Articles | Volume 11, issue 1
https://doi.org/10.5194/esd-11-201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-11-201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
25 Feb 2020
Research article | Highlight paper |
| 25 Feb 2020
| 25 Feb 2020
Earth system data cubes unravel global multivariate dynamics
Miguel D. Mahecha
CORRESPONDING AUTHOR
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, Leipzig, Germany
Michael Stifel Center Jena for Data-Driven and Simulation Science, Jena, Germany
Fabian Gans
CORRESPONDING AUTHOR
Max Planck Institute for Biogeochemistry, Jena, Germany
Gunnar Brandt
Brockmann Consult GmbH, Hamburg, Germany
Rune Christiansen
Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
Sarah E. Cornell
Stockholm Resilience Center, Stockholm University, Stockholm, Sweden
Normann Fomferra
Brockmann Consult GmbH, Hamburg, Germany
Guido Kraemer
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, Leipzig, Germany
Image Processing Lab, Universitat de València, Paterna, Spain
Jonas Peters
Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
Paul Bodesheim
Max Planck Institute for Biogeochemistry, Jena, Germany
Computer Vision Group, Friedrich Schiller University Jena, Jena, Germany
Gustau Camps-Valls
Image Processing Lab, Universitat de València, Paterna, Spain
Jonathan F. Donges
Stockholm Resilience Center, Stockholm University, Stockholm, Sweden
Earth System Analysis, Potsdam Institute for Climate Impact Research, PIK, Potsdam, Germany
Wouter Dorigo
Department of Geodesy and Geo-Information, TU Wien, Vienna, Austria
Lina M. Estupinan-Suarez
Max Planck Institute for Biogeochemistry, Jena, Germany
Department of Geography, Friedrich Schiller University Jena, Jena, Germany
Victor H. Gutierrez-Velez
Department of Geography and Urban Studies, Temple University, Philadelphia, PA, USA
Martin Gutwin
Max Planck Institute for Biogeochemistry, Jena, Germany
Department of Geography, Friedrich Schiller University Jena, Jena, Germany
Martin Jung
Max Planck Institute for Biogeochemistry, Jena, Germany
Maria C. Londoño
Alexander von Humboldt Biological Resources Research Institute, Bogotá, Colombia
Diego G. Miralles
Hydro-Climate Extremes Lab (H-CEL), Ghent, Belgium
Phillip Papastefanou
TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
Markus Reichstein
Max Planck Institute for Biogeochemistry, Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, Leipzig, Germany
Michael Stifel Center Jena for Data-Driven and Simulation Science, Jena, Germany
Viewed
Total article views: 13,829 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 09 Oct 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 10,737 | 2,969 | 123 | 13,829 | 179 | 161 |
- HTML: 10,737
- PDF: 2,969
- XML: 123
- Total: 13,829
- BibTeX: 179
- EndNote: 161
Total article views: 11,980 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 25 Feb 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 9,679 | 2,186 | 115 | 11,980 | 154 | 144 |
- HTML: 9,679
- PDF: 2,186
- XML: 115
- Total: 11,980
- BibTeX: 154
- EndNote: 144
Total article views: 1,849 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 09 Oct 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,058 | 783 | 8 | 1,849 | 25 | 17 |
- HTML: 1,058
- PDF: 783
- XML: 8
- Total: 1,849
- BibTeX: 25
- EndNote: 17
Viewed (geographical distribution)
Total article views: 13,829 (including HTML, PDF, and XML)
Thereof 12,456 with geography defined
and 1,373 with unknown origin.
Total article views: 11,980 (including HTML, PDF, and XML)
Thereof 10,774 with geography defined
and 1,206 with unknown origin.
Total article views: 1,849 (including HTML, PDF, and XML)
Thereof 1,682 with geography defined
and 167 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
48 citations as recorded by crossref.
