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14 results for “urbisphere”
Metadata for the urbisphere-Paris campaign during 2022-2024: fieldwork maintenance log [L1]
<p>Machine-readable, formatted and redacted electronic fieldwork logs from the urbisphere-Paris observation campaign conducted between 2022-09-05 and 2024-07-22 in Paris, France. Provided in text format with comma separated columns (.csv) and in Microsoft Excel (.xlsx) format.</p> <p>The fieldwork logs are created from raw google form data submitted by campaign managers, scientists, technicinas and students. The formatting process is detailed in https://github.com/Urban-Meteorology-Reading/urbisphere-paris-fieldwork-log-format. The GitHub output has then been manually edited and adjusted.</p> <p>Contains maintenance information for the following observational sites operated as part of the urbisphere Paris campaign 2022 - 2024:</p> <table> <tbody> <tr> <td>PAARBO</td> <td>Paris – Arboretum de Vallée-aux-Loups </td> </tr> <tr> <td>PAAUNA</td> <td>Paris – Aunay-sous-Auneau</td> </tr> <tr> <td>PABOBI</td> <td>Paris – Bobigny</td> </tr> <tr> <td>PABONN</td> <td>Paris – Bonniel</td> </tr> <tr> <td>PABPAC</td> <td>Paris – Balloon Parc Andre Citroën</td> </tr> <tr> <td>PACHAM</td> <td>Paris – Chamant</td> </tr> <tr> <td>PACHAN</td> <td>Paris – Changis-sur-Marne </td> </tr> <tr> <td>PACHEM</td> <td>Paris – Chemin Vert Bobigny</td> </tr> <tr> <td>PACOMP</td> <td>Paris – Compiègne</td> </tr> <tr> <td>PACOUR</td> <td>Paris – Courdimanche-sur-Essonne</td> </tr> <tr> <td>PACRET</td> <td>Paris – Créteil</td> </tr> <tr> <td>PADENF</td> <td>Paris – Denfert Rocherau </td> </tr> <tr> <td>PADROU</td> <td>Paris – Droue Sur Drouette</td> </tr> <tr> <td>PAHOTE</td> <td>Paris – Hôtel de Ville</td> </tr> <tr> <td>PAJUSS</td> <td>Paris – Jussieu </td> </tr> <tr> <td>PALUPD</td> <td>Paris – Université Paris Diderot (LISA Platform)</td> </tr> <tr> <td>PAMEUD</td> <td>Paris – Meudon</td> </tr> <tr> <td>PANANG</td> <td>Paris – Nangis</td> </tr> <tr> <td>PANATI</td> <td>Paris – Rue Nationale</td> </tr> <tr> <td>PAPRUN</td> <td>Paris – Prunay-le-Temple</td> </tr> <tr> <td>PAROIS</td> <td>Paris – Roissy</td> </tr> <tr> <td>PAROMA</td> <td>Paris – Romainville</td> </tr> <tr> <td>PASIRT</td> <td>Paris – SIRTA Observatory Palaiseau</td> </tr> <tr> <td>PASTFE</td> <td>Paris – Saint Félix</td> </tr> <tr> <td>PAWYDT</td> <td>Paris – Wy-dit-Joli-Village</td> </tr> </tbody> </table> <p> </p>
urbisphere-Berlin campaign BAMS data repository
<p>This data set accompanies Fenner et al. (2024) and contains the data (and references to data sources) of the plots and tables therein.</p> <p>Data are organized by Figure and Table in the article, each located in a separate (zip-)folder.</p> <p>See README.pdf for additional information and data descriptions.</p> <p>Detailed data processing details are given in the Appendices of the article.</p> <p>RAW measurement data are accessible via the <a title="Zenodo &ldquo;urbisphere&rdquo; community" href="../communities/urbisphere/" target="_blank" rel="noopener">Zenodo “urbisphere” community</a>.</p> <p> </p> <p>Fenner, D., Christen, A., Grimmond, S., Meier, F., Morrison, W., Zeeman, M., Barlow, J., Birkmann, J., Blunn, L., Chrysoulakis, N., Clements, M., Glazer, R., Hertwig, D., Kotthaus, S., König, K., Looschelders, D., Mitraka, Z., Poursanidis, D., Tsirantonakis, D., Bechtel, B., Benjamin, K., Beyrich, F., Briegel, F., Feigel, G., Gertsen, C., Iqbal, N., Kittner, J., Lean, H., Liu, Y., Luo, Z., McGrory, M., Metzger, S., Paskin, M., Ravan, M., Ruhtz, T., Saunders, B., Scherer, D., Smith, S. T., Stretton, M., Trachte, K. and Van Hove, M., 2024: urbisphere-Berlin campaign: Investigating multi-scale urban impacts on the atmospheric boundary layer. <em>Bull. Am. Meteorol. Soc. </em>DOI: <a href="https://doi.org/10.1175/BAMS-D-23-0030.1">10.1175/BAMS-D-23-0030.1</a><em><br></em></p> <p> </p>
urbisphere-Berlin Analysis Ready Geospatial dataset
<p>Analysis-Ready (ARD) Geospatial dataset (v3) for the administrative boundaries of Berlin produced by FORTH in the framework of urbisphere. The dataset includes a) Digital Surface Model (DSM) b) Digital Terrain Model (DTM) c) Building Heights d) Vegetation Heights e) Land Cover (SUEWS format i.e. 1=Paved/Impervious, 2=Buildings, 3=Evergreen Trees and Shrubs, 4=Deciduous Trees and Shrubs , 5=Grass, 6=Bare Soil, 7=Water) in raster format (.tif).</p> <p>Resolution: 1m<br>CRS: EPSG:25833<br>noData: -999 / -9999<br>compression: LZW</p> <p>Reference year: 2021</p> <p>LC reported overall accuracy 89% (v2)</p>
