed algorithm that'self-teaches' it to translate languages'Zero-shot translation' can translate between languages it doesn't know GNMT developed algorithm that'self-teaches' it to translate languages Google headquarters in Menlo Park, California is seen in the above stock photo. Google says it has built an algorithm that allows its Google Translate service to translate languages it doesn't even know Google says that its artificial intelligence uses a'token' at the beginning of the input sentence to specify the required target language to translate to Skating on thin ice: Wife of Vladimir Putin's spokesman... 'This had nothing to do with Donald': Rosie O'Donnell... Liberty University President Jerry Falwell Jr. says he... New Orleans violence'out of control' says mayor after one... Skating on thin ice: Wife of Vladimir Putin's spokesman... 'This had nothing to do with Donald': Rosie O'Donnell... Liberty University President Jerry Falwell Jr. says he... New Orleans violence'out of control' says mayor after one... Barron Trump clapping during his father's appearance at RNC Penny for your thoughts: Cute baby laughs at hearing dad say 4p Mob storm police station and lynch suspected paedophile Homeless man has zebra-skin slipcovers & porcelain toilet Bear with us!: Workers rescue bear under concrete pit in Turkey All washed up! People desperately try free 4x4 stuck on beach 100 special police agents protect suspected paedophile from mob Surprise Castro is dead: Florida grandmother is shocked! Moment pranksters invade the X Factor stage after Honey G performs Girlfriend confronts'cheating boyfriend' at supermarket It was a long and tiresome night for 10-year-old Barron Trump Raging bull destroys car with horns at Spanish festival Surprise Castro is dead: Florida grandmother is shocked! Girlfriend confronts'cheating boyfriend' at supermarket Trump nemesis Rosie O'Donnell is slammed after speculating... Homeless man who turned freeway underpass into a personal... Donald goes to war as Hillary backs recount: Trump accuses... Trump launches furious morning Twitter rant at Hillary,... REVEALED: California supermom was heavily beaten and chained... ISIS fighters target Israel for the first time and are... Thousands of fans BOO Colin Kaepernick in Miami after he... Skating on thin ice: Wife of Vladimir Putin's spokesman... Cop tries desperately to save a one-month-old girl who... Outrage as Prince Harry is forced to take part in an...

Google says its artificial intelligence has taught itself to'translate between languages that it doesn't even know' 'Zero-shot translation' can translate between languages it doesn't know Deep-learning researchers developed Google Neural Machine Translation GNMT developed algorithm that'self-teaches' it to translate languages'Zero-shot translation' can translate between languages it doesn't know GNMT developed algorithm that'self-teaches' it to translate languages Google headquarters in Menlo Park, California is seen in the above stock photo. Google says it has built an algorithm that allows its Google Translate service to translate languages it doesn't even know Google says that its artificial intelligence uses a'token' at the beginning of the input sentence to specify the required target language to translate to Skating on thin ice: Wife of Vladimir Putin's spokesman... 'This had nothing to do with Donald': Rosie O'Donnell... Liberty University President Jerry Falwell Jr. says he... New Orleans violence'out of control' says mayor after one... Skating on thin ice: Wife of Vladimir Putin's spokesman... 'This had nothing to do with Donald': Rosie O'Donnell... Liberty University President Jerry Falwell Jr. says he... New Orleans violence'out of control' says mayor after one... Barron Trump clapping during his father's appearance at RNC Penny for your thoughts: Cute baby laughs at hearing dad say 4p Mob storm police station and lynch suspected paedophile Homeless man has zebra-skin slipcovers & porcelain toilet Moment pranksters invade the X Factor stage after Honey G performs All washed up! People desperately try free 4x4 stuck on beach Surprise Castro is dead: Florida grandmother is shocked! 100 special police agents protect suspected paedophile from mob Bear with us!: Workers rescue bear under concrete pit in Turkey Trollstation celebrate storming the X Factor stage in Wembley Girlfriend confronts'cheating boyfriend' at supermarket It was a long and tiresome night for 10-year-old Barron Trump Surprise Castro is dead: Florida grandmother is shocked! Girlfriend confronts'cheating boyfriend' at supermarket Trump nemesis Rosie O'Donnell is slammed after speculating... Homeless man who turned freeway underpass into a personal... Trump launches furious morning Twitter rant at Hillary,... Donald goes to war as Hillary backs recount: Trump accuses... REVEALED: California supermom was heavily beaten and chained... Cop tries desperately to save a one-month-old girl who... Skating on thin ice: Wife of Vladimir Putin's spokesman... ISIS fighters target Israel for the first time and are... Thousands of fans BOO Colin Kaepernick in Miami after he... The curious demise of internet mogul once worth $95m who now... From sneaking into your teacher's house to winning prizes... Talk is cheap!

Google says its artificial intelligence has taught itself to'translate between languages that it doesn't even know' 'Zero-shot translation' can translate between languages it doesn't know Deep-learning researchers developed Google Neural Machine Translation GNMT developed algorithm that'self-teaches' it to translate languages'Zero-shot translation' can translate between languages it doesn't know GNMT developed algorithm that'self-teaches' it to translate languages Google headquarters in Menlo Park, California is seen in the above stock photo. Google says it has built an algorithm that allows its Google Translate service to translate languages it doesn't even know Google says that its artificial intelligence uses a'token' at the beginning of the input sentence to specify the required target language to translate to Skating on thin ice: Wife of Vladimir Putin's spokesman... 'This had nothing to do with Donald': Rosie O'Donnell... Liberty University President Jerry Falwell Jr. says ...