- Developing polar data-cylinders to map spatiotemporal changes in Arctic sea ice D. Kontou 10.1080/21681376.2022.2074306
- Think global, cube local: an Earth Observation Data Cube’s contribution to the Digital Earth vision M. Sudmanns et al. 10.1080/20964471.2022.2099236
- The AIDE Toolbox: Artificial intelligence for disentangling extreme events [Software and Data Sets] M. Gonzalez-Calabuig et al. 10.1109/MGRS.2024.3382544
- A Framework for Multivariate Analysis of Land Surface Dynamics and Driving Variables—A Case Study for Indo-Gangetic River Basins S. Uereyen et al. 10.3390/rs14010197
- The Low Dimensionality of Development G. Kraemer et al. 10.1007/s11205-020-02349-0
- Lexcube: Interactive Visualization of Large Earth System Data Cubes M. Söchting et al. 10.1109/MCG.2023.3321989
- Gaussianizing the Earth: Multidimensional information measures for Earth data analysis J. Johnson et al. 10.1109/MGRS.2021.3066260
- Spatial Patterns of Vegetation Activity Related to ENSO in Northern South America L. Estupinan‐Suarez et al. 10.1029/2022JG007344
- Enabling coastal analytics at planetary scale F. Calkoen et al. 10.1016/j.envsoft.2024.106257
- Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins S. Uereyen et al. 10.1016/j.scitotenv.2022.157515
- Earth Video Cube: A Geospatial Data Cube for Multisource Earth Observation Video Management and Analysis Z. Li et al. 10.1109/JSTARS.2024.3358342
- A ConvNets-based approach for capturing the heterogeneity of spatial domain in parallel geoprocessing F. Gao et al. 10.1080/17538947.2024.2398066
- Geospatial Information Research: State of the Art, Case Studies and Future Perspectives R. Bill et al. 10.1007/s41064-022-00217-9
- DSTree: A Spatio-Temporal Indexing Data Structure for Distributed Networks M. Hojati et al. 10.3390/mca29030042
- RTGDC: a real-time ingestion and processing approach in geospatial data cube for digital twin of earth R. Liu et al. 10.1080/17538947.2024.2365386
- Spatiotemporal multi-resolution approximations for analyzing global environmental data M. Appel & E. Pebesma 10.1016/j.spasta.2020.100465
- Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities C. Persello et al. 10.1109/MGRS.2021.3136100
- Learning extreme vegetation response to climate drivers with recurrent neural networks F. Martinuzzi et al. 10.5194/npg-31-535-2024
- Limited climate change mitigation potential through forestation of the vast dryland regions S. Rohatyn et al. 10.1126/science.abm9684
- Differentiable modelling to unify machine learning and physical models for geosciences C. Shen et al. 10.1038/s43017-023-00450-9
- A Regional Earth System Data Lab for Understanding Ecosystem Dynamics: An Example from Tropical South America L. Estupinan-Suarez et al. 10.3389/feart.2021.613395
- Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation C. Bonannella et al. 10.7717/peerj.15593
- Summarizing the state of the terrestrial biosphere in few dimensions G. Kraemer et al. 10.5194/bg-17-2397-2020
- Domain knowledge-driven variational recurrent networks for drought monitoring M. Zhang et al. 10.1016/j.rse.2024.114252
- Spectral Dependence H. Ombao & M. Pinto 10.1016/j.ecosta.2022.10.005
- Ecodatacube.eu: analysis-ready open environmental data cube for Europe M. Witjes et al. 10.7717/peerj.15478
- Kernel methods and their derivatives: Concept and perspectives for the earth system sciences J. Johnson et al. 10.1371/journal.pone.0235885
- Ecosystems are showing symptoms of resilience loss J. Rocha 10.1088/1748-9326/ac73a8
- A multi-source spatio-temporal data cube for large-scale geospatial analysis F. Gao et al. 10.1080/13658816.2022.2087222
- Quantum Tensor DBMS and Quantum Gantt Charts: Towards Exponentially Faster Earth Data Engineering R. Rodriges Zalipynis 10.3390/earth5030027
- Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data S. Biass et al. 10.5194/nhess-22-2829-2022
- Toward Causal Inference for Spatio-Temporal Data: Conflict and Forest Loss in Colombia R. Christiansen et al. 10.1080/01621459.2021.2013241
- Research into land atmosphere interactions supports the sustainable development agenda G. Hayman et al. 10.1017/sus.2024.3
