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106 results for “map projections”
Malthi Mapping Project 2016
Malthi is a fortified hilltop settlement on the northern spur of the Ramovouni Hill, overlooking the Soulima Valley in northern Messenia, Greece. It was inhabited during the Middle and Late Bronze Ages (ca. 1800-1200 BCE). Over one hundred rooms, many of which were constructed along the interior façade of the fortification, were excavated by Natan Valmin between 1926 and 1935. Since 2015, [Michael Lindblom](http://www.arkeologi.uu.se/Research/Presentations/michael-lindblom/?languageId=1) and [Rebecca Worsham](http://classics.unc.edu/people/graduate-students/rebecca-worsham/) have resumed studies of the settlement in order to better understand its chronology and development. 300 hectares were scanned on two days, June 13-14 2016, in a UAS survey with a DJI Phantom 3 Pro. 667 photos were used to create this model, giving a maximum orthophoto resolution of 10,7 cm. Co-pilot [Kalle Lindholm](http://www.arkeologi.uu.se/Research/Presentations/karl-johan-lindholm/). [Location](https://goo.gl/maps/Byo8EeuAcCG2) Source: Objaverse 1.0 / Sketchfab
SYMBA project Industrial Symbiosis mapping
<p>The dataset includes the infomation collected during the elaboration of the Industrial Symbiosis (IS) mapping carried out in the framework of the SYMBA project (101135562). Concretely, it compiles the data included in the deliverable D3.1 Report on current Industrial Symbiosis solutions in Europe.</p> <p>The updated v3.0 of the dataset includes the prioritisation of IS solutions, resulting from the application of the Multicriteria Decision Analysis (MCDA) methodology developed under the SYMBA project. This prioritisation, detailed in Deliverable D3.3: Evaluation of IS Prioritised Solutions, applies weighted scoring factors across five readiness dimensions: Symbiosis, Environmental, Societal, Organisational, and Legal/Ethical. The weighting factors used for prioritisation are presented in the adjacent table. For more in-depth insight into the evaluation and prioritisation approach, consult Deliverable D3.3.</p>
IRIS Carbon Mapping Project: Curated Dataset
<p>Dataset to support IRIS Carbon Mapping Project final report.</p>
First picture of the Deep Mapping Project
<p>This is a picture taken by a professionnal kitesurfer in Le Morne, Mauritius.</p>
Mapping the potential habitat suitability, and opportunities of bush encroacher species in Southern Africa: a case study of the SteamBioAfrica project.
<p>Senegalia mellifera (Benth) Seigler & Ebinger. , Dichrostachys cinerea (L.) Wight & Arn. and Terminalia sericea Burch. Ex DC., are three important bush encroacher species that contribute to the well-known ecological process named "thicketization" in Southern Africa. This issue has persisted for many years, impacting species distribution, plant communities, soil, and fauna dynamics. According to climate change projections, Southern Africa is expected to become drier and warmer in future scenarios, creating favourable conditions for proliferation of bush encroacher species.</p> <p>In the paper, we analyze the habitat suitability of these bush encroachers through MaxEnt 3.4.4 under three different future climate models and scenarios. Future projections were made using the shared socio-economic pathways (SSPs) for greenhouse gas concentrations, specifically SSP245-585 across two-time horizons: 2041-2060 and 2061-2180. We utilized <a href="https://www.worldclim.org/data/cmip6/cmip6climate.html">WorldClim 1-km resolution climate data</a> from three global Earth System Models (ESMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) that obtained better results than CMIP5 models (Bouramdane 2022; Mmame and Ngongondo 2024): the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2-HR), the Hadley Climate Center Earth System Model (UK-ESM1.0-LL) and the Institute Model for Numerical Mathematics (INM-CM5-0). </p>
Augmented Spaces and Maps, research project 2015–2019
<div> <p>"Augmented Space” (2015-2019) is a research project initiated by Dr. Christine Schranz which brings together both theoretical and and practical parts as a basic introduction to the field of digital cartographies. Complementary to the book publication “Augmented Spaces and Maps. Das Design von kartenbasierten Interfaces”, the AR application offers a historical perspective on the Campus of the Arts (formerly the site of the Basel bonded warehouse) and combines this view with a contemporary critique of the practice of art-related bonded warehouses. The project was carried at the FHNW Academy of Arts and Design in Basel, with the support from the Swiss National Science Foundation (SNSF).</p> <p>Principal Investigator, Book Editor: Dr. Christine Schranz</p> <p>Video Production: Maria Smigielska</p> </div>
A Systematic Mapping Study on Student Reflection in Software Engineering Project-Based Learning (supplementary material)
<p>This repository contains supplementary material for the manuscript "A Systematic Mapping Study on Student Reflection in Software Engineering Project-Based Learning". The CSV file is structured as follows:</p> <ul> <li>Column A represents the paper citation key generated by Zotero that we used as a unique identifier for all papers in this study.</li> <li>Columns B-I include the results of our data extraction as per the data extraction form.</li> <li>Columns J-AB include metadata about each paper.</li> </ul>
A map showing the locations of instruments used during the Convective Storm Initiation Project (CSIP) pilot
The CSIP pilot project was conducted in July 2004 centred around the Chilbolton radar facility where there is a 25 metre radar dish with two of the most sophisticated meteorological radars in the world. The pilot project utilised many of the instruments and facilities from the NCAS Universities' Facility for Atmospheric Measurement (UFAM) including a Cessna aircraft, wind profiler, Doppler lidar, sodar and automatic weather stations and scientists from the universities of Aberystwyth, Leeds, Reading, Salford, Essex, Bath and UMIST as well also from the Met Office.
