Wei Ji Leong
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View article: Finetuning AI Foundation Models to Develop Subgrid‐Scale Parameterizations: A Case Study on Atmospheric Gravity Waves
Finetuning AI Foundation Models to Develop Subgrid‐Scale Parameterizations: A Case Study on Atmospheric Gravity Waves Open
Global climate models parameterize a range of atmospheric‐oceanic processes, including gravity waves (GWs), clouds, moist convection, and turbulence, that cannot be sufficiently resolved. These subgrid‐scale closures for unresolved process…
View article: Choosing Earth Foundation Models: From research grade to community maintained
Choosing Earth Foundation Models: From research grade to community maintained Open
View article: icepyx: querying, obtaining, analyzing, andmanipulating ICESat-2 datasets
icepyx: querying, obtaining, analyzing, andmanipulating ICESat-2 datasets Open
icepyx is both a software library and a community composed of ICESat-2 (NASA satellite) data users, developers, maintainers, and the scientific community.We are working together to develop a shared library of resources -including existing …
View article: Review of "Extensive and anomalous grounding line retreat at Vanderford Glacier, Vincennes Bay, Wilkes Land, East Antarctica" by Picton et al. 2022
Review of "Extensive and anomalous grounding line retreat at Vanderford Glacier, Vincennes Bay, Wilkes Land, East Antarctica" by Picton et al. 2022 Open
Abstract. Wilkes Land, East Antarctica, has been losing mass at an accelerating rate over recent decades in response to enhanced oceanic forcing. Overlying the Aurora Subglacial Basin, it has been referred to as the ‘weak …
View article: H2OvalNet: Detecting Fairy Circles from Sentinel-2 imagery in Australia
H2OvalNet: Detecting Fairy Circles from Sentinel-2 imagery in Australia Open
View article: Deep learning based landslide density estimation on SAR data for rapid response
Deep learning based landslide density estimation on SAR data for rapid response Open
This work aims to produce landslide density estimates using Synthetic Aperture Radar (SAR) satellite imageries to prioritise emergency resources for rapid response. We use the United States Geological Survey (USGS) Landslide Inventory data…
View article: SAR-based landslide classification pretraining leads to better segmentation
SAR-based landslide classification pretraining leads to better segmentation Open
Rapid assessment after a natural disaster is key for prioritizing emergency resources. In the case of landslides, rapid assessment involves determining the extent of the area affected and measuring the size and location of individual lands…
View article: Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes
Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes Open
With climate change predicted to increase the likelihood of landslide events, there is a growing need for rapid landslide detection technologies that help inform emergency responses. Synthetic Aperture Radar (SAR) is a remote sensing techn…
View article: Datacubes for Landslide Detection with SAR Imagery
Datacubes for Landslide Detection with SAR Imagery Open
Four analysis-ready datacubes with multiple layers of SAR time-series data and interferometric products (coherence, InSAR) and auxiliary topographic information (elevation, slope, aspect, curvature) for multiple landslide events along with…
View article: Datacubes for Landslide Detection with SAR Imagery
Datacubes for Landslide Detection with SAR Imagery Open
Four analysis-ready datacubes with multiple layers of SAR time-series data and interferometric products (coherence, InSAR) and auxiliary topographic information (elevation, slope, aspect, curvature) for multiple landslide events along with…
View article: Melting and Refreezing in an Ice Shelf Basal Channel at the Grounding Line of the Kamb Ice Stream, West Antarctica
Melting and Refreezing in an Ice Shelf Basal Channel at the Grounding Line of the Kamb Ice Stream, West Antarctica Open
Ice shelves buttress ice streams and glaciers, slowing the rate at which they flow into the ocean. When this buttressing is reduced, either through increased melt or calving, the increased discharge of grounded ice upstream contributes to …
View article: Collaborative Computational Resource Development around ICESat-2 Data: the icepyx Community and Library
Collaborative Computational Resource Development around ICESat-2 Data: the icepyx Community and Library Open
Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Collaborative Computational Resource Development around ICESat-2 Data: the icepyx Community and LibraryAuthorsJessicaScheickiDKelseyBis…
