Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Prapas, Ioannis"'
Autor:
Camps-Valls, Gustau, Fernández-Torres, Miguel-Ángel, Cohrs, Kai-Hendrik, Höhl, Adrian, Castelletti, Andrea, Pacal, Aytac, Robin, Claire, Martinuzzi, Francesco, Papoutsis, Ioannis, Prapas, Ioannis, Pérez-Aracil, Jorge, Weigel, Katja, Gonzalez-Calabuig, Maria, Reichstein, Markus, Rabel, Martin, Giuliani, Matteo, Mahecha, Miguel, Popescu, Oana-Iuliana, Pellicer-Valero, Oscar J., Ouala, Said, Salcedo-Sanz, Sancho, Sippel, Sebastian, Kondylatos, Spyros, Happé, Tamara, Williams, Tristan
In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. However, the latter
Externí odkaz:
http://arxiv.org/abs/2406.20080
Autor:
Michail, Dimitrios, Panagiotou, Lefki-Ioanna, Davalas, Charalampos, Prapas, Ioannis, Kondylatos, Spyros, Bountos, Nikolaos Ioannis, Papoutsis, Ioannis
With climate change expected to exacerbate fire weather conditions, the accurate anticipation of wildfires on a global scale becomes increasingly crucial for disaster mitigation. In this study, we utilize SeasFire, a comprehensive global wildfire dat
Externí odkaz:
http://arxiv.org/abs/2404.06437
Autor:
Zhao, Shan, Prapas, Ioannis, Karasante, Ilektra, Xiong, Zhitong, Papoutsis, Ioannis, Camps-Valls, Gustau, Zhu, Xiao Xiang
Wildfire forecasting is notoriously hard due to the complex interplay of different factors such as weather conditions, vegetation types and human activities. Deep learning models show promise in dealing with this complexity by learning directly from
Externí odkaz:
http://arxiv.org/abs/2403.08414
Autor:
Karasante, Ilektra, Alonso, Lazaro, Prapas, Ioannis, Ahuja, Akanksha, Carvalhais, Nuno, Papoutsis, Ioannis
The global occurrence, scale, and frequency of wildfires pose significant threats to ecosystem services and human livelihoods. To effectively quantify and attribute the antecedent conditions for wildfires, a thorough understanding of Earth system dyn
Externí odkaz:
http://arxiv.org/abs/2312.07199
Autor:
Prapas, Ioannis, Bountos, Nikolaos Ioannis, Kondylatos, Spyros, Michail, Dimitrios, Camps-Valls, Gustau, Papoutsis, Ioannis
Wildfires are increasingly exacerbated as a result of climate change, necessitating advanced proactive measures for effective mitigation. It is important to forecast wildfires weeks and months in advance to plan forest fuel management, resource procu
Externí odkaz:
http://arxiv.org/abs/2306.10940
We introduce Mesogeos, a large-scale multi-purpose dataset for wildfire modeling in the Mediterranean. Mesogeos integrates variables representing wildfire drivers (meteorology, vegetation, human activity) and historical records of wildfire ignitions
Externí odkaz:
http://arxiv.org/abs/2306.05144
Autor:
Boehm, Vanessa, Leong, Wei Ji, Mahesh, Ragini Bal, Prapas, Ioannis, Nemni, Edoardo, Kalaitzis, Freddie, Ganju, Siddha, Ramos-Pollán, Raul
This work aims to produce landslide density estimates using Synthetic Aperture Radar (SAR) satellite imageries to prioritise emergency resources for rapid response. We use the United States Geological Survey (USGS) Landslide Inventory data annotated
Externí odkaz:
http://arxiv.org/abs/2211.10338
Autor:
Böhm, Vanessa, Leong, Wei Ji, Mahesh, Ragini Bal, Prapas, Ioannis, Nemni, Edoardo, Kalaitzis, Freddie, Ganju, Siddha, Ramos-Pollan, Raul
Rapid assessment after a natural disaster is key for prioritizing emergency resources. In the case of landslides, rapid assessment involves determining the extent of the area affected and measuring the size and location of individual landslides. Synt
Externí odkaz:
http://arxiv.org/abs/2211.09927
Autor:
Boehm, Vanessa, Leong, Wei Ji, Mahesh, Ragini Bal, Prapas, Ioannis, Nemni, Edoardo, Kalaitzis, Freddie, Ganju, Siddha, Ramos-Pollan, Raul
With climate change predicted to increase the likelihood of landslide events, there is a growing need for rapid landslide detection technologies that help inform emergency responses. Synthetic Aperture Radar (SAR) is a remote sensing technique that c
Externí odkaz:
http://arxiv.org/abs/2211.02869
Autor:
Prapas, Ioannis, Ahuja, Akanksha, Kondylatos, Spyros, Karasante, Ilektra, Panagiotou, Eleanna, Alonso, Lazaro, Davalas, Charalampos, Michail, Dimitrios, Carvalhais, Nuno, Papoutsis, Ioannis
Climate change is expected to aggravate wildfire activity through the exacerbation of fire weather. Improving our capabilities to anticipate wildfires on a global scale is of uttermost importance for mitigating their negative effects. In this work, w
Externí odkaz:
http://arxiv.org/abs/2211.00534