Environmental research https://doi.org/10.5281/zenodo.17171136 2025-09-22 10:48:24.562016+00:00 2025-09-22 10:48:25.226799+00:00 Contains outputs, (results), generated in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Outputs 2025-09-22 10:48:24.562016+00:00 https://doi.org/10.5281/zenodo.17175792 2025-09-22 10:48:22.888533+00:00 2025-09-22 10:48:23.594034+00:00 Contains input Input datasets used in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Input Input datasets 2025-09-22 10:48:22.888533+00:00 https://github.com/eds-book/dea59792-5a6d-4633-a74c-eb73edce61b8/blob/main/notebook.ipynb 2025-09-22 10:48:20.987054+00:00 2025-09-22 10:48:21.788847+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2025-09-22 10:48:20.987054+00:00 Rio de Janeiro State University rpedruzzi@eng.uerj.br Rizzieri Pedruzzi 0000-0003-0852-0396 Hangzhou Dianzi University Zehao Liu 0009-0000-3855-6352 Computational notebooks community focused on Environmental Data Science environmental.ds.book@gmail.com Environmental Data Science Book Community https://github.com/alan-turing-institute/environmental-ds-book/issues/new/choose 0 https://api.rohub.org/api/ros/d14c540e-0a98-4c7f-a028-d535535369ac/crate/download/ 2025-09-22 10:47:58.115149+00:00 2025-10-16 11:11:37.969501+00:00 2025-09-22 10:47:58.115149+00:00 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/d14c540e-0a98-4c7f-a028-d535535369ac Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book MANUAL Lucky J. Yang, Rizzieri Pedruzzi, and Zehao Liu. "Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Sep 22 ,2025. https://w3id.org/ro-id/d14c540e-0a98-4c7f-a028-d535535369ac. output biblio tool input 100693 https://api.rohub.org/api/resources/8b27e6dc-ac97-4c73-8d99-d9dea59f1f5a/download/ 2025-09-22 10:48:18.468040+00:00 2025-09-22 10:48:19.978707+00:00 image/png Image showing an example of the vehicle-based observation emissions data 2025-09-22 10:48:18.468040+00:00 simulation 12.0 9.9 Environmental Data Science book 12.727272727272727 11.9 experiment 18.78787878787879 15.5 mathematical and computer sciences 100.0 0.24472567439079285 earth sciences 100.0 0.7707348465919495 research object 22.352941176470587 20.9 Environmental Data Science 12.542759407069555 11.0 atmospheric sciences 100.0 0.7707348465919495 simulation 10.946408209806156 9.6 notebook 11.516533637400228 10.1 Book industry Economy, business and finance/Economic sector/Media/Book industry aim 7.2727272727272725 6.0 Literature Arts, culture and entertainment/Arts and entertainment/Literature notebook 12.0 9.9 observation data processing 33.04812834224599 30.9 computer operations and hardware 100.0 0.24472567439079285 simulation experiments notebook 2.5668449197860963 2.4 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book. 46.046046046046044 46.0 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. 53.95395395395395 53.9 data processing 28.164196123147093 24.7 research 9.454545454545455 7.8 book 10.376282782212087 9.1 experiment 17.44583808437856 15.3 data processing 28.96969696969697 23.9 simulation experiment 29.3048128342246 27.4 publishing 100.0 4.4 book 11.515151515151516 9.5 research 9.007981755986316 7.9 Language Arts, culture and entertainment/Culture/Language Environmental Data Science Book Community Westlake University yangjianqi@westlake.edu.cn Lucky J. Yang Environmental research https://doi.org/10.5281/zenodo.17171136 2025-09-22 10:49:18.454535+00:00 2025-09-22 10:49:19.122602+00:00 Contains outputs, (results), generated in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Outputs 2025-09-22 10:49:18.454535+00:00 https://doi.org/10.5281/zenodo.17175792 2025-09-22 10:49:16.843742+00:00 2025-09-22 10:49:17.507885+00:00 Contains input Input datasets used in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Input Input datasets 2025-09-22 10:49:16.843742+00:00 https://github.com/eds-book/dea59792-5a6d-4633-a74c-eb73edce61b8/blob/main/notebook.ipynb 2025-09-22 10:49:14.547747+00:00 2025-09-22 10:49:15.345765+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2025-09-22 10:49:14.547747+00:00 Rio de Janeiro State University rpedruzzi@eng.uerj.br Rizzieri Pedruzzi 0000-0003-0852-0396 Hangzhou Dianzi University Zehao Liu 0009-0000-3855-6352 0 https://api.rohub.org/api/ros/0b449ecb-dc8f-4ba0-9211-8bb9864ce7e2/crate/download/ 2025-09-22 10:48:52.986447+00:00 2025-10-16 11:11:19.223037+00:00 2025-09-22 10:48:52.986447+00:00 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/0b449ecb-dc8f-4ba0-9211-8bb9864ce7e2 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book MANUAL Lucky J. Yang, Rizzieri Pedruzzi, and Zehao Liu. "Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Sep 22 ,2025. https://w3id.org/ro-id/0b449ecb-dc8f-4ba0-9211-8bb9864ce7e2. output biblio input tool 100693 https://api.rohub.org/api/resources/41e32a87-e2e9-44a8-9317-e1a03e8423bc/download/ 2025-09-22 10:49:12.096244+00:00 2025-09-22 10:49:13.527385+00:00 image/png Image showing an example of the vehicle-based observation emissions data 2025-09-22 10:49:12.096244+00:00 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. 