urbisphere_gb-london_UR-7: Gridded total road lengths by type for London, UK
<h2>Files in this Archive </h2> <ul> <li>London_road_lengths_by_type.zip <ul> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> <li>Total road lengths by road type (all lanes and traffic flow directions) in 500-m grid-boxes covering Greater London, UK</li> </ul> </li> <li>code.zip <ul> <li>Python3</li> <li>Process input road data in 500-m grid-boxes covering Greater London, UK </li> </ul> </li> <li>urbisphere_gb-london_UR-7.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support urbisphere–London modelling activities, including the generation of a travel route database for private vehicle transport on roads.</p> <h3>Linked with</h3> <ul> <li>McGrory et al. 2024. urbisphere_gb-london_UR-3: Transport database derived from UK road networks, OSM data, and TfL public transport timetables, for modelling in London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889780</li> <li>Hertwig et al. 2024. urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889756</li> </ul>
urbisphere_gb-london_UR-6: Gridded building information for London, UK
<h2>Files in this archive </h2> <ul> <li>London_sample_region_building_info.zip <ul> <li>Gridded building volume and population information in 500-m processing grids for a sample region in central London</li> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>auxiliary_data.zip <ul> <li>Auxiliary data for processing (*.csv)</li> </ul> </li> <li>code.zip <ul> <li>Process building data in 500-m grid-boxes covering London (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-6.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support APEx, <em>urbisphere</em>-London and ASSURE modelling activities for London, UK.</p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024. urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889756</li> </ul>
urbisphere_gb-london_UR-5: Gridded land-cover fractions for London, UK
<h2>Files in this archive </h2> <ul> <li>London_landcover.zip <ul> <li>Land-cover fractions in 500-m grid boxes covering Greater London, UK</li> <li>Polygons, ESRI shapefiles (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>code.zip <ul> <li>Code to process land cover (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-5.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support APEx, <em>urbisphere</em>-London and ASSURE modelling activities, including simulations with the Surface Urban Energy and Water Balance Scheme (<a href="https://suews.readthedocs.io/en/latest/">SUEWS</a>).</p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024. urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889756</li> </ul>
urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK
<h2>Files in this archive </h2> <ul> <li>London_500m_grid.zip <ul> <li>Grid with ~500 m horizontal resolution, covering Greater London, UK </li> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>code.zip <ul> <li>Code to produce the dataset (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-1.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>This dataset includes a grid with ~500 m horizontal resolution covering Greater London, UK. It is used to support <em>urbisphere</em>–London, APex and ASSURE modelling activities and analyses of socio-economic data. </p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024a. urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> <li>Hertwig et al. 2024b. urbisphere_presentations_UR-2: Connecting physical and socio-economic spaces for urban agent-based modelling, EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889885</li> <li>McGrory et al. 2024. urbisphere_presentations_UR-3: Dynamic Anthropogenic actiVities and feedback to Emissions (DAVE): An agent-based model for heat and exposure to other anthropogenic emissions. EMS Annual Meeting 2023 [Presentation]. Zenodo. https://doi.org/10.5281/zenodo.10889900</li> </ul>
urbisphere_gb-london_UR-4: Derivation of building thermal and radiative parameters for building energy modelling
