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The global occurrence, scale, and frequency of wildfires pose significant threats to ecosystem services and human livelihoods.
Causation, prediction, and search (2001)
Spirtes, P., Glymour, C. & Scheines, R · 2001
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Welcome to EFFIS
JRC-EFFIS · 2008
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An active-fire based burned area mapping algorithm for the MODIS sensor
Giglio, L., Loboda, T., Roy, D. P., Quayle, B. & Justice, C. O · 2009
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Causality, 10.1017/cbo9780511803161 (2009)
Pearl, J · 2009
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Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power
Kaiser, J. W. et al · 2012
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Climate-induced variations in global wildfire danger from 1979 to 2013
Jolly, W. M. et al · 2015
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A systematic review of the physical health impacts from non-occupational exposure to wildfire smoke
Liu, J. C., Pereira, G., Uhl, S. A., Bravo, M. A. & Bell, M. L · 2015
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Mcd64a1 modis/terra+aqua burned area monthly l3 global 500m sin grid v006, 10.5067/MODIS/MCD64A1.006 (2015)
Giglio, L., Justice, C., Boschetti, L. & Roy, D · 2015
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MOD13C1 MODIS/Terra Vegetation Indices 16-Day L3 Global 0.05Deg CMG V006, 10.5067/MODIS/MOD13C1.006 (2015)
Didan, K · 2015
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MCD15A2H MODIS/Terra+Aqua Leaf Area Index/FPAR 8-day L4 Global 500m SIN Grid V006, 10.5067/MODIS/MCD15A2H.006 (2015)
Myneni, R., Knyazikhin, Y. & Park, T · 2015
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xarray: N-D labeled arrays and datasets in Python
Hoyer, S. & Hamman, J · 2016
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The collection 6 MODIS active fire detection algorithm and fire products
Giglio, L., Schroeder, W. & Justice, C. O · 2016
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Adapt to more wildfire in western north american forests as climate changes
Schoennagel, T. et al · 2017
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Spatial wildfire occurrence data for the united states, 1992-2015 [fpa_fod_20170508]
Short, K. C · 2017
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CDCol: A geoscience data cube that meets colombian needs
Ariza-Porras, C. et al · 2017
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Digital earth australia – unlocking new value from earth observation data
Dhu, T. et al · 2017
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The australian geoscience data cube — foundations and lessons learned
Lewis, A. et al · 2017
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Building an earth observations data cube: lessons learned from the swiss data cube (SDC) on generating analysis ready data (ARD)
Giuliani, G. et al · 2017
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Global fire emissions database, version 4.1 (gfedv4)
Randerson, J., Van Der Werf, G., Giglio, L., Collatz, G. & Kasibhatla, P · 2017
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An ecoregion-based approach to protecting half the terrestrial realm
Dinerstein, E. et al · 2017
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Prescribed fire and its impacts on ecosystem services in the uk
Harper, A. R., Doerr, S. H., Santin, C., Froyd, C. A. & Sinnadurai, P · 2018
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Wildland fire smoke and human health
Cascio, W. E · 2018
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Datacubes: Towards space/time analysis-ready data
Baumann, P., Misev, D., Merticariu, V. & Huu, B. P · 2018
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Historic Perimeters Combined 2000-2018 GeoMAC — data-nifc.opendata.arcgis.com
NIFC · 2018
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Overview of the open data cube initiative
Killough, B · 2018
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CEOS analysis ready data for land (CARD4l) overview
Lewis, A. et al · 2018
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Esa fire climate change initiative (fire cci): Modis fire cci burned area pixel product, version 5.1
Chuvieco, E., Pettinari, M. L., Lizundia-Loiola, J., Storm, T. & Padilla Parellada, M · 2018
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The collection 6 MODIS burned area mapping algorithm and product
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L. & Justice, C. O · 2018
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ERA5 hourly data on single levels from 1959 to present., 10.24381/cds.adbb2d47 (2018)
Hersbach, H. et al · 2018
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Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 (NASA Socioeconomic Data and Applications Center (SEDAC), 2018)
for International Earth Science Information Network CIESIN Columbia University, C · 2018
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UNet++: A Nested U-Net Architecture for Medical Image Segmentation, 10.48550/arXiv.1807.10165 (2018)
Zhou, Z., Siddiquee, M. M. R., Tajbakhsh, N. & Liang, J · 2018
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The effects of wildfire severity and pyrodiversity on bat occupancy and diversity in fire-suppressed forests
Steel, Z. L., Campos, B. R., Frick, W. F., Burnett, R. D. & Safford, H. D · 2019
Cited alongside, same era.
