62 datasets found
  1. GIS Data and Analysis for Cooling Demand and Environmental Impact in The...

    • zenodo.org
    • data.niaid.nih.gov
    Updated Apr 24, 2025
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    Simon van Lierde; Simon van Lierde (2025). GIS Data and Analysis for Cooling Demand and Environmental Impact in The Hague [Dataset]. http://doi.org/10.5281/zenodo.8344581
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    Dataset updated
    Apr 24, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Simon van Lierde; Simon van Lierde
    Area covered
    The Hague
    Description

    This dataset contains raw GIS data sourced from the BAG (Basisregistratie Adressen en Gebouwen; Registry of Addresses and Buildings). It provides comprehensive information on buildings, including advanced height data and administrative details. It also contains geographic divisions within The Hague. Additionally, the dataset incorporates energy label data, offering insights into the energy efficiency and performance of these buildings. This combined dataset serves as the backbone of a Master's thesis in Industrial Ecology, analysing residential and office cooling and its environmental impacts in The Hague, Netherlands. The codebase of this analysis can be found in this Github repository: https://github.com/simonvanlierde/msc-thesis-ie

    The dataset includes a background research spreadsheet containing supporting calculations. It also presents geopackages with results from the cooling demand model (CDM) for various scenarios: Status quo (SQ), 2030, and 2050 scenarios (Low, Medium, and High)

    Background research data

    The background_research_data.xlsx spreadsheet contains comprehensive background research calculations supporting the shaping of input parameters used in the model. It contains several sheets:

    • Cooling Technologies: Details the various cooling technologies examined in the study, summarizing their characteristics and the market penetration mixes used in the analysis.
    • LCA Results of Ventilation Systems: Provides an overview of the ecoinvent processes serving as proxies for the life-cycle impacts of cooling equipment, along with calculations of the weight of cooling systems and contribution tables from the LCA-based assessment.
    • Material Scarcity: A detailed examination of the critical raw material content in the material footprint of ecoinvent processes, representing cooling equipment.
    • Heat Plans per Neighbourhood: Forecasts of future heating solutions for each neighbourhood in The Hague.
    • Building Stock: Analysis of the projected growth trends in residential and office building stocks in The Hague. AC Market: Market analysis covering air conditioner sales in the Netherlands from 2002 to 2022.
    • Climate Change: Computations of climate-related parameters based on KNMI climate scenarios.
    • Electricity Mix Analysis: Analysis of future projections for the Dutch electricity grid and calculations of life-cycle carbon intensities of the grid.

    Input data

    Geographic divisions

    • The outline of The Hague municipality through the Municipal boundaries (Gemeenten) layer, sourced from the Administrative boundaries (Bestuurlijke Gemeenten) dataset on the PDOK WFS service.
    • District (Wijken) and Neighbourhood (Buurten) layers were downloaded from the PDOK WFS service (from the CBS Wijken en Buurten 2022 data package) and clipped to the outline of The Hague.
    • The 4-digit postcodes layer was downloaded from PDOK WFS service (CBS Postcode4 statistieken 2020) and clipped to The Hague's outline. The postcodes within The Hague were subsequently stored in a csv file.
    • The census block layer was downloaded from the PDOK WFS service (from the CBS Vierkantstatistieken 100m 2021 data package) and also clipped to the outline of The Hague.
    • These layers have been combined in the GeographicDivisions_TheHague GeoPackage.

    BAG data

    • BAG data was acquired through the download of a BAG GeoPackage from the BAG ATOM download page.
    • In the resulting GeoPackage, the Residences (Verblijfsobject) and Building (Pand) layers were clipped to match The Hague's outline.
    • The resulting residence data can be found in the BAG_buildings_TheHague GeoPackage.

    3D BAG

    • Due to limitations imposed by the PDOK WFS service, which restricts the number of downloadable buildings to 10,000, it was necessary to acquire 145 individual GeoPackages for tiles covering The Hague from the 3D BAG website.
    • These GeoPackages were merged using the ogr2ogr append function from the GDAL library in bash.
    • Roof elevation data was extracted from the LoD 1.2 2D layer from the resulting GeoPackage.
    • Ground elevation data was obtained from the Pand layer.
    • Both of these layers were clipped to match The Hague's outline.
    • Roof and ground elevation data from the LoD 1.2 2D and Pand layers were joined to the Pand layer in the BAG dataset using the BAG ID of each building.
    • The resulting data can be found in the BAG_buildings_TheHague GeoPackage.

    Energy labels

    • Energy labels were downloaded from the Energy label registry (EP-online) and stored in energy_labels_TheNetherlands.csv.

    UHI effect data

    • A bitmap with the UHI effect intensity in The Hague was retrieved from the from the Dutch Natural Capital Atlas (Atlas Natuurlijk Kapitaal) and stored in UHI_effect_TheHague.tiff.