<h2>Files in this archive </h2> <ul> <li>GB_layer_info.zip <ul> <li>Output and specifications from uBEMM_v1_27-3-2024.xlsx for further processing (*.csv)</li> </ul> </li> <li>GB_layer_processed.zip <ul> <li>Processed layer-specific thermal and radiative material parameters for UK building typologies (external wall, roofs, ground floors; *.csv)</li> </ul> </li> <li>GB_effective_parameters.zip <ul> <li>Processed effective thermal and radiative parameters of external walls, roofs, ground floors, windows, internal walls and internal floors for UK building typologies (*.csv)</li> </ul> </li> <li>uBEMM_v1_27-3-2024.xlsx <ul> <li>Tool to characterise building structure layers based on bulk thermal parameters</li> </ul> </li> <li>code.zip <ul> <li>Code for processing of building materials (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-4.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support APEx, <em>urbisphere</em>-London and ASSURE modelling activities of building energy exchanges in London. </p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024. urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> </ul>
urbisphere_de-berlin_UR-3: Gridded residential population data for Berlin and parts of Brandenburg, Germany
<h2>Files in this archive </h2> <ul> <li>respop_300m_grid_Berlin_Brandenburg.zip <ul> <li>Residential population numbers in 300-m grid-boxes covering Berlin and parts of Brandenburg, Germany</li> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>code.zip <ul> <li>Code to produce the dataset (Python3)</li> </ul> </li> <li>urbisphere_de-berlin_UR-3.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>Dataset contains residential population numbers and densities for Berlin and Brandenburg, Germany, aggregated to regular grids of ~300 m horizontal resolution for 2021. The data support <em>urbisphere</em>–Berlin characterisation of observations undertaken in the region and modelling activities. </p> <h3>Linked with</h3> <ul> <li>Glazer et al. 2024. urbisphere_de-berlin_UR-1: <em>urbispher</em>e-Berlin Model grids defined for use with the Unified Model (UM). <em>urbisphere</em>–Berlin Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889490</li> <li>Hertwig et al. 2024. urbisphere_de-berlin_UR-2: Gridded building volumes for Berlin and parts of Brandenburg, Germany. <em>urbisphere</em>–Berlin Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889609</li> </ul> <p> </p>
urbisphere_de-berlin_UR-2: Gridded building volumes for Berlin and parts of Brandenburg, Germany
<h2>Files in this archive</h2> <ul> <li>buildvolume_300m_grid_Berlin_Brandenburg.zip <ul> <li>Building volumes by function categories in 300-m grid-boxes covering Berlin and parts of Brandenburg, Germany</li> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>auxiliary_data.zip <ul> <li>Auxiliary data for the processing (*.csv).</li> </ul> </li> <li>code.zip <ul> <li>Code to produce dataset (Python3)</li> </ul> </li> <li>urbisphere_de-berlin_UR-2.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>This dataset contains aggregated building volumes of residential (i.e., domestic), non-residential (non-domestic) and mixed-use buildings for Berlin and Brandenburg, Germany, in regular grids of ~300 m horizontal resolution. The data support <em>urbisphere</em>–Berlin characterisation of observations undertaken in the region and modelling activities. </p> <h3>Linked with</h3> <ul> <li>Glazer et al. 2024. urbisphere_de-berlin_UR-1: urbisphere-Berlin Model Grids defined for use with the Unified Model (UM). <em>urbisphere</em>–Berlin Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889490</li> <li>Hertwig et al. 2024. urbisphere_de-berlin_UR-3: Gridded residential population data for Berlin and parts of Brandenburg, Germany. <em>urbisphere</em>–Berlin Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889632</li> </ul>
urbisphere_de-berlin_UR-1: urbisphere-Berlin Model grids defined for use with the Unified Model (UM)
<h2>Files in this archive </h2> <ul> <li>urbisphere-de-berlin_umgrids.zip <ul> <li>UM model grids</li> </ul> </li> <li>urbisphere-de-berlin_unrotated_umgrids.zip <ul> <li>grid files in CRS EPSG:4326 - WGS84</li> </ul> </li> <li>1p5_L70_zlvls.csv <ul> <li>UM model vertical levels height above surface (m)</li> </ul> </li> <li>0p3_L70_zlvls.csv <ul> <li>UM model vertical levels height above surface (m)</li> </ul> </li> <li>0p1_L140_zlvls.csv <ul> <li>UM model vertical levels height above surface (m)</li> </ul> </li> <li>um_unrotate.py <ul> <li>Program used to rotate the UM grid files (Python 3.10.125)</li> </ul> </li> <li>urbisphere_de-berlin_UR-1.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose</h2> <p>The dataset is used as part of the <em>urbisphere</em>-Berlin multi-scale modelling activities, including the numerical weather prediction (NWP) and observation site characterization. As the UK Met Office (UKMO) Unified Model (UM) uses a rotated pole projection to construct the model grid, there are two versions of the model grid: (1) unrotated used for the UM NWP modelling, and (2) rotated for data presentation, other local scale modelling and to complement analysis of atmospheric observations and surveys.</p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024a. urbisphere_de-berlin_UR-2: Gridded building volumes for Berlin and parts of Brandenburg, Germany. urbisphere–Berlin Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889609 </li> <li>Hertwig et al. 2024b. urbisphere_de-berlin_UR-3: Gridded residential population data for Berlin and parts of Brandenburg, Germany. urbisphere–Berlin Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889632</li> </ul>
