Zobrazeno 1 - 10
of 387
pro vyhledávání: '"Mahecha, Miguel D."'
Autor:
Pellicer-Valero, Oscar J., Fernández-Torres, Miguel-Ángel, Ji, Chaonan, Mahecha, Miguel D., Camps-Valls, Gustau
With climate change-related extreme events on the rise, high dimensional Earth observation data presents a unique opportunity for forecasting and understanding impacts on ecosystems. This is, however, impeded by the complexity of processing, visualiz
Externí odkaz:
http://arxiv.org/abs/2410.01770
Vegetation often understood merely as the result of long-term climate conditions. However, vegetation itself plays a fundamental role in shaping Earth's climate by regulating the energy, water, and biogeochemical cycles across terrestrial landscapes.
Externí odkaz:
http://arxiv.org/abs/2409.04872
Autor:
Montero, David, Kraemer, Guido, Anghelea, Anca, Aybar, César, Brandt, Gunnar, Camps-Valls, Gustau, Cremer, Felix, Flik, Ida, Gans, Fabian, Habershon, Sarah, Ji, Chaonan, Kattenborn, Teja, Martínez-Ferrer, Laura, Martinuzzi, Francesco, Reinhardt, Martin, Söchting, Maximilian, Teber, Khalil, Mahecha, Miguel D.
Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by moderate to high spatio-temporal resolutions. Earth System Data Cubes (ESDCs) have emerged
Externí odkaz:
http://arxiv.org/abs/2408.02348
Understanding the dynamics of the land-atmosphere exchange of CO$_2$ is key to advance our predictive capacities of the coupled climate-carbon feedback system. In essence, the net vegetation flux is the difference of the uptake of CO$_2$ via photosyn
Externí odkaz:
http://arxiv.org/abs/2407.19237
Autor:
Ji, Chaonan, Fincke, Tonio, Benson, Vitus, Camps-Valls, Gustau, Fernandez-Torres, Miguel-Angel, Gans, Fabian, Kraemer, Guido, Martinuzzi, Francesco, Montero, David, Mora, Karin, Pellicer-Valero, Oscar J., Robin, Claire, Soechting, Maximilian, Weynants, Melanie, Mahecha, Miguel D.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-re
Externí odkaz:
http://arxiv.org/abs/2406.18179
The Sentinel-2 (S2) mission from the European Space Agency's Copernicus program provides essential data for Earth surface analysis. Its Level-2A products deliver high-to-medium resolution (10-60 m) surface reflectance (SR) data through the MultiSpect
Externí odkaz:
http://arxiv.org/abs/2404.15812
Autor:
Montero, David, Aybar, César, Ji, Chaonan, Kraemer, Guido, Söchting, Maximilian, Teber, Khalil, Mahecha, Miguel D.
Advancements in Earth system science have seen a surge in diverse datasets. Earth System Data Cubes (ESDCs) have been introduced to efficiently handle this influx of high-dimensional data. ESDCs offer a structured, intuitive framework for data analys
Externí odkaz:
http://arxiv.org/abs/2404.13105
Autor:
Montero, David, Mahecha, Miguel D., Martinuzzi, Francesco, Aybar, César, Klosterhalfen, Anne, Knohl, Alexander, Koebsch, Franziska, Anaya, Jesús, Wieneke, Sebastian
Accurate quantification of Gross Primary Production (GPP) is crucial for understanding terrestrial carbon dynamics. It represents the largest atmosphere-to-land CO$_2$ flux, especially significant for forests. Eddy Covariance (EC) measurements are wi
Externí odkaz:
http://arxiv.org/abs/2404.12745
Publikováno v:
Journal of Machine Learning Research 23 (2022) 1-8
We introduce ReservoirComputing.jl, an open source Julia library for reservoir computing models. The software offers a great number of algorithms presented in the literature, and allows to expand on them with both internal and external tools in a sim
Externí odkaz:
http://arxiv.org/abs/2204.05117
Autor:
Mahecha, Miguel D.1,2,3 (AUTHOR) miguel.mahecha@uni-leipzig.de, Kraemer, Guido3 (AUTHOR), Crameri, Fabio4,5 (AUTHOR)
Publikováno v:
Earth System Dynamics. 2024, Vol. 15 Issue 4, p1153-1159. 7p.