53.95395395395395 53.9 aim 7.2727272727272725 6.0 Environmental Data Science book 12.727272727272727 11.9 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book. 46.046046046046044 46.0 research 9.454545454545455 7.8 Book industry Economy, business and finance/Economic sector/Media/Book industry simulation 12.0 9.9 notebook 11.516533637400228 10.1 data processing 28.96969696969697 23.9 mathematical and computer sciences 100.0 0.24472567439079285 book 10.376282782212087 9.1 earth sciences 100.0 0.7707348465919495 computer operations and hardware 100.0 0.24472567439079285 Literature Arts, culture and entertainment/Arts and entertainment/Literature Language Arts, culture and entertainment/Culture/Language research 9.007981755986316 7.9 publishing 100.0 4.4 simulation experiment 29.3048128342246 27.4 observation data processing 33.04812834224599 30.9 experiment 18.78787878787879 15.5 Environmental Data Science 12.542759407069555 11.0 research object 22.352941176470587 20.9 notebook 12.0 9.9 simulation experiments notebook 2.5668449197860963 2.4 simulation 10.946408209806156 9.6 atmospheric sciences 100.0 0.7707348465919495 book 11.515151515151516 9.5 experiment 17.44583808437856 15.3 data processing 28.164196123147093 24.7 Environmental Data Science Book Community Westlake University yangjianqi@westlake.edu.cn Lucky J. Yang Environmental research https://doi.org/10.5281/zenodo.17171136 2025-09-22 10:50:40.131872+00:00 2025-09-22 10:50:40.766967+00:00 Contains outputs, (results), generated in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Outputs 2025-09-22 10:50:40.131872+00:00 https://doi.org/10.5281/zenodo.17175792 2025-09-22 10:50:38.422172+00:00 2025-09-22 10:50:39.116427+00:00 Contains input Input datasets used in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Input Input datasets 2025-09-22 10:50:38.422172+00:00 https://github.com/eds-book/dea59792-5a6d-4633-a74c-eb73edce61b8/blob/main/notebook.ipynb 2025-09-22 10:50:36.343361+00:00 2025-09-22 10:50:37.222607+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2025-09-22 10:50:36.343361+00:00 Rio de Janeiro State University rpedruzzi@eng.uerj.br Rizzieri Pedruzzi 0000-0003-0852-0396 Hangzhou Dianzi University Zehao Liu 0009-0000-3855-6352 0 https://api.rohub.org/api/ros/368f9594-6513-4f49-a510-275c07b1c3b6/crate/download/ 2025-09-22 10:50:14.653665+00:00 2025-10-16 11:11:03.381864+00:00 2025-09-22 10:50:14.653665+00:00 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/368f9594-6513-4f49-a510-275c07b1c3b6 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book MANUAL Lucky J. Yang, Rizzieri Pedruzzi, and Zehao Liu. "Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Sep 22 ,2025. https://w3id.org/ro-id/368f9594-6513-4f49-a510-275c07b1c3b6. output tool input biblio 100693 https://api.rohub.org/api/resources/59322158-c890-4018-9316-71e09c41c47f/download/ 2025-09-22 10:50:34.313127+00:00 2025-09-22 10:50:35.343626+00:00 image/png Image showing an example of the vehicle-based observation emissions data 2025-09-22 10:50:34.313127+00:00 Literature Arts, culture and entertainment/Arts and entertainment/Literature Language Arts, culture and entertainment/Culture/Language publishing 100.0 4.4 simulation 10.946408209806156 9.6 data processing 28.164196123147093 24.7 experiment 17.44583808437856 15.3 aim 7.2727272727272725 6.0 experiment 18.78787878787879 15.5 observation data processing 33.04812834224599 30.9 research object 22.352941176470587 20.9 research 9.007981755986316 7.9 research 9.454545454545455 7.8 notebook 11.516533637400228 10.1 simulation experiments notebook 2.5668449197860963 2.4 Environmental Data Science book 12.727272727272727 11.9 atmospheric sciences 100.0 0.7707348465919495 Environmental Data Science 12.542759407069555 11.0 mathematical and computer sciences 100.0 0.24472567439079285 data processing 28.96969696969697 23.9 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book. 46.046046046046044 46.0 simulation experiment 29.3048128342246 27.4 earth sciences 100.0 0.7707348465919495 computer operations and hardware 100.0 0.24472567439079285 book 11.515151515151516 9.5 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. 53.95395395395395 53.9 book 10.376282782212087 9.1 notebook 12.0 9.9 simulation 12.0 9.9 Book industry Economy, business and finance/Economic sector/Media/Book industry Environmental Data Science Book Community Westlake University yangjianqi@westlake.edu.cn Lucky J. Yang Environmental research Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Flood_protection_line_Saarland.ipynb 2025-10-08 08:47:29.592762+00:00 2025-10-08 08:47:30.239969+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-08 08:47:29.592762+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-08 08:46:18.994606+00:00 2025-10-08 08:46:19.636455+00:00 Example for FAIR2Adapt training on RO-Crate and ROHub image/png flood in saarland with JupyterGIS 2025-10-08 08:46:18.994606+00:00 0527eb4e-b7c8-4ac0-9b85-52e0773c3b79 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 0 https://api.rohub.org/api/ros/8a351029-86a8-4e90-a9d1-a67d45d63656/crate/download/ 2025-10-08 08:39:21.885634+00:00 2025-10-16 11:10:21.642786+00:00 2025-10-08 08:39:21.885634+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 08 ,2025. https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656. POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio tool input output 907 https://api.rohub.org/api/resources/4d1eee3a-9631-4d76-a15a-ab1de329fde1/download/ 2025-10-08 08:44:48.739835+00:00 2025-10-08 08:44:50.121842+00:00 image/png