Results of the crowd-mapping action within the project TeRRIFICA [Dataset No. 2 dated 2023-01-19]
<p>The dataset includes the results of the crowd-mapping action within the project "Territorial RRI fostering innovative climate action" - TeRRIFICA (Horizon 2020 under GA 824489) dated 2023-01-19. The data are points added to the map by the users (volunteers) and represent locations where climate change-related issues occur regarding air temperature, air quality, water, soil, and wind (SPOTS). The second part of the dataset is related to the crowd-mapping users and their anonymized characteristics (USERS). More details are available at https://terrifica.eu/.</p>
Shifts in Mapping, research project 2018–2021
<p>“Shifts in Mapping” (2018-2021) is a fundamental research project initiated by Dr. Christine Schranz with a focus on digital maps and critical mapping, carried at the FHNW Academy of Arts and Design in Basel, with the support from the Swiss National Science Foundation (SNSF).<br> <br> Principal Investigator, Book Editor, Exhibition Co-Curator: Dr. Christine Schranz<br> <br> Video Production: Maria Smigielska<br> Soudtrack: Vodovoz Music Production</p>
Source Index Map Layer for High-Resolution Orthorectified Imagery from Approximately 1990, Niwot Ridge LTER Project Area, Colorado
Citation Manley, W.F., Parrish, E.G., and Lestak, L.R., 2009, High-Resolution Orthorectified Imagery and Digital Elevation Models for Study of Environmental Change at Niwot Ridge and Green Lakes Valley, Colorado: Niwot Ridge LTER, INSTAAR, University of Colorado at Boulder, digital media. This vector shapefile is a source index map layer for the mosaic of orthorectified aerial photography from 1988 and 1990 for the Niwot Ridge Long Term Ecological Research (LTER) project. The index also covers the Green Lakes Valley portion of the Boulder Creek Critical Zone Observatory (CZO). The index polygons are attributed with source photo date and photo year. The mosaic is derived from approx. 1:40,000 scale, color infrared (CIR) photographs acquired by the United States Geological Survery (USGS) National Aerial Photography Program (NAPP). Other datasets available in this series includes orthorectified aerial photograph mosaics (for 1953, 1972, 1985, approximately 1990, 1999, 2000, 2002, 2004, 2006 and 2008), digital elevation models (DEM's), and accessory map layers. Together, the DEM's and imagery will be of interest to students, research scientists, and others for observation and analysis of natural features and ecosystems. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
Metrics Literacies research project mapped to Knowledge two Action (K2A) framework
<p><strong>Schematic representation of the Metrics Literacies research project mapped onto the Knowledge to Action (K2A) framework </strong></p> <p>Based on K2A framework proposed by:</p> <p>Wilson, K. M., Brady, T. J., Lesesne, C., & NCCDPHP Work Group on Translation. (2011). An organizing framework for translation in public health: The Knowledge to Action Framework. <em>Preventing Chronic Disease</em>, <em>8</em>(2), A46. PMID: 21324260</p> <p> </p>
Map-projected time-lapse of zebrafish left-right somite formation
<p>Zebrafish embryos in their chorions were imaged from 6 angles in a multiview light sheet microscope. The imaging was started 10 hours post fertilization and was performed for about 4 to 5 hours at a frame interval of 5 min. The resulting images were fused using FIJI, followed by nuclei detection in the fused images and map projection. This data set contains map projected time-lapses of 6 utr::mcherry transgenic embryos. Utrophin binds to actin filaments and was used as a somite boundary marker. The pixel size varies spatially in a map as well as across different projection layers in a single time-lapse. The corresponding Map_pixel_size mat file for each time-lapse contains respective pixel sizes.</p>
Data from: Incorporating interspecific competition into species-distribution mapping by upward scaling of small-scale model projections to the landscape
There are a number of overarching questions and debate in the scientific community concerning the importance of biotic interactions in species distribution models at large spatial scales. In this paper, we present a framework for revising the potential distribution of tree species native to the Western Ecoregion of Nova Scotia, Canada, by integrating the long-term effects of interspecific competition into an existing abiotic-factor-based definition of potential species distribution (PSD). The PSD model is developed by combining spatially explicit data of individualistic species' response to normalized incident photosynthetically active radiation, soil water content, and growing degree days. A revised PSD model adds biomass output simulated over a 100-year timeframe with a robust forest gap model and scaled up to the landscape using a forestland classification technique. To demonstrate the method, we applied the calculation to the natural range of 16 target tree species as found in 1,240 provincial forest-inventory plots. The revised PSD model, with the long-term effects of interspecific competition accounted for, predicted that eastern hemlock (Tsuga canadensis), American beech (Fagus grandifolia), white birch (Betula papyrifera), red oak (Quercus rubra), sugar maple (Acer saccharum), and trembling aspen (Populus tremuloides) would experience a significant decline in their original distribution compared with balsam fir (Abies balsamea), black spruce (Picea mariana), red spruce (Picea rubens), red maple (Acer rubrum L.), and yellow birch (Betula alleghaniensis). True model accuracy improved from 64.2% with original PSD evaluations to 81.7% with revised PSD. Kappa statistics slightly increased from 0.26 (fair) to 0.41 (moderate) for original and revised PSDs, respectively.
