1,720,955 research outputs found
Outputs of the Jupyter Notebook - Detecting floating objects using Deep Learning and Sentinel-2 imagery
No full textThe dataset contains the outputs of the notebook "Detecting floating objects using Deep Learning and Sentinel-2 imagery" published in the ocean modelling section of The Environmental Data Science Book.
Contributions
Notebook
Jamila Mifdal (author), European Space Agency Φ-lab, @jmifdal
Raquel Carmo (author), European Space Agency Φ-lab, @raquelcarmo
Alejandro Coca-Castro (reviewer), The Alan Turing Institute, @acocac
Modelling codebase
Jamila Mifdal (author), European Space Agency Φ-lab, @jmifdal
Raquel Carmo (author), European Space Agency Φ-lab, @raquelcarmo
Marc Rußwurm (author), EPFL-ECEO, @marccor
Outputs of the Jupyter Notebook - Concatenating a gridded rainfall reanalysis dataset into a time series
No full textThe dataset contains the outputs of the notebook "Concatenating a gridded rainfall reanalysis dataset into a time series" published in The Environmental Data Science Book.
Contributions
Notebook
Timothy Lam (author), University of Exeter, @timo0thy
Marlene Kretschmer (author), University of Reading, @MarleneKretschmer
Samantha Adams (author), Met Office Informatics Lab, @svadams
Rachel Prudden (author), Met Office Informatics Lab, @RPrudden
Elena Saggioro (author), University of Reading, @ESaggioro
Nick Homer (reviewer), University of Edinburgh, @NHomer
Alejandro Coca-Castro (reviewer), The Alan Turing Institute, @acocac
Dataset originator/creator
NOAA National Center for Environmental Prediction (creator)
Dataset authors
Eugenia Kalnay, Director, NCEP Environmental Modeling Center
Dataset documentation
E. Kalnay, M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, Roy Jenne, and Dennis Joseph. The ncep/ncar 40-year reanalysis project. Bulletin of the American Meteorological Society, 77(3):437 – 472, 1996. URL: https://journals.ametsoc.org/view/journals/bams/77/3/1520-0477_1996_077_0437_tnyrp_2_0_co_2.xml, doi:10.1175/1520-0477(1996)0772.0.CO;2.
Pipeline documentation
Marlene Kretschmer, Samantha V. Adams, Alberto Arribas, Rachel Prudden, Niall Robinson, Elena Saggioro, and Theodore G. Shepherd. Quantifying causal pathways of teleconnections. Bulletin of the American Meteorological Society, 102(12):E2247 – E2263, 2021. URL: https://journals.ametsoc.org/view/journals/bams/102/12/BAMS-D-20-0117.1.xml, doi:10.1175/BAMS-D-20-0117.1
Outputs of the Jupyter Notebook - Tree crown delineation using detectreeRGB
No full textThe dataset contains the outputs of the notebook "Tree crown detection using DeepForest" published in The Environmental Data Science Book.
Contributions
Notebook
Sebastian H. M. Hickman (author), University of Cambridge, @shmh40
Alejandro Coca-Castro (reviewer), The Alan Turing Institute, @acocac
Modelling codebase
Sebastian H. M. Hickman (author), University of Cambridge @shmh40
James G. C. Ball (contributor), University of Cambridge @PatBall1
David A. Coomes (contributor), University of Cambridge
Toby Jackson (contributor), University of Cambridg
Outputs of the Jupyter Notebook - Met Office UKV high-resolution atmosphere model data
No full textThe dataset contains the outputs of the notebook "Met Office UKV high-resolution atmosphere model data" published in the urban sensors section of The Environmental Data Science Book.
Contributions
Notebook
Samantha V. Adams (author), Met Office Informatics Lab, @svadams
Alejandro Coca-Castro (reviewer), The Alan Turing Institute, @acocac
Dataset originator/creator
Met Office Informatics Lab (creator)
Microsoft (support)
European Regional Development Fund (support)
Dataset authors
Met Office
Dataset documentation
Theo McCaie. Met office and partners offer data and compute platform for covid-19 researchers. URL: https://medium.com/informatics-lab/met-office-and-partners-offer-data-and-compute-platform-for-covid-19-researchers-83848ac55f5f
Outputs of the Jupyter Notebook - Cosmos-UK soil moisture
No full textThe dataset contains the outputs of the notebook "Cosmos-UK soil moisture" published in The Environmental Data Science Book.