Paving the way to increased interoperability of earth observations data cubes
Giuliani, G., Masó, J., Mazzetti, P., Nativi, S. & Zabala, A · 2019
Cited alongside, same era.
The global fire atlas of individual fire size, duration, speed and direction
Andela, N. et al · 2019
Cited alongside, same era.
National Interagency Fire Center — data-nifc.opendata.arcgis.com
National Interagency Fire Center · 2019
Cited alongside, same era.
Addendum: The FAIR guiding principles for scientific data management and stewardship
Wilkinson, M. D. et al · 2019
Cited alongside, same era.
Achieving the full vision of earth observation data cubes
Earthnets: Empowering ai in earth observation, 10.48550/ARXIV.2210.04936 (2022)
Xiong, Z., Zhang, F., Wang, Y., Shi, Y. & Zhu, X. X · 2022
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Deep learning for global wildfire forecasting, 10.48550/ARXIV.2211.00534 (2022)
Prapas, I. et al · 2022
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Canadian Wildland Fire Information System | Canadian National Fire Database (CNFDB) — cwfis.cfs.nrcan.gc.ca
CNFDB · 2022
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Sentimental wildfire: a social-physics machine learning model for wildfire nowcasting
Lever, J. & Arcucci, R · 2022
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Wildfire Danger Prediction and Understanding With Deep Learning
Kondylatos, S. et al · 2022
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Global burned area mapping from sentinel-3 synergy and VIIRS active fires
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Kopp, S. et al · 2019
Cited alongside, same era.
A global wildfire dataset for the analysis of fire regimes and fire behaviour
Artés, T. et al · 2019
Cited alongside, same era.
A comparison of remotely-sensed and inventory datasets for burned area in mediterranean europe
Turco, M., Herrera, S., Tourigny, E., Chuvieco, E. & Provenzale, A · 2019
Cited alongside, same era.
Fire danger indices historical data from the Copernicus Emergency Management Service, 10.24381/CDS.0E89C522 (2019)
CMES · 2019
Cited alongside, same era.
Land cover classification gridded maps from 1992 to present derived from satellite observations, 10.24381/CDS.006F2C9A (2019)
Copernicus Climate Change Service · 2019
Cited alongside, same era.
A global wildfire dataset for the analysis of fire regimes and fire behaviour
Artés, T. et al · 2019
Cited alongside, same era.
ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Grid product, version 5.1, 10.5285/3628CB2FDBA443588155E15DEE8E5352 (2019)
Chuvieco, E., Pettinari, M. L., Lizundia Loiola, J., Storm, T. & Padilla Parellada, M · 2019
Cited alongside, same era.
Lizundia-Loiola, J., Franquesa, M., Khairoun, A. & Chuvieco, E · 2022
Later among the works it cites.
Influence of atmospheric patterns on soil moisture dynamics in Europe
Almendra-Martín, L. et al · 2022
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Understanding climate variability: The north atlantic oscillation
Climate.gov · 2022
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Severe wildfires promoted by climate change negatively impact forest amphibian metacommunities
Beranek, C. T. et al · 2023
Closest in time.
Mega forest fires intensify flood magnitudes in southeast australia
Xu, Z., Zhang, Y., Blöschl, G. & Piao, S · 2023
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Data cubes for earth system research: Challenges ahead
Loaiza, D. M. et al · 2023
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Televit: Teleconnection-driven transformers improve subseasonal to seasonal wildfire forecasting, 10.48550/ARXIV.2306.10940 (2023)
Prapas, I. et al · 2023
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FIRMS Frequently Asked Questions | Earthdata — earthdata.nasa.gov
Earth Data, N · 2023
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Product catalogue - Geoscience Australia — ecat.ga.gov.au
Government of Australia · 2023
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All-hazards dataset mined from the US national incident management system 1999–2020
Denis, L. A. S. et al · 2023
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Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the mediterranean, 10.48550/ARXIV.2306.05144 (2023)
Kondylatos, S., Prapas, I., Camps-Valls, G. & Papoutsis, I · 2023
Closest in time.
