Change predictions based on my and Patrick Ebel 's method in Mariupol over the last month, which subsequently would require ground truth confirmations. This may be areas impacted by explosion, but also other changes. Note that the method does not use any post-event optical image.

The challenge we tackle is that of combining the accuracy of sparse in-situ data with the dense coverage of global atmosphere and ocean state products. While the latter are available worldwide, in-situ infrastructure is often limited for communities most at risk of such hazards.

Our approach aims to densify sparsely deployed but precise in-situ measurements on a global scale. This is accomplished by e.g. broadcasting forecasts from gauged to ungauged sites, input data dropout and auxiliary supervision.

Exciting news: Dr. Ebel Patrick Ebel has successfully defended his PhD on #cloudremoval in #AI4EO . Congrats, Patrick! 🎉 In my view, he did significant contributions towards #trustworthy and #scalable cloud removal in satellite images for real world applications.

Elber Nabuco Silveira De Carvalho 🔰 TheYellows 🔰 ..xiaoxuuu🎧🎶 Nmsl Dr. Ing. Thomas Duriez Norana ❛ # yani ; rpwp ꒱ ぱこさん 🩵نور🩵 ほげぇた Patrick Ebel ちろちゃん☆チロくま @biblewcp2512 Sunnysuz 🟧🇺🇸🇺🇦🌻 Abbas Akbar @omer_eren17 Betterkeepcalm G REX KABURU 🔰 TME 🔰

LBank.com 똥코인 (DongCoin) pedro Patrick Ebel @owueb

Patrick Ebel #CVPR2024 EarthVision YES!

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Patrick Ebel

I and Patrick Ebel stressed the importance of change detection systems that can work without post-change optical data (e.g., ieeexplore.ieee.org/document/95383…). Ukraine crisis further confirms it, there is hardly any cloud-free optical S2 image there so far. #remotesensing #AI #disastermapping

on a related matter, also see our Master student Ziqi’s work on “Explicit Haze & Cloud Removal for Global Land Cover Classification” presented earlier this year sites.google.com/view/rainfores…

Take a look at our recent paper by Jakob Gawlikowski Patrick Ebel Xiaoxiang ZHU et al on how clouds affect #EarthObservation downstream applications. #AI4EO

Patrick Ebel Robin Cole Thank you for the kind words Patrick Ebel - also, those interested in cloud removal problems should definitely check out Patrick’s excellent works like DSen2-CR, GLF-CR (among many others) as well as their related datasets!

Please check out the pre-print for more information.

Thanks to my co-authors at @ESA and elsewhere: Brandon, Peter, Gabriele, Federico and Rochelle Schneider!

… and stay tuned for more follow-up work from @zhu_lab on this topic and others :)

Hao Zhu Lab whoops I’m still figuring out this Twitter thing :) let’s try again with Zhu Lab then ;)

Patrick Ebel wrong zhu lab but thanks for the shout out!! great work!