Image to illustrate my case study 2025-10-08 08:44:48.739835+00:00 earth sciences 100.0 0.9335481524467468 geosciences 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 case study 13.456090651558075 9.5 crate 15.700737618545837 14.9 research 17.91359325605901 17.0 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 object 15.59536354056902 14.8 FAIR2Adapt 21.390937829293993 20.3 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 Ro 10.326659641728135 9.8 crate 20.538243626062325 14.5 case study 2 0.30060120240480964 0.3 Ro 13.597733711048159 9.6 research object 73.44689378757515 73.3 Jupyter notebook 9.062170706006322 8.6 case study 10.010537407797681 9.5 example 7.36543909348442 5.2 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 aim 20.67988668555241 14.6 Food and drink Lifestyle and leisure/Lifestyle/Food and drink Language Arts, culture and entertainment/Culture/Language Food Economy, business and finance/Economic sector/Consumer goods/Food Environmental research 0 https://api.rohub.org/api/ros/bc6f13f4-e7d6-4490-ae63-3dff3939f914/crate/download/ 2025-12-07 19:52:04.926440+00:00 2026-04-11 09:47:42.427406+00:00 2025-12-07 19:52:04.926440+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/bc6f13f4-e7d6-4490-ae63-3dff3939f914 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/bc6f13f4-e7d6-4490-ae63-3dff3939f914. output biblio input tool Water management Climate change impacts, risks and adaptation Geographical Scope tool 17.95543905635649 13.7 Institutional: Government policies and programs Weather phenomena Weather/Weather phenomena Climate-ADAPT Adaptation Sectors data pipelining tool 36.442786069651746 29.3 Stakeholders water datum 5.72139303482587 4.6 fact 21.62516382699869 16.5 Academia/ Research Institutions Book industry Economy, business and finance/Economic sector/Media/Book industry European Continent Language Arts, culture and entertainment/Culture/Language book 7.601572739187418 5.8 Storms Key Type Measures User Needs (RAST) data visualization 16.43132220795892 12.8 Funding tool in r 26.74129353233831 21.5 datum 22.0795892169448 17.2 Methodology Geosciences pipeline processing 11.926605504587156 9.1 research 9.82961992136304 7.5 IPCC Climate Hazard research object 22.63681592039801 18.2 data 16.775884665792923 12.8 Engineering Engineering (General) Geosciences (General) Academic/ Institutional Environmental Data Science 9.242618741976893 7.2 Policy Scale Environmental Data Science book 8.45771144278607 6.8 none Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 No policy or regulation Literature Arts, culture and entertainment/Arts and entertainment/Literature Environmental Science and Management Weather Weather research 10.141206675224646 7.9 Preparing the ground pipelining 12.708600770218228 9.9 aim 6.553079947575361 5.0 tool 18.485237483953785 14.4 Environmental Sciences Physical and Technological Knowledge Sector (EEA) notebook 7.732634338138926 5.9 data 10.91142490372272 8.5 computer science 100.0 15.9 Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research data visualization 16.43132220795892 12.8 water datum 5.72139303482587 4.6 computer science 100.0 15.9 Policy Scale IPCC Weather Weather Environmental Science and Management Climate-ADAPT Adaptation Sectors research 10.141206675224646 7.9 aim 6.553079947575361 5.0 notebook 7.732634338138926 5.9 Environmental Sciences European Continent tool in r 26.74129353233831 21.5 Literature Arts, culture and entertainment/Arts and entertainment/Literature Water management Climate change impacts, risks and adaptation data pipelining tool 36.442786069651746 29.3 tool 18.485237483953785 14.4 Environmental Data Science book 8.45771144278607 6.8 research object 22.63681592039801 18.2 Physical and Technological Environmental Data Science 9.242618741976893 7.2 Institutional: Government policies and programs tool 17.95543905635649 13.7 book 7.601572739187418 5.8 research 9.82961992136304 7.5 Methodology Geosciences (General) none Book industry Economy, business and finance/Economic sector/Media/Book industry No policy or regulation Funding Storms Geographical Scope Language Arts, culture and entertainment/Culture/Language Engineering (General) Weather phenomena Weather/Weather phenomena Knowledge Sector (EEA) Geosciences Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Engineering Academia/ Research Institutions fact 21.62516382699869 16.5 Key Type Measures Stakeholders Academic/ Institutional data 16.775884665792923 12.8 User Needs (RAST) pipelining 12.708600770218228 9.9 data 10.91142490372272 8.5 Preparing the ground datum 22.0795892169448 17.2 Climate Hazard pipeline processing 11.926605504587156 9.1 0 https://api.rohub.org/api/ros/f4cfe8f4-abcc-41b0-9c8d-8a01bed66730/crate/download/ 2025-12-07 19:52:30.693118+00:00 2026-04-11 09:48:02.572671+00:00 2025-12-07 19:52:30.693118+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/f4cfe8f4-abcc-41b0-9c8d-8a01bed66730 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Community, Environmental Data Science Book. