Mathieu Lapôtre

@marslogander.bsky.social

Associate Prof @ Stanford, Planetary Geologist. I study planetary surface processes and what they can tell us about hydrology, climate, and habitability. 🏳️‍🌈 http://epsp.stanford.edu

Jusqu’ici, les géologues pensaient que les plantes avaient fait naître les rivières en méandres - ces grands cours d'eau en forme de S. Une nouvelle étude montre qu’elles existaient déjà avant : la végétation a seulement modifié leur façon de bouger 🌱 Explications avec du GIF végétal ⬇️

La végétation a sculpté la forme des rivières

Jusqu’ici, les géologues pensaient que les plantes avaient fait naître les rivières en méandres - ces grands cours d'eau en forme de S. Une nouvelle étude montre qu’elles existaient déjà avant : la vé...

radiofrance.fr

New paper by PhD student @mcolinmarvin.bsky.social uses #patterns formed by #dunes to better understand sources, pathways, and sinks of #sand on #Titan. Spoiler: #Xanadu has outsized influence on #eolian sediments, and sand travels far!! @stanforddoerr.bsky.social

M. Colin Marvin@mcolinmarvin.bsky.social · last yr.

Check out our paper in @agu.org where we provide evidence for a continuous transport pathway around Titan’s equatorial dune fields, only interrupted by the Xanadu region (with implications for the nature of Titan’s sand grains!) agupubs.onlinelibrary.wiley.com/doi/full/10....

Just off the press: new paper by former @StanfordEarth postdoc @_algunn, now lecturer @MonashEAE analyzing spatial and temporal patterns in sand accumulation in impact craters on #Mars. Suggests enhanced sediment production in L. Noachian-E. Hesperian! doi.org/10.1130/G49936…

Accumulation of windblown sand in impact craters on Mars | Geology | GeoScienceWorld

Abstract. Loose sand, blown away from source regions by winds, is transported across Mars's surface into sand sheets and dunes and accumulates within

doi.org

Wrapping up a week of #Mars analog fieldwork in 🇮🇸 with the incredible SAND-E team @TAMU @PurdueEAPS @StanfordEarth @MissionCtrlSS @NASA w/ Ryan Ewing, Liz Rampe, @ironywithab @MasonKashauna @MarionNach @mikethorpe_geo @bedford_candice @mhasson7 @rudolpa and many others!

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Wanna learn more about how to map surface winds on Mars from dunes using machine learning? Make sure to check out @Liorruba’s #vEGU21 invited presentation @ 9:05 am CEST/12:05 am PDT! Abstract:@EuroGeosciences @StanfordEarth meetingorganizer.copernicus.org/EGU21/EGU21-12…

CO Meeting Organizer EGU21

The surface of Mars is riddled with dunes that form by accumulating sand particles that are carried by the wind. Since dune geometry and orientation adjust in response to prevailing wind conditions, the morphometrics of dunes can reveal information about the winds that formed them. Previous studies inferred the prevailing local wind direction from the orientation of dunes by manually analyzing spacecraft imagery. However, building a global map remained challenging, as manual detection of individual dunes over the entire Martian surface is impractical. Here, we employ Mask R-CNN, a state-of-the-art instance segmentation neural network, to detect and analyze isolated barchan dunes on a global scale.We prepared a training dataset by extracting Mars Context Camera (CTX) scenes of dune fields from a global CTX mosaic, as identified in the global dune-fields catalog. Images were cropped and standardized to a resolution of 832x832 pixels, and labeled using Labelbox’s online instance segmentation platform. Image augmentation and weight decay were employed to prevent overfitting during training. By inspecting 100 sample images from the validation database, we find that the network correctly identified ~86% of the isolated dunes, falsely identifying one feature as a barchan dune in a single image.

meetingorganizer.copernicus.org