Miguel D. Mahecha
@miguelmahecha.bsky.social
Earth system data sciences Prof. @UniLeipzig @RSC4Earth related to @UFZ_de @iDiv @SCADS.AI, worried about climate extremes, biodiversity, the human-environment nexus and the 🌎's future in general. Editor @EnvDataScience
You’ll work on spatiotemporal anomaly detection and use explainable AI to link impacts to weather, soil, and human land use—paving the way for better predictions.
One of 34 funded PhD topics at ScaDS.AI Dresden/Leipzig, spanning ML, time series, ethics, and more.
More details below! Check T9.3!
One of 34 funded PhD topics at ScaDS.AI Dresden/Leipzig, spanning ML, time series, ethics, and more.
More details below! Check T9.3!
March 23, 2025 at 10:17 PM
You’ll work on spatiotemporal anomaly detection and use explainable AI to link impacts to weather, soil, and human land use—paving the way for better predictions.
One of 34 funded PhD topics at ScaDS.AI Dresden/Leipzig, spanning ML, time series, ethics, and more.
More details below! Check T9.3!
One of 34 funded PhD topics at ScaDS.AI Dresden/Leipzig, spanning ML, time series, ethics, and more.
More details below! Check T9.3!
Supported primarily by the DeepESDL project @esa.int advised by @ancaanghelea.bsky.social in cooperation with with @brockmannconsult.bsky.social but also supported by @nfdi4earth.bsky.social and @belspo.bsky.social BELSPO via the HERMES projects led by Diego Miralles
March 5, 2025 at 9:42 PM
Supported primarily by the DeepESDL project @esa.int advised by @ancaanghelea.bsky.social in cooperation with with @brockmannconsult.bsky.social but also supported by @nfdi4earth.bsky.social and @belspo.bsky.social BELSPO via the HERMES projects led by Diego Miralles
WHAT? YOU DON'T WANT TO USE IT IN JUPYTER? 😊 No worries! Just visit hashtag#Lexcube www.lexcube.org
This work was led by @soechting.bsky.social with support from Gerik Scheuermann, @dmlmont.bsky.social and myself. I am very proud of my strong team!!!
This work was led by @soechting.bsky.social with support from Gerik Scheuermann, @dmlmont.bsky.social and myself. I am very proud of my strong team!!!
LexCube - Leipzig Explorer of Earth Data Cubes
LexCube is an interactive visualization for large-scale earth data sets. Created at Leipzig University by Maximilian Söchting.
www.lexcube.org
March 5, 2025 at 9:42 PM
WHAT? YOU DON'T WANT TO USE IT IN JUPYTER? 😊 No worries! Just visit hashtag#Lexcube www.lexcube.org
This work was led by @soechting.bsky.social with support from Gerik Scheuermann, @dmlmont.bsky.social and myself. I am very proud of my strong team!!!
This work was led by @soechting.bsky.social with support from Gerik Scheuermann, @dmlmont.bsky.social and myself. I am very proud of my strong team!!!
Introducing #Lexcube4Jupyter
An open-source tool for interactive 3D data cube visualization, seamlessly integrated into scientific workflows. It enables:
✅ Efficient, memory-aware handling of large datasets
✅ Direct integration into Python workflows (e.g., Jupyter Notebooks)
An open-source tool for interactive 3D data cube visualization, seamlessly integrated into scientific workflows. It enables:
✅ Efficient, memory-aware handling of large datasets
✅ Direct integration into Python workflows (e.g., Jupyter Notebooks)
March 5, 2025 at 9:42 PM
Introducing #Lexcube4Jupyter
An open-source tool for interactive 3D data cube visualization, seamlessly integrated into scientific workflows. It enables:
✅ Efficient, memory-aware handling of large datasets
✅ Direct integration into Python workflows (e.g., Jupyter Notebooks)
An open-source tool for interactive 3D data cube visualization, seamlessly integrated into scientific workflows. It enables:
✅ Efficient, memory-aware handling of large datasets
✅ Direct integration into Python workflows (e.g., Jupyter Notebooks)
We believe that interactive (!) visualisation is key to making high-dimensional Earth system data more accessible, interpretable, and actionable. With this you can achieve
✅ Real-time exploration of model outputs & residuals
✅ Quick data quality checks & anomaly detection
✅ Real-time exploration of model outputs & residuals
✅ Quick data quality checks & anomaly detection
March 5, 2025 at 9:42 PM
We believe that interactive (!) visualisation is key to making high-dimensional Earth system data more accessible, interpretable, and actionable. With this you can achieve
✅ Real-time exploration of model outputs & residuals
✅ Quick data quality checks & anomaly detection
✅ Real-time exploration of model outputs & residuals
✅ Quick data quality checks & anomaly detection
This is one outcome of the DeepExtremes project funded by @esa.int excellently guided by @Anca Anghelea! Thank you!