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/f4cfe8f4-abcc-41b0-9c8d-8a01bed66730. input output biblio tool Environmental Data Science Book Community Environmental research 0 https://api.rohub.org/api/ros/3a33645c-7d45-452b-a53d-0133d12e991f/crate/download/ 2025-12-07 19:54:27.990497+00:00 2026-04-11 09:47:22.278061+00:00 2025-12-07 19:54:27.990497+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/3a33645c-7d45-452b-a53d-0133d12e991f Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/3a33645c-7d45-452b-a53d-0133d12e991f. output biblio input tool data 16.775884665792923 12.8 Preparing the ground Academia/ Research Institutions research object 22.63681592039801 18.2 Methodology Physical and Technological IPCC Geographical Scope Water management Institutional: Government policies and programs Climate change impacts, risks and adaptation data visualization 16.43132220795892 12.8 Weather phenomena Weather/Weather phenomena book 7.601572739187418 5.8 pipeline processing 11.926605504587156 9.1 Storms Weather Weather Book industry Economy, business and finance/Economic sector/Media/Book industry fact 21.62516382699869 16.5 aim 6.553079947575361 5.0 Environmental Data Science 9.242618741976893 7.2 Geosciences Academic/ Institutional Engineering (General) Engineering research 10.141206675224646 7.9 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Knowledge Sector (EEA) Language Arts, culture and entertainment/Culture/Language notebook 7.732634338138926 5.9 Literature Arts, culture and entertainment/Arts and entertainment/Literature data pipelining tool 36.442786069651746 29.3 water datum 5.72139303482587 4.6 tool 17.95543905635649 13.7 Policy Scale Environmental Data Science book 8.45771144278607 6.8 User Needs (RAST) European Continent Climate Hazard computer science 100.0 15.9 No policy or regulation tool in r 26.74129353233831 21.5 pipelining 12.708600770218228 9.9 tool 18.485237483953785 14.4 Climate-ADAPT Adaptation Sectors research 9.82961992136304 7.5 Environmental Sciences data 10.91142490372272 8.5 Environmental Science and Management Geosciences (General) Stakeholders datum 22.0795892169448 17.2 Key Type Measures none Funding Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research 0 https://api.rohub.org/api/ros/acefb4d3-e320-4df8-a8b1-17cfa1a40ea0/crate/download/ 2025-12-07 19:54:45.553533+00:00 2026-04-11 09:47:32.519324+00:00 2025-12-07 19:54:45.553533+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/acefb4d3-e320-4df8-a8b1-17cfa1a40ea0 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/acefb4d3-e320-4df8-a8b1-17cfa1a40ea0. tool output input biblio none Academia/ Research Institutions Physical and Technological Weather phenomena Weather/Weather phenomena research object 22.63681592039801 18.2 Geosciences (General) Environmental Sciences IPCC Institutional: Government policies and programs Climate change impacts, risks and adaptation Methodology data 10.91142490372272 8.5 Engineering (General) research 9.82961992136304 7.5 Climate-ADAPT Adaptation Sectors Knowledge Sector (EEA) No policy or regulation computer science 100.0 15.9 data visualization 16.43132220795892 12.8 Environmental Science and Management Preparing the ground aim 6.553079947575361 5.0 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 fact 21.62516382699869 16.5 tool 18.485237483953785 14.4 Geographical Scope water datum 5.72139303482587 4.6 data 16.775884665792923 12.8 pipeline processing 11.926605504587156 9.1 Funding Key Type Measures Environmental Data Science 9.242618741976893 7.2 book 7.601572739187418 5.8 Weather Weather Book industry Economy, business and finance/Economic sector/Media/Book industry Engineering Storms tool in r 26.74129353233831 21.5 Environmental Data Science book 8.45771144278607 6.8 notebook 7.732634338138926 5.9 Language Arts, culture and entertainment/Culture/Language Literature Arts, culture and entertainment/Arts and entertainment/Literature User Needs (RAST) Stakeholders pipelining 12.708600770218228 9.9 Water management data pipelining tool 36.442786069651746 29.3 tool 17.95543905635649 13.7 European Continent research 10.141206675224646 7.9 datum 22.0795892169448 17.2 Policy Scale Academic/ Institutional Geosciences Climate Hazard Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research 0 https://api.rohub.org/api/ros/70040ead-8d3e-4e1d-ab67-2472d302dabd/crate/download/ 2025-12-07 19:55:20.674161+00:00 2026-04-11 09:47:52.885307+00:00 2025-12-07 19:55:20.674161+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/70040ead-8d3e-4e1d-ab67-2472d302dabd Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/70040ead-8d3e-4e1d-ab67-2472d302dabd. input output tool biblio Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Geographical Scope research 10.141206675224646 7.9 Geosciences aim 6.553079947575361 5.0 fact 21.62516382699869 16.5 data pipelining tool 36.442786069651746 29.3 IPCC none Storms Climate change impacts, risks and adaptation tool 17.95543905635649 13.7 Literature Arts, culture and entertainment/Arts and entertainment/Literature pipeline processing 11.926605504587156 9.1 Preparing the ground data 10.91142490372272 8.5 Book industry Economy, business and finance/Economic sector/Media/Book industry Methodology Climate Hazard Weather Weather datum 22.0795892169448 17.2 Climate-ADAPT Adaptation Sectors Geosciences (General) data 16.775884665792923 12.8 tool 18.485237483953785 14.4 No policy or regulation research object 22.63681592039801 18.2 Weather phenomena Weather/Weather phenomena Funding tool in r 26.74129353233831 21.5 Language Arts, culture and entertainment/Culture/Language water datum 