Gridded maps of global population scaled to match the 2023 Wittgenstein Center (WIC) Population projections
<p>The gridded population data used for calculating exposed populations is based on the population projections from the original SSPs (KC and Lutz, 2017) which were subsequently gridded (Jones and O’Neill, 2016). These gridded projections were aggregated to 0.5 ° spatial resolution and then scaled to match the latest available projections for population in line with the updated SSPs, v3.0 (KC <em>et al.</em>, 2024). The scaling is done on a country basis for all countries included in the latest SSP projections. Countries, which are not included in these projections, remain unchanged. The scaling process is done on a country-level basis using the following step:<br> </p> <ol> <li>The total population for the original gridded data is calculated using the ISIMIP fractional country raster (Perrette, 2023), excluding border cells containing contributions from more than one country.</li> <li>The population of the fractional border cells is subtracted from the total population of the SSP population projections and the required scalar to match the population from the gridded data to the SSP population projections is calculated.</li> <li>This scalar is applied to all non-fractional cells. </li> </ol> <p>While it is possible to calculate the scalar for each country including the proportion of the population in the fractional border cells, this would require the scalar to also be applied to that proportion of the population in the border cells to match the overall population number for each country. Applying different scalars to the population proportions for each country in the same cell would, however, change the ratios of the population in the fractional border cells and subsequently lead to skewed results when reapplying the fractional country raster to the scaled data for the aggregation to country level. For small countries, where more population lives in fractional border cells than in non-border cells, and for countries that only consist of border cells with contributions from more than one country, all cells were used in the scaling process. <br><br>It should be noted that some smaller countries cannot be scaled properly and that the latest SSP population projections do not contain values for all countries. Since there has been no release of updated gridded population projections yet, the gridded population data created using this approach still provide the closest match to the latest SSP population projections currently available.</p>
ECFAS Mapping products, Deliverable 5.5 – Mapping products – ECFAS Project (GA 101004211), www.ecfas.eu
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p><p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p><p><i><strong>Description of the product</strong></i></p><p>The deliverable includes a document and a compressed directory with ready-to-print maps, the associated geospatial datasets and symbology files. All products were developed under Task 5.5 – Mapping products.<br>The document reports on the activities conducted during Task 5.5 – Mapping products that aimed at demonstrating the added value of the ECFAS products and propose adequate representation for communication and integration into the Copernicus Emergency Management Services. Five Demonstration cases, corresponding each to one recent coastal event and one location, were selected to highlight the ECFAS products resulting of the coastal Flood, Impacts and Shoreline position tools developed previously during the ECFAS activities. The Mapping products prepared for each demonstration case are provided along the document in cartographic formats (ready-to-print maps), along with the symbology files and geospatial datasets that were used to create the products.</p><p>This <strong>dataset</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of this dataset are licensed under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p><p>This <strong>Report</strong> is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p><p><i><strong>Disclaimer:</strong></i></p><p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p><p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p><p> </p><p> </p>
Shorelines dataset. Deliverable 3.2 - Algorithms for satellite derived shoreline mapping and shorelines dataset, ECFAS project (GA 101004211), www.ecfas.eu.