- Crowd‐sourced plant occurrence data provide a reliable description of macroecological gradients M. Mahecha et al. 10.1111/ecog.05492
- Time‐Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity N. Linscheid et al. 10.1029/2021GL093285
- The Austrian Semantic EO Data Cube Infrastructure M. Sudmanns et al. 10.3390/rs13234807
- Flood susceptibility mapping to improve models of species distributions E. Ebrahimi et al. 10.1016/j.ecolind.2023.111250
- Gap‐Filled Multivariate Observations of Global Land–Climate Interactions V. Bessenbacher et al. 10.1029/2023JD039099
- Potential of Recurrence Metrics from Sentinel-1 Time Series for Deforestation Mapping F. Cremer et al. 10.1109/JSTARS.2020.3019333
- CloudSEN12, a global dataset for semantic understanding of cloud and cloud shadow in Sentinel-2 C. Aybar et al. 10.1038/s41597-022-01878-2
- Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review M. E. D. Chaves et al. 10.3390/rs12183062
- A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research D. Montero et al. 10.1038/s41597-023-02096-0
- An In-Memory Data-Cube Aware Distributed Data Discovery Across Clouds for Remote Sensing Big Data J. Song et al. 10.1109/JSTARS.2023.3267118
- Multivariate analysis of land surface dynamics in Central Asia: patterns of trends and drivers under a changing climate S. Uereyen et al. 10.1080/15481603.2024.2364461
- A framework for the detection and attribution of biodiversity change A. Gonzalez et al. 10.1098/rstb.2022.0182
- Scaling‐up biodiversity‐ecosystem functioning research A. Gonzalez et al. 10.1111/ele.13456
- Towards a global understanding of vegetation–climate dynamics at multiple timescales N. Linscheid et al. 10.5194/bg-17-945-2020
- OpenEOcubes: an open-source and lightweight R-based RESTful web service for analyzing earth observation data cubes B. Pondi et al. 10.1007/s12145-024-01249-y
44 citations as recorded by crossref.
- Developing polar data-cylinders to map spatiotemporal changes in Arctic sea ice D. Kontou 10.1080/21681376.2022.2074306
- Think global, cube local: an Earth Observation Data Cube’s contribution to the Digital Earth vision M. Sudmanns et al. 10.1080/20964471.2022.2099236
- The AIDE Toolbox: Artificial intelligence for disentangling extreme events [Software and Data Sets] M. Gonzalez-Calabuig et al. 10.1109/MGRS.2024.3382544
- A Framework for Multivariate Analysis of Land Surface Dynamics and Driving Variables—A Case Study for Indo-Gangetic River Basins S. Uereyen et al. 10.3390/rs14010197
- The Low Dimensionality of Development G. Kraemer et al. 10.1007/s11205-020-02349-0
- Lexcube: Interactive Visualization of Large Earth System Data Cubes M. Söchting et al. 10.1109/MCG.2023.3321989
- Gaussianizing the Earth: Multidimensional information measures for Earth data analysis J. Johnson et al. 10.1109/MGRS.2021.3066260
- Spatial Patterns of Vegetation Activity Related to ENSO in Northern South America L. Estupinan‐Suarez et al. 10.1029/2022JG007344
- Enabling coastal analytics at planetary scale F. Calkoen et al. 10.1016/j.envsoft.2024.106257
- Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins S. Uereyen et al. 10.1016/j.scitotenv.2022.157515
- Earth Video Cube: A Geospatial Data Cube for Multisource Earth Observation Video Management and Analysis Z. Li et al. 10.1109/JSTARS.2024.3358342
- A ConvNets-based approach for capturing the heterogeneity of spatial domain in parallel geoprocessing F. Gao et al. 10.1080/17538947.2024.2398066
- Geospatial Information Research: State of the Art, Case Studies and Future Perspectives R. Bill et al. 10.1007/s41064-022-00217-9
- DSTree: A Spatio-Temporal Indexing Data Structure for Distributed Networks M. Hojati et al. 10.3390/mca29030042
- RTGDC: a real-time ingestion and processing approach in geospatial data cube for digital twin of earth R. Liu et al. 10.1080/17538947.2024.2365386
- Spatiotemporal multi-resolution approximations for analyzing global environmental data M. Appel & E. Pebesma 10.1016/j.spasta.2020.100465
- Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities C. Persello et al. 10.1109/MGRS.2021.3136100