5.72139303482587 4.6 Key Type Measures Environmental Data Science 9.242618741976893 7.2 Stakeholders Environmental Sciences Engineering (General) computer science 100.0 15.9 Policy Scale Academic/ Institutional Academia/ Research Institutions European Continent data visualization 16.43132220795892 12.8 Water management Environmental Data Science book 8.45771144278607 6.8 Environmental Science and Management User Needs (RAST) Knowledge Sector (EEA) Physical and Technological Institutional: Government policies and programs pipelining 12.708600770218228 9.9 book 7.601572739187418 5.8 Engineering notebook 7.732634338138926 5.9 research 9.82961992136304 7.5 Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research 0 https://api.rohub.org/api/ros/18c1e606-b72e-4971-964a-af90a0503f41/crate/download/ 2025-12-07 19:55:29.829541+00:00 2026-04-11 09:48:22.768026+00:00 2025-12-07 19:55:29.829541+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/18c1e606-b72e-4971-964a-af90a0503f41 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/18c1e606-b72e-4971-964a-af90a0503f41. biblio output tool input Policy Scale water datum 5.72139303482587 4.6 Water management Environmental Science and Management Environmental Data Science book 8.45771144278607 6.8 Stakeholders Climate change impacts, risks and adaptation Physical and Technological Key Type Measures book 7.601572739187418 5.8 Institutional: Government policies and programs Geosciences (General) Environmental Sciences Storms tool 18.485237483953785 14.4 Literature Arts, culture and entertainment/Arts and entertainment/Literature computer science 100.0 15.9 Academia/ Research Institutions aim 6.553079947575361 5.0 User Needs (RAST) Geosciences pipelining 12.708600770218228 9.9 Weather phenomena Weather/Weather phenomena Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 No policy or regulation Climate-ADAPT Adaptation Sectors none Geographical Scope datum 22.0795892169448 17.2 Funding fact 21.62516382699869 16.5 Language Arts, culture and entertainment/Culture/Language pipeline processing 11.926605504587156 9.1 Knowledge Sector (EEA) IPCC European Continent Methodology Engineering (General) research 10.141206675224646 7.9 research object 22.63681592039801 18.2 Academic/ Institutional notebook 7.732634338138926 5.9 Environmental Data Science 9.242618741976893 7.2 Weather Weather data pipelining tool 36.442786069651746 29.3 Engineering data 10.91142490372272 8.5 Preparing the ground tool in r 26.74129353233831 21.5 tool 17.95543905635649 13.7 Book industry Economy, business and finance/Economic sector/Media/Book industry data 16.775884665792923 12.8 Climate Hazard data visualization 16.43132220795892 12.8 research 9.82961992136304 7.5 Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research Stakeholders Climate Hazard book 7.601572739187418 5.8 User Needs (RAST) tool 18.485237483953785 14.4 Engineering IPCC Environmental Data Science 9.242618741976893 7.2 Environmental Data Science book 8.45771144278607 6.8 research 10.141206675224646 7.9 Weather Weather pipeline processing 11.926605504587156 9.1 European Continent computer science 100.0 15.9 Water management research object 22.63681592039801 18.2 aim 6.553079947575361 5.0 Policy Scale none research 9.82961992136304 7.5 Language Arts, culture and entertainment/Culture/Language notebook 7.732634338138926 5.9 Climate change impacts, risks and adaptation data 10.91142490372272 8.5 Literature Arts, culture and entertainment/Arts and entertainment/Literature Storms Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Book industry Economy, business and finance/Economic sector/Media/Book industry Academic/ Institutional Physical and Technological Institutional: Government policies and programs Climate-ADAPT Adaptation Sectors Preparing the ground Geosciences No policy or regulation water datum 5.72139303482587 4.6 fact 21.62516382699869 16.5 Geosciences (General) Environmental Science and Management Key Type Measures data 16.775884665792923 12.8 Geographical Scope tool in r 26.74129353233831 21.5 Weather phenomena Weather/Weather phenomena Engineering (General) Knowledge Sector (EEA) pipelining 12.708600770218228 9.9 Academia/ Research Institutions Environmental Sciences data visualization 16.43132220795892 12.8 datum 22.0795892169448 17.2 Methodology data pipelining tool 36.442786069651746 29.3 tool 17.95543905635649 13.7 Funding 0 https://api.rohub.org/api/ros/fa165103-2ad7-426e-baf0-b8f52a130720/crate/download/ 2025-12-07 19:55:45.229974+00:00 2026-04-11 09:48:12.622500+00:00 2025-12-07 19:55:45.229974+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/fa165103-2ad7-426e-baf0-b8f52a130720 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/fa165103-2ad7-426e-baf0-b8f52a130720. input biblio output tool Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Earth observation https://github.com/EOPF-Sample-Service/eopf-sample-notebooks 2025-12-21 14:59:18.341013+00:00 2025-12-21 14:59:18.963543+00:00 ESA Earth Observation Processing Framework for Sentinel-1, 2 and 3 data access EOPF Sample Service 2025-12-21 14:59:18.341013+00:00 https://github.com/geojupyter/jupytergis 2025-12-21 14:59:14.270649+00:00 2025-12-21 14:59:14.934927+00:00 Collaborative GIS environment for Jupyter - required to open .jGIS files JupyterGIS 2025-12-21 14:59:14.270649+00:00 Anne