The idea of the paper in a nutshell was already presented by @dmlmont.bsky.social (2025) in Earth System Data Cubes: Avenues for advancing Earth system research. EnvDataSci, 3, e27
The idea of the paper in a nutshell was already presented by @dmlmont.bsky.social (2025) in Earth System Data Cubes: Avenues for advancing Earth system research. EnvDataSci, 3, e27
January 25, 2025 at 9:26 PM
This is one outcome of the DeepExtremes project funded by @esa.int excellently guided by @Anca Anghelea! Thank you!
The idea of the paper in a nutshell was already presented by @dmlmont.bsky.social (2025) in Earth System Data Cubes: Avenues for advancing Earth system research. EnvDataSci, 3, e27
The idea of the paper in a nutshell was already presented by @dmlmont.bsky.social (2025) in Earth System Data Cubes: Avenues for advancing Earth system research. EnvDataSci, 3, e27
From the @mpi-bgc.bsky.social we have @vitusbenson.bsky.social Fabian Gans @clair3rbn.bsky.social and Melanie Weynants and from @brockmannconsult.bsky.social we have the amazing Tonio Fincke!
January 25, 2025 at 9:26 PM
From the @mpi-bgc.bsky.social we have @vitusbenson.bsky.social Fabian Gans @clair3rbn.bsky.social and Melanie Weynants and from @brockmannconsult.bsky.social we have the amazing Tonio Fincke!
Authors Uni Leipzig: @chaonanji.bsky.social @gdkrmr.bsky.social @martinuzzi.bsky.social @dmlmont.bsky.social @soechting.bsky.social Karin Mora. Uni Valencia: @isp-uv-es.bsky.social with Gustau Camps-Valls, Miguel Ángel Fernández Torres, J Pellicer-Valero, Oscar J Pellicer-Valero,
LinkedIn
This link will take you to a page that’s not on LinkedIn
lnkd.in
January 25, 2025 at 9:26 PM
Authors Uni Leipzig: @chaonanji.bsky.social @gdkrmr.bsky.social @martinuzzi.bsky.social @dmlmont.bsky.social @soechting.bsky.social Karin Mora. Uni Valencia: @isp-uv-es.bsky.social with Gustau Camps-Valls, Miguel Ángel Fernández Torres, J Pellicer-Valero, Oscar J Pellicer-Valero,
Please find the paper here: rdcu.be/d7udC Ji, C., Fincke, T., Benson, V. et al. DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts. Sci Data 12, 149 (2025). lnkd.in/en4ZHt3F
DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts
Scientific Data - DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts
rdcu.be
January 25, 2025 at 9:26 PM
Please find the paper here: rdcu.be/d7udC Ji, C., Fincke, T., Benson, V. et al. DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts. Sci Data 12, 149 (2025). lnkd.in/en4ZHt3F
🌿 The dataset focuses on sampling areas impacted by climate extremes, across diverse vegetation types. By prioritizing compound heatwave and drought events, it provides a globally representative and reproducible resource for studying these phenomena!
January 25, 2025 at 9:26 PM
🌿 The dataset focuses on sampling areas impacted by climate extremes, across diverse vegetation types. By prioritizing compound heatwave and drought events, it provides a globally representative and reproducible resource for studying these phenomena!
💡 DeepExtremeCubes is a new database designed to address this gap. 📊 Key features of DeepExtremeCubes: 40,000 globally sampled mini data cubes (2.5 x 2.5 km) with Sentinel-2 L2A for vegetation monitoring, ERA5-Land variables, and ancillary data, including land cover and topography maps.
January 25, 2025 at 9:26 PM
💡 DeepExtremeCubes is a new database designed to address this gap. 📊 Key features of DeepExtremeCubes: 40,000 globally sampled mini data cubes (2.5 x 2.5 km) with Sentinel-2 L2A for vegetation monitoring, ERA5-Land variables, and ancillary data, including land cover and topography maps.