urbisphere_gb-london_UR-2: Activities profiles derived from UK Time Use Survey data for modelling
<h2>Files in this archive </h2> <ul> <li>UK_TUS2014-15_activity_profiles_190324.zip <ul> <li>Activity profile dataset derived from the UK Time Use Survey (2014/15; *.csv) </li> </ul> </li> <li>auxiliary_data.zip <ul> <li>Auxiliary datasets created for processing</li> </ul> </li> <li>AppliancePowerManufacturer.zip <ul> <li>Information used to assigned values</li> </ul> </li> <li>code.zip <ul> <li>Code to produce the dataset</li> <li>Python3.9 Jupyter notebook</li> </ul> </li> <li>urbisphere_gb-london_UR-2.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>People’s activities change through the day and between days. Information about human behaviour and the changing locations where activities occur are used in neighbourhood scale agent-based models of anthropogenic heat fluxes and building scale energy modelling to give realistic occupancy and activity-based energy-use timings.</p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024a: urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> <li>Hertwig et al. 2024b: urbisphere_presentations_UR-2: Connecting physical and socio-economic spaces for urban agent-based modelling, EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889885</li> <li>McGrory et al. 2024: urbisphere_presentations_UR-3: Dynamic Anthropogenic actiVities and feedback to Emissions (DAVE): An agent-based model for heat and exposure to other anthropogenic emissions. EMS Annual Meeting 2023 [Presentation]. Zenodo. https://doi.org/10.5281/zenodo.10889900</li> </ul>
urbisphere_gb-london_UR-3: Transport database derived from UK road networks, OSM, and TfL public transport timetables, for modelling in London, UK
<h2><strong>Files included in this archive</strong></h2> <p><strong>Documentation</strong></p> <ul> <li> urbisphere_London_transport_database.pdf</li> </ul> <p><strong>JSON Database files</strong> (JSON: <a href="https://www.loc.gov/preservation/digital/formats/fdd/fdd000381.shtml">https://www.loc.gov/preservation/digital/formats/fdd/fdd000381.shtml</a> (<em>last accessed: 30/3/2024</em>))</p> <ul> <li>driving_transport.json <ul> <li>Database of driving routes</li> </ul> </li> <li>cycling_transport.json <ul> <li>Database of cycling routes</li> </ul> </li> <li>walking_transport.json <ul> <li>Database of walking routes</li> </ul> </li> <li>public_transport.json <ul> <li>Database of public transport routes</li> </ul> </li> </ul> <p><strong>Python 3.9 Code</strong></p> <ul> <li>London_travel_dictionaries.py <ul> <li>to create databases</li> </ul> </li> <li>assign_speed_limits.py <ul> <li> to assign OSM speed limits to each road in GLA</li> </ul> </li> <li>reduce_sub_services.py <ul> <li> to group transport routes within the TfL timetables</li> </ul> </li> </ul> <h2>Data purpose</h2> <p>This dataset contains transport routes for walking, driving, cycling, and public transport (train, tube, and bus) within the Greater London (GLA), which can be used for simulations of human behaviour and movement, for example using agent-based models (e.g. Capel-Timms et al. 2021, McGrory et al. 2024b).</p> <h3><em>Associated publications</em></h3> <ul> <li>Hertwig et al. 2024b: urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> <li>Hertwig et al. 2024c: urbisphere_gb-london_UR-7: Gridded total road lengths by type for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset].. Zenodo. https://doi.org/10.5281/zenodo.10889841</li> <li>McGrory et al. 2024a: urbisphere_presentations_UR-3: Dynamic Anthropogenic actiVities and feedback to Emissions (DAVE): An agent-based model for heat and exposure to other anthropogenic emissions. EMS Annual Meeting 2023 [Presentation].. Zenodo. https://doi.org/10.5281/zenodo.10889900</li> </ul> <div> <div> </div> <div> <p> </p> </div> </div>
Data from Radiosounding System (RSS) measurements during the urbisphere-Berlin campaign from 2022-03-28 to 2022-08-11 [RAW]
<p>Original data files from RSS measurements.</p>
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