Fouilloux https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/../requirements.txt 2025-12-21 14:59:16.320382+00:00 2025-12-21 14:59:16.930237+00:00 Conda environment specification with all Python dependencies text/plain Conda Environment 2025-12-21 14:59:16.320382+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/Wetland_ML_Demo_EOPF.ipynb 2025-12-21 14:59:20.404796+00:00 2025-12-21 14:59:21.070859+00:00 Main Jupyter notebook implementing the wetland classification workflow Wetland ML Demo Notebook 2025-12-21 14:59:20.404796+00:00 0 https://api.rohub.org/api/ros/972ba092-9239-4947-9bf6-495c53e57266/crate/download/ 2025-12-21 14:59:12.328362+00:00 2026-04-11 03:22:47.701619+00:00 2025-12-21 14:59:12.328362+00:00 Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. application/ld+json https://w3id.org/ro-id/972ba092-9239-4947-9bf6-495c53e57266 JupyterGIS Wetland Classification Demo - ESA EOPF MANUAL Fouilloux, Anne. "JupyterGIS Wetland Classification Demo - ESA EOPF." ROHub. Dec 21 ,2025. https://w3id.org/ro-id/972ba092-9239-4947-9bf6-495c53e57266. output tool biblio input Geographical Scope annotation 13.086770981507822 9.2 Knowledge Sector (EEA) Physical and Technological Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. 30.93093093093093 30.9 Academic/ Institutional Preparing the ground Aerospace Engineering Climate Hazard Mathematical and computer sciences (general) classification 12.091038406827881 8.5 Policy Scale JupyterGIS Wetland Classification Demo IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Methodology Academia/ Research Institutions User Needs (RAST) machine learning workflow 29.345372460496613 26.0 Geosciences correction 9.174311926605505 6.0 Geosciences (General) Funding collaborative annotation 13.31828442437923 11.8 Key Type Measures Mathematical and computer sciences practice 7.339449541284403 4.8 Wetlands Environment/Natural resources/Water/Wetlands Retraining Labour/Employment/Employment training/Retraining JupyterGIS Wetland Classification Demo - ESA EOPF Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. 69.06906906906906 69.0 computer science 100.0 11.7 European Continent Education Education Computer programming and software data 15.443425076452598 10.1 Other Technology Case Study Engineering Sentinel-2 13.371266002844951 9.4 Climate-ADAPT Adaptation Sectors Data Format Land use planning Engineering (General) Teaching and learning Education/Teaching and learning Esa Eopf 15.07823613086771 10.6 Earth resources and remote sensing Distributed Computing none workflow 11.009174311926605 7.2 IPCC Esa Eopf wetland 7.339449541284403 4.8 wetland classification 29.006772009029344 25.7 research 7.798165137614677 5.1 Stakeholders note 13.608562691131498 8.9 Other Engineering Other Information and Computing Sciences No policy or regulation Information Systems Interdisciplinary Engineering Biodiversity: state of habitats and species category 13.30275229357798 8.7 Computer Software Engineering JupyterGIS Wetland Classification Demo 17.780938833570413 12.5 machine learning 14.22475106685633 10.0 Information and Computing Sciences research practice 20.428893905191874 18.1 data from Esa eopf 7.900677200902933 7.0 machine learning 14.984709480122325 9.8 Technology data 14.366998577524894 10.1 Computer systems none Earth observation https://annefou.github.io/jupytergis-showcases/lab/index.html?path=Wetland_Annotation.jGIS 2025-12-21 16:29:01.808092+00:00 2025-12-21 16:29:02.435279+00:00 Interactive map with expert annotations for model corrections text/html JupyterGIS Annotation Document 2025-12-21 16:29:01.808092+00:00 https://github.com/EOPF-Sample-Service/eopf-sample-notebooks 2025-12-21 16:28:57.399750+00:00 2025-12-21 16:28:58.038982+00:00 ESA Earth Observation Processing Framework for Sentinel-1, 2 and 3 data access EOPF Sample Service 2025-12-21 16:28:57.399750+00:00 https://github.com/annefou/jupytergis-showcases 2025-12-21 16:29:33.240998+00:00 2025-12-21 16:29:33.849049+00:00 Source repository for this demo GitHub Repository 2025-12-21 16:29:33.240998+00:00 https://github.com/geojupyter/jupytergis 2025-12-21 16:28:53.494405+00:00 2025-12-21 16:28:54.119033+00:00 Collaborative GIS environment for Jupyter - required to open .jGIS files JupyterGIS 2025-12-21 16:28:53.494405+00:00 Simula Research Laboratory annef@simula.no Anne Fouilloux 0000-0002-1784-2920 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/../requirements.txt 2025-12-21 16:28:55.442396+00:00 2025-12-21 16:28:56.067960+00:00 Conda environment specification with all Python dependencies text/plain Conda Environment 2025-12-21 16:28:55.442396+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/Wetland_ML_Demo_EOPF.ipynb 2025-12-21 16:28:59.461288+00:00 2025-12-21 16:29:00.096604+00:00 Main Jupyter notebook implementing the wetland classification workflow Wetland ML Demo Notebook 2025-12-21 16:28:59.461288+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/Wetland_ML_ROhub.ipynb 2025-12-21 16:41:18.541514+00:00 2025-12-21 16:41:19.390117+00:00 Jupyter notebook to create a RO-Crate in ROHub Wetland_ML_ROhub 2025-12-21 16:41:18.541514+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/corrections.geojson 2025-12-21 16:29:08.929182+00:00 2025-12-21 16:29:13.322705+00:00 Expert corrections extracted from JupyterGIS annotations Expert Corrections (GeoJSON) 2025-12-21 16:29:08.929182+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/sentinel2_rgb.tif 2025-12-21 16:29:04.078500+00:00 2025-12-21 16:54:53.937124+00:00 Cloud Optimized GeoTIFF - RGB composite from Sentinel-2 L2A image/tiff Sentinel-2 RGB Composite (COG) 2025-12-21 16:29:04.078500+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/wetland_model_v2.joblib 2025-12-21 16:29:27.413086+00:00 2025-12-21 16:29:31.950449+00:00 Serialized Random Forest model retrained with expert corrections Trained Model v2 (joblib) 2025-12-21 16:29:27.413086+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/wetland_prediction_v1.tif 2025-12-21 16:29:06.069310+00:00 2025-12-21 16:29:06.645893+00:00 Initial Random Forest classification - before expert corrections image/tiff Wetland Prediction v1 2025-12-21 16:29:06.069310+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/wetland_prediction_v2_corrected.tif 2025-12-21 16:29:16.556974+00:00 2025-12-21 16:29:23.003791+00:00 Improved classification after retraining with expert corrections image/tiff Wetland Prediction v2 (Corrected) 2025-12-21 16:29:16.556974+00:00 0 https://api.rohub.org/api/ros/10dc322d-eedd-43ff-a4af-7adb6281cb6e/crate/download/ 2025-12-21 16:28:47.782517+00:00 2026-04-11 03:23:09.225173+00:00 2025-12-21 16:28:47.782517+00:00 Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. application/ld+json https://w3id.org/ro-id/10dc322d-eedd-43ff-a4af-7adb6281cb6e JupyterGIS Wetland ML Classification Demo - ESA EOPF MANUAL Fouilloux, Anne. "JupyterGIS Wetland ML Classification Demo - ESA EOPF." ROHub. Dec 21 ,2025. https://w3id.org/ro-id/10dc322d-eedd-43ff-a4af-7adb6281cb6e. biblio tool input output Biodiversity Methodology IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences machine learning workflow 29.345372460496613 26.0 computer science 100.0 11.7 machine learning 14.22475106685633 10.0 Psychology and Cognitive Sciences data 15.443425076452598 10.1 none Computer Software Engineering (General) Other Physical Sciences Other Mathematical Sciences Wetlands Environment/Natural resources/Water/Wetlands Other History and Archaeology Other Commerce, Management, Tourism and Services Other Engineering JupyterGIS Wetland ML Classification Demo - ESA EOPF Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. 69.06906906906906 69.0 research 7.798165137614677 5.1 Other Technology JupyterGIS Wetland ML Classification Demo 17.780938833570413 12.5 Engineering Other Language, Literature and Culture Sentinel-2 13.371266002844951 9.4 Medical and Health Sciences Other Philosophy and Religious Studies Distributed Computing Institutional: Government policies and programs European Continent Other Agricultural and Veterinary Sciences Information and Computing Sciences Technology Education Other Studies in Human Society Other Studies in Creative Arts and Writing Other Medical and Health Sciences Agricultural and Veterinary Sciences Studies in Creative Arts and Writing Mathematical Sciences wetland classification 29.006772009029344 25.7 Preparing the ground wetland 7.339449541284403 4.8 Biodiversity: state of habitats and species Other Psychology and Cognitive Sciences collaborative annotation 13.31828442437923 11.8 Commerce, Management, Tourism and Services classification 12.091038406827881 8.5 Physical Sciences History and Archaeology Teaching and learning Education/Teaching and learning Stakeholders Knowledge Sector (EEA) Key Type Measures Law and Legal Studies Mathematical Physics Climate-ADAPT Adaptation Sectors Physical and Technological Geographical Scope Academic/ Institutional Data Format Artifical Intelligence and Image Processing Case Study annotation 13.086770981507822 9.2 Environmental Science and Management machine learning 14.984709480122325 9.8 Earth resources and remote sensing Philosophy and Religious Studies Geosciences (General) Geosciences Computer systems Astronomical and Space Sciences Computation Theory and Mathematics Studies in Human Society Other Information and Computing Sciences Policy Scale Funding Other Education Retraining Labour/Employment/Employment training/Retraining Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. 30.93093093093093 30.9 note 13.608562691131498 8.9 research practice 20.428893905191874 18.1 data from Esa eopf 7.900677200902933 7.0 User Needs (RAST) Mathematical and computer sciences (general) Other Environmental Sciences Environmental Sciences Esa Eopf workflow 11.009174311926605 7.2 Built Environment and Design Other Law and Legal Studies Computer programming and software Engineering Mathematical and computer sciences IPCC practice 7.339449541284403 4.8 Other Built Environment and Design correction 9.174311926605505 6.0 Economics data 14.366998577524894 10.1 Language, Communication and Culture category 13.30275229357798 8.7 Esa Eopf 15.07823613086771 10.6 Climate Hazard Education Education Academia/ Research Institutions No policy or regulation Other Economics Information Systems JupyterGIS Wetland ML Classification Demo Applied sciences https://fair2adapt.github.io/riomar-dashboard/ 2026-03-20 15:22:58.427334+00:00 2026-03-20 18:12:17.330524+00:00 Dashboard Dashboard 2026-03-20 15:22:58.427334+00:00 https://pangeo-eosc-minioapi.vm.fedcloud.eu/afouilloux-dggs/sentinel_bbox_l20_pyramid.zarr/7 2026-03-20 18:13:34.399299+00:00 2026-03-20 