Ropelewski, C. F. and Jones, P. D. (1987): https://journals.ametsoc.org/view/journals/mwre/115/9/1520-0493_1987_115_2161_aeotts_2_0_co_2.xml
Southern oscillation index (soi) [dataset] · 2023
Closest in time.
Smith, J. and Sardeshmukh, P. (2000): https://rmets.onlinelibrary.wiley.com/doi/10.1002/1097-0088(20001115)20:13%3C1543::AID-JOC579%3E3.0.CO;2-A
Bivariate enso timeseries [dataset] · 2023
Closest in time.
Barnston, Anthony G. and Livezey, Robert E. (1987): https://journals.ametsoc.org/view/journals/mwre/115/6/1520-0493_1987_115_1083_csapol_2_0_co_2.xml
Arctic oscillation (ao) [dataset] · 2023
Closest in time.
Jones Phillip. D., Jonsson T, and Wheeler D. (1997): https://rmets.onlinelibrary.wiley.com/doi/10.1002/(SICI)1097-0088(19971115)17:13%3C1433::AID-JOC203%3E3.0.CO;2-P
North atlantic oscillation index (nao) [dataset] · 2023
Closest in time.
Barnston, Anthony G. and Livezey, Robert E. (1987): https://journals.ametsoc.org/view/journals/mwre/115/6/1520-0493_1987_115_1083_csapol_2_0_co_2.xml
East atlantic (ea) [dataset] · 2023
Closest in time.
Wallace, John M. and Gutzler, David S. (1981): https://journals.ametsoc.org/view/journals/mwre/109/4/1520-0493_1981_109_0784_titghf_2_0_co_2.xml
East atlantic (ea) [dataset] · 2023
Closest in time.
Smith Thomas M., et al., (1996): https://journals.ametsoc.org/view/journals/clim/9/6/1520-0442_1996_00_1403_rohsst_2_0_co_2.xml
Global mean land/ocean temperature index from nasa/giss [dataset] · 2023
Closest in time.
Rayner, N. A. et al., (2003): https://www.metoffice.gov.uk/hadobs/hadisst/HadISST_paper.pdf
Niño 3.4 calculated from the hadisst1.1 dataset at noaa/esrl [dataset] · 2023
Closest in time.
Barnston, Anthony G. and Livezey, Robert E. (1987): https://journals.ametsoc.org/view/journals/mwre/115/6/1520-0493_1987_115_1083_csapol_2_0_co_2.xml
West pacific (wp) [dataset] · 2023
Closest in time.
Wallace, John M. and Gutzler, David S. (1981): https://journals.ametsoc.org/view/journals/mwre/109/4/1520-0493_1981_109_0784_titghf_2_0_co_2.xml
West pacific (wp) [dataset] · 2023
Closest in time.
Bell, Gerald D. and Janowiak, John E. (1995): https://journals.ametsoc.org/view/journals/bams/76/5/1520-0477_1995_076_0681_acawtm_2_0_co_2.xml
East pacific/north pacific oscillation (ep-np) [dataset] · 2023
Closest in time.
Mantua, Nathan J. and Hare, Steven R. and Zhang, Yuan (1997): https://journals.ametsoc.org/view/journals/bams/78/6/1520-0477_1997_078_1069_apicow_2_0_co_2.xml
Pacific decadal oscillation (pdo) [dataset] · 2023
Closest in time.
Barnston, Anthony G. and Livezey, Robert E. (1987): https://journals.ametsoc.org/view/journals/mwre/115/6/1520-0493_1987_115_1083_csapol_2_0_co_2.xml
Pacific north american index (pna) [dataset] · 2023
Closest in time.
Increasing vapor pressure deficit accelerates land drying
Li, S. et al · 2023
Closest in time.