activity
20192022
most citedLearning to forecast vegetation greenness at fine resolution over Africa with ConvLSTMs

17 citations · 19 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG202217 cited

Learning to forecast vegetation greenness at fine resolution over Africa with ConvLSTMs

Claire Robin, Christian Requena-Mesa, Vitus Benson +4

Forecasting the state of vegetation in response to climate and weather events is a major challenge. Its implementation will prove crucial in predicting crop yield, forest damage, o…

cs.LG20212 cited

EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task

Christian Requena-Mesa, Vitus Benson, Markus Reichstein +2

Satellite images are snapshots of the Earth surface. We propose to forecast them. We frame Earth surface forecasting as the task of predicting satellite imagery conditioned on futu…

cs.LG2020

EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts

Christian Requena-Mesa, Vitus Benson, Joachim Denzler +2

Climate change is global, yet its concrete impacts can strongly vary between different locations in the same region. Seasonal weather forecasts currently operate at the mesoscale (…

cs.CV2020

Physics-informed GANs for Coastal Flood Visualization

Björn Lütjens, Brandon Leshchinskiy, Christian Requena-Mesa +8

As climate change increases the intensity of natural disasters, society needs better tools for adaptation. Floods, for example, are the most frequent natural disaster, but during h…

cs.CV2019

Predicting Landscapes from Environmental Conditions Using Generative Networks

Christian Requena-Mesa, Markus Reichstein, Miguel Mahecha +2

Landscapes are meaningful ecological units that strongly depend on the environmental conditions. Such dependencies between landscapes and the environment have been noted since the…