View article: Spatiotemporal variability of active subglacial lakes in Antarctica from 2018-2021 using ICESat-2 laser altimetry
Spatiotemporal variability of active subglacial lakes in Antarctica from 2018-2021 using ICESat-2 laser altimetry Open
Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Spatiotemporal variability of active subglacial lakes in Antarctica from 2018-2021 using ICESat-2 laser altimetryAuthorsWei JiLeongiDHu…
View article: Review of "MPS-BedMappingV1" by Yin et al. 2021
Review of "MPS-BedMappingV1" by Yin et al. 2021 Open
Abstract. The subglacial bed topography is critical for modelling the evolution of Thwaites Glacier in the Amundsen Sea Embayment (ASE), where rapid ice loss threatens the stability of the West Antarctic Ice Sheet. However…
View article: The subglacial landscape and hydrology of Antarctica mapped from space
The subglacial landscape and hydrology of Antarctica mapped from space Open
To narrow uncertainties in the Antarctic ice sheet's contribution to sea level rise, we present a collection of novel machine learning and automated satellite remote sensing methods which use ice surface observations to infer the subgla…
View article: The subglacial landscape and hydrology of Antarctica mapped from space
The subglacial landscape and hydrology of Antarctica mapped from space Open
To narrow uncertainties in the Antarctic ice sheet's contribution to sea level rise, we present a collection of novel machine learning and automated satellite remote sensing methods which use ice surface observations to infer the subgla…
View article: PyGMT: A Python interface for the Generic Mapping Tools
PyGMT: A Python interface for the Generic Mapping Tools Open
PyGMT is a library for processing geospatial and geophysical data and making publication quality maps and figures. It provides a Pythonic interface for the Generic Mapping Tools (GMT), a command-line program widely used in the Earth Scienc…
View article: DeepBedMap: Resolving the bed topography of Antarctica with a deep neural network
DeepBedMap: Resolving the bed topography of Antarctica with a deep neural network Open
To better resolve the bed elevation of Antarctica, we present DeepBedMap - a deep learning method that produces realistic Antarctic bed topography from multiple remote sensing data inputs. Our super-resolution deep convolutional neural net…
View article: DeepBedMap: A super-resolution neural network created bed topography of Antarctica
DeepBedMap: A super-resolution neural network created bed topography of Antarctica Open
Going beyond BEDMAP2 using a super resolution deep neural network. deepbedmap_v1.1.0.zip: Python code for the DeepBedMap Super-Resolution Generative Adversarial Network. deepbedmap_dem.tif: Digital Elevation Model (250 m spatial resolution…
View article: DeepBedMap: A super-resolution neural network created bed topography of Antarctica
DeepBedMap: A super-resolution neural network created bed topography of Antarctica Open
Going beyond BEDMAP2 using a super resolution deep neural network. deepbedmap_v1.1.0.zip: Python code for the DeepBedMap Super-Resolution Generative Adversarial Network. deepbedmap_dem.tif: Digital Elevation Model (250 m spatial resolution…
View article: DeepBedMap: a deep neural network for resolving the bed topography of Antarctica
DeepBedMap: a deep neural network for resolving the bed topography of Antarctica Open
To resolve the bed elevation of Antarctica, we present DeepBedMap – a novel machine learning method that can produce Antarctic bed topography with adequate surface roughness from multiple remote sensing data inputs. The super-resolution de…
View article: Response to Martin Siegert's comments
Response to Martin Siegert's comments Open
I very much enjoyed looking at this paper.Using neural networks (and ai) to better depict the shape of the Antarctic bed is a great idea, and I applaud this effort.The authors have done a good job in describing their work, and its potentia…
View article: Response to Anonymous Referee #2's comments
Response to Anonymous Referee #2's comments Open
This paper introduces a new method, based on Machine Learning, namely a Generative Adversarial Network (GAN), to add short-scale roughness to the bed of Bedmap2.The paper is well written, easy to follow and well illustrated,
View article: DeepBedMap: Using a deep neural network to better resolve the bed topography of Antarctica
DeepBedMap: Using a deep neural network to better resolve the bed topography of Antarctica Open
To better resolve the bed elevation of Antarctica, we present DeepBedMap – a novel machine learning method that produces realistic Antarctic bed topography from multiple remote sensing data inputs. Our super-resolution deep convolutional n…