Martin Jung

Affiliations:
  • Max Planck Institute for Biogeochemistry, Jena, Germany


According to our database1, Martin Jung authored at least 13 papers between 2013 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

Online presence:

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Bibliography

2022
Observation-based assessment of secondary water effects on seasonal vegetation decay across Africa.
Frontiers Big Data, 2022

2019
Deep learning and process understanding for data-driven Earth system science.
Nat., 2019

Identifying Dynamic Memory Effects on Vegetation State Using Recurrent Neural Networks.
Frontiers Big Data, 2019

2018
Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data.
Remote. Sens., 2018

The FLUXCOM ensemble of global land-atmosphere energy fluxes.
CoRR, 2018

Assessing the relationship between microwave vegetation optical depth and gross primary production.
Int. J. Appl. Earth Obs. Geoinformation, 2018

Modelling Landsurface Time-Series with Recurrent Neural Nets.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

SMOS Vegetation Optical Depth and Ecosystem Functional Properties: Exploring Their Relationships in Tropical Forests.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Compensatory water effects link yearly global land CO<sub>2</sub> sink changes to temperature.
Nat., 2017

2015
Ranking drivers of global carbon and energy fluxes over land.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2014
1982-2010 Trends of Light Use Efficiency and Inherent Water Use Efficiency in African vegetation: Sensitivity to Climate and Atmospheric CO<sub>2</sub> Concentrations.
Remote. Sens., 2014

2013
A Guided Hybrid Genetic Algorithm for Feature Selection with Expensive Cost Functions.
Proceedings of the International Conference on Computational Science, 2013

Estimating Basal Area of Spruce and Fir in Post-Fire Residual Stands in Central Siberia Using Quickbird, Feature Selection, and Random Forests.
Proceedings of the International Conference on Computational Science, 2013


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