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p> <p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p> <p><em><strong>Reference literature:</strong></em></p> <p><em><strong>Palomar-Vázquez, J.; Pardo-Pascual, J.E.; Almonacid-Caballer, J.; Cabezas-Rabadán, C. Shoreline Analysis and Extraction Tool (SAET): A New Tool for the Automatic Extraction of Satellite-Derived Shorelines with Subpixel Accuracy. Remote Sens. 2023, 15, 3198. <a href="https://doi.org/10.3390/rs15123198">https://doi.org/10.3390/rs15123198</a></strong></em></p> <p><em><strong>J.E. Pardo-Pascual, J. Almonacid-Caballer, C. Cabezas-Rabadán, A. Fernández-Sarría, C. Armaroli, P. Ciavola, J. Montes, P.E. Souto-Ceccon, J. Palomar-Vázquez: Assessment of satellite-derived shorelines automatically extracted from Sentinel-2 imagery using SAET. Coastal Engineering, 2023, 104426, ISSN 0378-3839, <a href="https://doi.org/10.1016/j.coastaleng.2023.104426">https://doi.org/10.1016/j.coastaleng.2023.104426</a>.</strong></em></p> <p><em>Pardo-Pascual, J. E., Cabezas-Rabadán, C., Palomar-Vázquez, J., Fernández-Sarría, A., Almonacid-Caballer, J., Souto-Ceccon, P. E., Montes, J., Armaroli, C., and Ciavola, P.: Satellite-derived shorelines extracted using SAET for characterizing the effect of Storm Gloria in the Ebro Delta (W Mediterranean), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9856, <a href="https://doi.org/10.5194/egusphere-egu22-9856">https://doi.org/10.5194/egusphere-egu22-9856</a>, 2022.</em></p> <p>In relation to <strong>SAET</strong>, additional information, instructions and the <strong>open-source code</strong> are available here <a href="https://doi.org/10.5281/zenodo.5807710"><strong>https://zenodo.org/records/10256957</strong></a> and also in <strong>GitHub </strong>here<strong> <a href="https://github.com/jpalomav/SAET_master">https://github.com/jpalomav/SAET_master</a></strong></p> <p> </p> <p><strong>Description of the containing files inside the Dataset</strong></p> <p>The deliverable includes two different files: the dataset of shorelines and the accompanying report.</p> <p>The report describes the structure of the dataset of shorelines produced in Task 3.2 - Shoreline mapping validation and calibration and described in Deliverable 3.2 - Algorithms for satellite derived shoreline mapping and shorelines dataset (DOI: 10.5281/zenodo.5807711).</p> <p>The dataset is composed of three folders.</p> <ol> <li>The first folder ("SDS_vs_VHR_shoreline") contains the SDSs extracted at each test site by the different algorithms tested in ECFAS (SHOREX, Cabezas-Rabadán et al., 2021; Sánchez-García et al., 2020; CoastSat, Vos et al., 2019a,b and SAET, Palomar-Vázquez et al., 2021; Pardo-Pascual et al., 2021) to assess their performance through the comparison with shorelines photo-interpreted on coincident VHR satellite images. The SDSs obtained at all the test sites using SAET and CoastSAT are included, as well the SDSs obtained using SHOREX at the Spanish test sites. The photo-interpreted shorelines are also provided. For all the test sites it is provided the line separating the instantaneous shoreline (water/land boundary), obtained by photo-interpretation. For the sites in the Netherlands, also the wet/dry line is provided.</li> <li>The second folder ("SDS_vs_video-monitored_shorelines") presents for each of the three test sites the SDSs obtained using the different algorithms and video-derived shorelines. The SDSs at the beaches of la Victoria and Cala Millor were obtained using SAET, SHOREX and CoastSAT. In the case of Gerakas Beach, the shorelines were obtained using SAET and CoastSAT.</li> <li>The third folder ("SDS_SAET_Storm_cases") includes eight examples in different European coasts in which the SDSs before and after a storm have been obtained.</li> </ol> <p>This <strong>ECFAS dataset of shorelines</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of the ECFAS dataset of shorelines are licensed under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p> <p>This <strong>Report</strong> is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p> <p> </p> <p><em><strong>Disclaimer:</strong></em></p> <p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p> <p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p> <p> </p>
ECFAS Pan-EU Flood Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211), https://www.ecfas.eu/