- Learning extreme vegetation response to climate drivers with recurrent neural networks F. Martinuzzi et al. 10.5194/npg-31-535-2024
- Limited climate change mitigation potential through forestation of the vast dryland regions S. Rohatyn et al. 10.1126/science.abm9684
- Differentiable modelling to unify machine learning and physical models for geosciences C. Shen et al. 10.1038/s43017-023-00450-9
- A Regional Earth System Data Lab for Understanding Ecosystem Dynamics: An Example from Tropical South America L. Estupinan-Suarez et al. 10.3389/feart.2021.613395
- Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation C. Bonannella et al. 10.7717/peerj.15593
- Summarizing the state of the terrestrial biosphere in few dimensions G. Kraemer et al. 10.5194/bg-17-2397-2020
- Domain knowledge-driven variational recurrent networks for drought monitoring M. Zhang et al. 10.1016/j.rse.2024.114252
- Spectral Dependence H. Ombao & M. Pinto 10.1016/j.ecosta.2022.10.005
- Ecodatacube.eu: analysis-ready open environmental data cube for Europe M. Witjes et al. 10.7717/peerj.15478
- Kernel methods and their derivatives: Concept and perspectives for the earth system sciences J. Johnson et al. 10.1371/journal.pone.0235885
- Ecosystems are showing symptoms of resilience loss J. Rocha 10.1088/1748-9326/ac73a8
- A multi-source spatio-temporal data cube for large-scale geospatial analysis F. Gao et al. 10.1080/13658816.2022.2087222
- Quantum Tensor DBMS and Quantum Gantt Charts: Towards Exponentially Faster Earth Data Engineering R. Rodriges Zalipynis 10.3390/earth5030027
- Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data S. Biass et al. 10.5194/nhess-22-2829-2022
- Toward Causal Inference for Spatio-Temporal Data: Conflict and Forest Loss in Colombia R. Christiansen et al. 10.1080/01621459.2021.2013241
- Research into land atmosphere interactions supports the sustainable development agenda G. Hayman et al. 10.1017/sus.2024.3
- Crowd‐sourced plant occurrence data provide a reliable description of macroecological gradients M. Mahecha et al. 10.1111/ecog.05492
- Time‐Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity N. Linscheid et al. 10.1029/2021GL093285
- The Austrian Semantic EO Data Cube Infrastructure M. Sudmanns et al. 10.3390/rs13234807
- Flood susceptibility mapping to improve models of species distributions E. Ebrahimi et al. 10.1016/j.ecolind.2023.111250
- Gap‐Filled Multivariate Observations of Global Land–Climate Interactions V. Bessenbacher et al. 10.1029/2023JD039099
- Potential of Recurrence Metrics from Sentinel-1 Time Series for Deforestation Mapping F. Cremer et al. 10.1109/JSTARS.2020.3019333
- CloudSEN12, a global dataset for semantic understanding of cloud and cloud shadow in Sentinel-2 C. Aybar et al. 10.1038/s41597-022-01878-2
- Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review M. E. D. Chaves et al. 10.3390/rs12183062
- A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research D. Montero et al. 10.1038/s41597-023-02096-0
- An In-Memory Data-Cube Aware Distributed Data Discovery Across Clouds for Remote Sensing Big Data J. Song et al. 10.1109/JSTARS.2023.3267118
- Multivariate analysis of land surface dynamics in Central Asia: patterns of trends and drivers under a changing climate S. Uereyen et al. 10.1080/15481603.2024.2364461
4 citations as recorded by crossref.
- A framework for the detection and attribution of biodiversity change A. Gonzalez et al. 10.1098/rstb.2022.0182
- Scaling‐up biodiversity‐ecosystem functioning research A. Gonzalez et al. 10.1111/ele.13456
- Towards a global understanding of vegetation–climate dynamics at multiple timescales N. Linscheid et al. 10.5194/bg-17-945-2020
- OpenEOcubes: an open-source and lightweight R-based RESTful web service for analyzing earth observation data cubes B. Pondi et al. 10.1007/s12145-024-01249-y
Latest update: 20 Nov 2024
Short summary
The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
The ever-growing availability of data streams on different subsystems of the Earth brings...
Altmetrics
Final-revised paper
Preprint