David Montero Loaiza
@dmlmont.bsky.social
Creator of #AwesomeSpectralIndices | #eemont | #spectral
PhD Student @RSC4Earth
#EarthEngine GDE
PhD Student @RSC4Earth
#EarthEngine GDE
BIG NEWS! 😁 I'm happy to announce that cubo v2024.1.0 can create cubes from Google Earth Engine in addition to STAC catalogues!
gh: github.com/ESDS-Leipzig...
Check the tutorial here: cubo.readthedocs.io/en/latest/tu...
gh: github.com/ESDS-Leipzig...
Check the tutorial here: cubo.readthedocs.io/en/latest/tu...
January 22, 2024 at 12:47 PM
BIG NEWS! 😁 I'm happy to announce that cubo v2024.1.0 can create cubes from Google Earth Engine in addition to STAC catalogues!
gh: github.com/ESDS-Leipzig...
Check the tutorial here: cubo.readthedocs.io/en/latest/tu...
gh: github.com/ESDS-Leipzig...
Check the tutorial here: cubo.readthedocs.io/en/latest/tu...
Reposted by David Montero Loaiza
Big news from #Lexcube! 🌍 We have released Lexcube for Jupyter, an open-source Jupyter notebook extension that allows everyone to visualize their own 3D data as interactive data cubes, right in their notebooks! And the best part: it is as easy as plotting a 2D figure! github.com/msoechting/l...
January 18, 2024 at 12:14 PM
Big news from #Lexcube! 🌍 We have released Lexcube for Jupyter, an open-source Jupyter notebook extension that allows everyone to visualize their own 3D data as interactive data cubes, right in their notebooks! And the best part: it is as easy as plotting a 2D figure! github.com/msoechting/l...
Reposted by David Montero Loaiza
The Planetary Boundary concept is based on a strong visualisation. However, we argue that (1) the PB figure exaggerate via quadratic scaling of effect sizes, (2) colour gradations are highly non-linear, and (1)+(2) amplifies the perception of high-risk areas: egusphere.copernicus.org/preprints/20...
December 11, 2023 at 11:54 AM
The Planetary Boundary concept is based on a strong visualisation. However, we argue that (1) the PB figure exaggerate via quadratic scaling of effect sizes, (2) colour gradations are highly non-linear, and (1)+(2) amplifies the perception of high-risk areas: egusphere.copernicus.org/preprints/20...
Reposted by David Montero Loaiza
Researchers often use interpretable machine learning tools like feature importances to identify drivers, but cross-validation strategy used can affect these results: Our open access study in AIES doi.org/10.1175/AIES... (with co-authors Jakob Zscheischler, Christoph Müller, Mohit Anand)
Cross-Validation Strategy Impacts the Performance and Interpretation of Machine Learning Models
Abstract Machine learning algorithms are able to capture complex, nonlinear, interacting relationships and are increasingly used to predict agricultural yield variability at regional and national scal...
doi.org
October 16, 2023 at 11:09 AM
Researchers often use interpretable machine learning tools like feature importances to identify drivers, but cross-validation strategy used can affect these results: Our open access study in AIES doi.org/10.1175/AIES... (with co-authors Jakob Zscheischler, Christoph Müller, Mohit Anand)
Reposted by David Montero Loaiza
My amazing PhD student Maximilan Söchting published his first paper on a fully interactive viewer for very large Earth data: www.lexcube.org Please try it out! Paper published in IEEE Computer Graphics and Applications ieeexplore.ieee.org/document/102...
October 18, 2023 at 9:21 AM
My amazing PhD student Maximilan Söchting published his first paper on a fully interactive viewer for very large Earth data: www.lexcube.org Please try it out! Paper published in IEEE Computer Graphics and Applications ieeexplore.ieee.org/document/102...
Reposted by David Montero Loaiza
Happy for PhD cand Francesco Martinuzzi for having is paper in discussion comparing various RNNs in modelling vegetation responses ... there are still arguments for #ESNs, but all models struggled to capture impact of extremes. More research needed! 🌱🌍 🔗https://doi.org/10.5194/egusphere-2023-2368
October 18, 2023 at 9:35 AM
Happy for PhD cand Francesco Martinuzzi for having is paper in discussion comparing various RNNs in modelling vegetation responses ... there are still arguments for #ESNs, but all models struggled to capture impact of extremes. More research needed! 🌱🌍 🔗https://doi.org/10.5194/egusphere-2023-2368