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p> <p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p> <p><em><strong>Reference literature:</strong></em></p> <p><em><strong>Le Gal, M., Fernández-Montblanc, T., Duo, E., Montes Perez, J., Cabrita, P., Souto Ceccon, P., Gastal, V., Ciavola, P., and Armaroli, C.: A new European coastal flood database for low–medium intensity events, Nat. Hazards Earth Syst. Sci., 23, 3585–3602, <a href="https://doi.org/10.5194/nhess-23-3585-2023">https://doi.org/10.5194/nhess-23-3585-2023</a>, 2023.</strong></em></p> <p><strong>Description of the Dataset</strong></p> <p>The present database gathers flood and velocity maps for the European Union coast as well as their associated forcing parameters. The coast is divided into geographic regions embracing similar oceanographic conditions and subsequently into coastal sectors. The coastal sectors can be identified by its region index RXXX and its own index CSYYY. For each coastal sector, flood models were developed using the LISFLOOD-FP model with a grid resolution of 100 m. The flood model configuration follows the recommendation highlighted in ECFAS Deliverable D5.2 - Validated LISFLOOD-FP model for coastal areas. The flood and velocity maps are associated with synthetic storms that are characterised by a specific extreme water level and storm duration. These parameters were derived from Extreme Value Analyses performed on the ECFAS ANYEU-SSL hindcast (ECFAS D4.1 - Report on the calibration and validation of hindcasts and forecasts of TWL and D4.3 - Report on the identification of local thresholds of TWL for triggering coastal flooding). Five extreme water level values for each coastal point of the hindcast, and three durations (12, 24 and 36 h) were identified leading to 15 scenarios for each coastal sector. The flood and velocity maps are gathered into a NetCDF file for each coastal sector indicating the scenario parameters as attributes. In addition, the extreme water level values used for each coastal sector are contained in a complementary NetCDF file.</p> <p>The shapefile of the polygons defining the coastal sectors as defined for the catalogue implementation is included in the database.</p> <p><strong>- The ECFAS Flood Catalogue was used to produce the associated ECFAS Pan-EU Impact Catalogue:</strong></p> <p><strong>Impact Catalogue in Zenodo</strong>: Duo, E., Montes Pérez, J., Le Gal, M., Souto Ceccon, P.E., Cabrita, P., Fernández Montblanc, T., and Ciavola, P., 2022. ECFAS Pan-EU Impact Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211). <a href="http://www.ecfas.eu/">www.ecfas.eu</a> [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6778864">https://doi.org/10.5281/zenodo.677865</a></p> <p><em><strong>Impact Catalogue Reference literature</strong>: Duo, E., Montes, J., Le Gal, M., Fernández-Montblanc, T., Ciavola, P., and Armaroli, C.: Validated probabilistic approach to estimate flood direct impacts on the population and assets on European coastlines, Nat. Hazards Earth Syst. Sci., 25, 13–39, <a href="https://doi.org/10.5194/nhess-25-13-2025">https://doi.org/10.5194/nhess-25-13-2025</a>, 2025.</em></p> <p> </p> <p>The Flood Catalogue is accompanied by a technical document describing methods, datasets, structure, format and content of the ECFAS Flood and Impact Catalogues:</p> <p>Duo, E., Le Gal, M., Souto Ceccon, P.E., Montes Pérez, J., 2022. <a href="https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5ee287a5d&appId=PPGMS">Technical document</a> on the ECFAS Flood and Impact Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211). <a href="http://www.ecfas.eu/">www.ecfas.eu</a></p> <p> </p> <p>This ECFAS <strong>Flood Catalogue</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of the Flood Catalogue are licensed under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p> <p>This <strong>technical document</strong> describing methods, datasets, structure, format and content of the ECFAS Flood and Impact Catalogues is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p> <p>*The size of the uncompressed dataset is 124 GB.</p> <p> </p> <p><em><strong>Disclaimer:</strong></em></p> <p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p> <p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p> <p> </p>
linguistlist/LL-MAP: LL-MAP: Language and Location - A Map Annotation Project
No description provided.
Mapping the Health Status of the Population of French Polynesia: the MATAEA Project
ClinicalTrials.gov study NCT06133400. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.