Contributions
Notebook
Alejandro Coca-Castro (author), The Alan Turing Institute, @acocac
Doran Khamis (reviewer), UK Centre for Ecology & Hydrology, @dorankhamis
Matt Fry (reviewer), UK Centre for Ecology & Hydrology, @mattfry-ceh
Dataset originator/creator
UK Centre for Ecology & Hydrology (creator)
Natural Environment Research Council (support)
Dataset reference and documentation
S. Stanley, V. Antoniou, A. Askquith-Ellis, L.A. Ball, E.S. Bennett, J.R. Blake, D.B. Boorman, M. Brooks, M. Clarke, H.M. Cooper, N. Cowan, A. Cumming, J.G. Evans, P. Farrand, M. Fry, O.E. Hitt, W.D. Lord, R. Morrison, G.V. Nash, D. Rylett, P.M. Scarlett, O.D. Swain, M. Szczykulska, J.L. Thornton, E.J. Trill, A.C. Warwick, and B. Winterbourn. Daily and sub-daily hydrometeorological and soil data (2013-2019) [cosmos-uk]. 2021. URL: https://doi.org/10.5285/b5c190e4-e35d-40ea-8fbe-598da03a1185, doi:10.5285/b5c190e4-e35d-40ea-8fbe-598da03a1185.
Further references
Jonathan G. Evans, H. C. Ward, J. R. Blake, E. J. Hewitt, R. Morrison, M. Fry, L. A. Ball, L. C. Doughty, J. W. Libre, O. E. Hitt, D. Rylett, R. J. Ellis, A. C. Warwick, M. Brooks, M. A. Parkes, G. M.H. Wright, A. C. Singer, D. B. Boorman, and A. Jenkins. Soil water content in southern england derived from a cosmic-ray soil moisture observing system – cosmos-uk. Hydrological Processes, 30:4987–4999, 12 2016. doi:10.1002/hyp.10929.
M. Zreda, W. J. Shuttleworth, X. Zeng, C. Zweck, D. Desilets, T. Franz, and R. Rosolem. Cosmos: the cosmic-ray soil moisture observing system. Hydrology and Earth System Sciences, 16(11):4079–4099, 2012. URL: https://hess.copernicus.org/articles/16/4079/2012/, doi:10.5194/hess-16-4079-2012
Environmental Data Science Book: A living, open and community-driven online resource to showcase and support the publication of data, research and open-source tools for collaborative, reproducible and transparent Environmental Data Science.
No full textWhat's Changed
Adding ocean-modelling-litter-philab notebook by @raquelcarmo in https://github.com/alan-turing-institute/environmental-ds-book/pull/22
docs: add raquelcarmo as a contributor for blog, code by @allcontributors in https://github.com/alan-turing-institute/environmental-ds-book/pull/41
docs: add jmifdal as a contributor for blog, code by @allcontributors in https://github.com/alan-turing-institute/environmental-ds-book/pull/42
add additional information section to executable notebooks by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/43
add rohub and citation to urban-sensors-climate_ukv by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/44
hide cells metadata by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/45
add rohub and citation to wildfires-sensors-fires_modis by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/46
add rohub and citation to forest-modelling-treecrown_deepforest by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/47
Update templates by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/48
Improve guidelines submission by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/51
add rohub and citation wildfires sensors fires seviri by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/55
docs: add annefou as a contributor for ideas by @allcontributors in https://github.com/alan-turing-institute/environmental-ds-book/pull/58
Update README.md by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/59
Add rohub forest modelling treecrown detectree rgb by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/60
add rohub scripts by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/61
Add rohub polar modelling icenet by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/62
docs: add mattfry-ceh as a contributor for review by @allcontributors in https://github.com/alan-turing-institute/environmental-ds-book/pull/63
docs: add dorankhamis as a contributor for review by @allcontributors in https://github.com/alan-turing-institute/environmental-ds-book/pull/64
Update .all-contributorsrc by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/65
docs: add timo0thy as a contributor for content by @allcontributors in https://github.com/alan-turing-institute/environmental-ds-book/pull/66
docs: add NHomer-Edi as a contributor for content by @allcontributors in https://github.com/alan-turing-institute/environmental-ds-book/pull/67
Add soil moisture notebook by @acocac in https://github.com/alan-turing-institute/environmental-ds-book/pull/50
New Contributors
@raquelcarmo made their first contribution in https://github.com/alan-turing-institute/environmental-ds-book/pull/22
Full Changelog: https://github.com/alan-turing-institute/environmental-ds-book/compare/0.0.1...0.0.
Outputs of the Jupyter Notebook - Exploring Land Cover Data (Impact Observatory)
No full textThe dataset contains the outputs of the notebook "Exploring Land Cover Data (Impact Observatory)" published in The Environmental Data Science Book
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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