19:26:14.441919+00:00 sentinel_bbox_l20_pyramid.zarr 2026-03-20 18:13:34.399299+00:00 https://pangeo-eosc-minioapi.vm.fedcloud.eu/afouilloux-dggs/sentinel_bbox_l20_pyramid.zarr/7 Academia/ Research Institutions HEALPix DGGS 15.098468271334792 6.9 Monitoring, evaluating and learning HEALPix DGGS approach 23.11046511627907 15.9 Climate-ADAPT Adaptation Sectors Rouen Climate Hazard database 28.448275862068968 3.3 Information Systems Mathematical Sciences Funding Geographical Scope Computer Software Stakeholders France Mathematical and computer sciences France 10.48951048951049 7.5 Methodology none Computer systems pyramid 14.879649890590809 6.8 satellite 8.251748251748252 5.9 Paris HEALPix Discrete Global Grid System 26.744186046511626 18.4 visualization 6.013986013986014 4.3 Normandie Mathematical Physics Social and information sciences Physics Case Study Key Type Measures computer science 30.17241379310345 3.5 Structural/physical: Ecosystem-based Discrete Global Grid System 12.472647702407002 5.7 geometry 13.793103448275863 1.6 Information and Computing Sciences Mathematical and computer sciences (general) metadata 6.293706293706293 4.5 EU pyramid 12.167832167832167 8.7 nested HEALPix 15.116279069767442 10.4 Geosciences (General) collection 4.895104895104895 3.5 Engineering (General) ### FAIRification - Satellite imagery converted to DGGS using [xhealpixify](https://github.com/IAOCEA/xhealpixify) - Machine-actionable: `schema:ViewAction` links the dataset to the [FAIR2Adapt dashboard](https://fair2adapt.github.io/riomar-dashboard/) for interactive visualization at any zoom level - Metadata enriched with [I-ADOPT](https://i-adopt.github.io/) variable decomposition 23.014804845222073 17.1 ### Dataset - **Variable**: Band 02 (Blue, 490nm) top-of-atmosphere reflectance - **Spatial coverage**: Normandy, France (~48.5°N–49.5°N, 0.5°E–1.5°E) - **Grid**: HEALPix multiscale pyramid (11 levels) - Finest: level 20 (nside=1,048,576, ~10m resolution, 208M cells) - Coarsest: level 10 (nside=1,024, ~10km resolution) - Resampling: mean aggregation between levels - **Format**: Cloud-optimized Zarr with nested HEALPix indexing on WGS84 ellipsoid 26.514131897711973 19.7 User Needs (RAST) Nanotechnology Science and technology/Technology and engineering/Micro science/Nanotechnology Physics (General) http 13.426573426573427 9.6 Knowledge Sector (EEA) IPCC European Continent Geosciences reflectivity 7.972027972027972 5.7 Documentation and information science dataset 13.006993006993008 9.3 Numerical and Computational Mathematics Policy Scale Normandie 10.48951048951049 7.5 FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid) Sentinel-2 Level-1C satellite observation converted to a HEALPix Discrete Global Grid System (DGGS) multiscale pyramid, covering a region in **Normandy, France** (Seine Valley, between Rouen and Paris) 50.47106325706594 37.5 Statistics information technology 27.586206896551726 3.2 Engineering France 12.691466083150983 5.8 Earth resources and remote sensing Climate change impacts, risks and adaptation Physical and Technological Physical Sciences http 16.192560175054705 7.4 spirit level 6.993006993006993 5.0 Agriculture Astronomical and Space Sciences Regional policy FAIR2Adapt 12.910284463894966 5.9 multiscale pyramid 10.755813953488373 7.4 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences dataset 15.754923413566738 7.2 satellite observation 24.27325581395349 16.7 Seine Valley Data Format 2026-03-20 18:12:17.997118+00:00 0 https://api.rohub.org/api/ros/fdc1c071-76d7-44df-a565-8217ebcc59fe/crate/download/ 2026-02-20 22:03:58.321018+00:00 2026-04-11 02:51:16.533696+00:00 2026-02-20 22:03:58.321018+00:00 Sentinel-2 Level-1C satellite observation converted to a HEALPix Discrete Global Grid System (DGGS) multiscale pyramid, covering a region in **Normandy, France** (Seine Valley, between Rouen and Paris). ### Dataset - **Variable**: Band 02 (Blue, 490nm) top-of-atmosphere reflectance - **Spatial coverage**: Normandy, France (~48.5°N–49.5°N, 0.5°E–1.5°E) - **Grid**: HEALPix multiscale pyramid (11 levels) - Finest: level 20 (nside=1,048,576, ~10m resolution, 208M cells) - Coarsest: level 10 (nside=1,024, ~10km resolution) - Resampling: mean aggregation between levels - **Format**: Cloud-optimized Zarr with nested HEALPix indexing on WGS84 ellipsoid ### FAIRification - Satellite imagery converted to DGGS using [xhealpixify](https://github.com/IAOCEA/xhealpixify) - Machine-actionable: `schema:ViewAction` links the dataset to the [FAIR2Adapt dashboard](https://fair2adapt.github.io/riomar-dashboard/) for interactive visualization at any zoom level - Metadata enriched with [I-ADOPT](https://i-adopt.github.io/) variable decomposition ### Context Part of the [FAIR2Adapt](https://fair2adapt.eu) project, demonstrating that the HEALPix DGGS approach works for both ocean model outputs and Earth observation data. The multiscale pyramid enables efficient visualization from global overview to full 10m resolution. application/ld+json https://w3id.org/ro-id/fdc1c071-76d7-44df-a565-8217ebcc59fe FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid) MANUAL Fouilloux, Anne. "FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid)." ROHub. Feb 20 ,2026. https://w3id.org/ro-id/fdc1c071-76d7-44df-a565-8217ebcc59fe. View Sentinel-2 data in FAIR2Adapt Dashboard