    Output data

    • The residence-level data joined to the building layer is contained in the BAG_buildings_with_residence_data_full GeoPackage.
    • The results for each building, according to different scenarios, are compiled in the buildings_with_CDM_results_[scenario]_full GeoPackages. The scenarios are abbreviated as follows:
      • SQ: Status Quo, covering the 2018-2022 reference period.
      • 2030: An average scenario projected for the year 2030.
      • 2050_L: A low-impact, best-case scenario for 2050.
      • 2050_M: A medium-impact, moderate scenario for 2050.
      • 2050_H: A high-impact, worst-case scenario for 2050.

  2. a

    STORMWATER

    • arc-garc.opendata.arcgis.com
    • opendata.atlantaregional.com
    Updated Mar 25, 2019
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    City of East Point (2019). STORMWATER [Dataset]. https://arc-garc.opendata.arcgis.com/maps/eastpointgis::stormwater/about
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    Dataset updated
    Mar 25, 2019
    Dataset authored and provided by
    City of East Point
    Area covered
    Description

    On January 25, 2018 FEMA replaced this map with a new NFHL map with additional functionality which allows users to print official flood maps. On April 1, 2018 this map and NFHL link will no longer function. Please update your bookmark to https://hazards-fema.maps.arcgis.com/apps/webappviewer/index.html?id=8b0adb51996444d4879338b5529aa9cd. For more information on NFHL data availability, please visit the NFHL GIS Services page at https://hazards.fema.gov/femaportal/wps/portal/NFHLWMSAs of August 1, 2017 all FEMA systems will require the use of the “https” protocol, and “http” links will no longer function. This may impact NFHL web services. The FEMA GeoPlatform (including this map) will not be affected by this change. For more information on how NFHL GIS services will be impacted, please visit the NFHL GIS Services page at https://hazards.fema.gov/femaportal/wps/portal/NFHLWMS.An NFHL FIRMette print service is now available HERE. (For a video tutorial, click here.)OverviewThe National Flood Hazard Layer (NFHL) dataset represents the current effective flood data for the country, where maps have been modernized. It is a compilation of effective Flood Insurance Rate Map (FIRM) databases and Letters of Map Change (LOMCs). The NFHL is updated as studies go effective. For more information, visit FEMA's Map Service Center (MSC). Base Map ConsiderationsThe default base map is from a USGS service and conforms to FEMA's specification for horizontal accuracy. This base map from The National Map (TNM) consists of National Agriculture Imagery Program (NAIP) and high resolution orthoimagery (HRO) that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a map. This map should be considered the best online resource to use for official National Flood Insurance Program (NFIP) purposes when determining locations in relation to regulatory flood hazard information. If a different base map is used with the NFHL, the accuracy specification may not be met and the resulting map should be used for general reference only, and not official NFIP purposes. Users can download a simplified base map from the USGS service via: https://viewer.nationalmap.gov/services/ For the specifics of FEMA’s policy on the use of digital flood hazard data for NFIP purposes see: http://www.fema.gov/library/viewRecord.do?id=3235Letter of Map Amendment (LOMA) pointsLOMA point locations are approximate. The location of the LOMA is referenced in the legal description of the letter itself. Click the LOMA point for a link to the letter (use the arrows at the top of the popup window to bring up the LOMA info, if needed).This LOMA database may include LOMAs that are no longer effective. To be certain a particular LOMA is currently valid, please check relevant documentation at https://msc.fema.gov/ . Relevant documents can be found for a particular community by choosing to "Search All Products", and finding the community by State and County. Documents include LOMAs found in the "Effective Products" and "LOMC" folders, as well as Revalidations (those LOMAs which are still considered to be effective after a map is revised).Updates3/27/2017 - Updated all references to https to prevent issues with mixed content.5/11/2016 - Added link to NFHL FIRMette Print Service. Updated LOMA and CBRS popup notes.2/20/2014 - Created a General Reference map for use when the USGS base map service is down. Renamed this map to "Official".Further InformationSpecific questions about FEMA flood maps can be directed to FEMAMapSpecialist@riskmapcds.comFor more flood map data, tool, and viewing options, visit the FEMA NFHL page. Information about connecting to web map services (REST, WMS, WFS) can be found here.Several fact sheets are available to help you learn more about FEMA’s NFHL utility: National Flood Hazard Layer (NFHL) GIS Services Users GuideNational Flood Hazard Layer (NFHL): New Products and Services for FEMA's Flood Hazard Map DataMoving to Digital Flood Hazard Information Standards for Flood Risk Analysis and MappingNFHL GIS Data: Perform Spatial Analyses and Make Custom Maps and Reports

  3. Floodplains Outline

    • catalog.data.gov
    • opendata.dc.gov
    • +3more
    Updated Apr 16, 2025
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    Federal Emergency Management Agency (2025). Floodplains Outline [Dataset]. https://catalog.data.gov/dataset/floodplains-outline
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    Dataset updated
    Apr 16, 2025
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Description

    The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA.The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.For more information, visit https://msc.fema.gov/portal/home.

  4. g

    National Flood Hazard - Letter of Map Revision (LOMR) | gimi9.com

    • gimi9.com
    Updated Apr 13, 2023
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    (2023). National Flood Hazard - Letter of Map Revision (LOMR) | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_national-flood-hazard-letter-of-map-revision-lomr-a2b77/
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    Dataset updated
    Apr 13, 2023
    Description

    The S_LOMR feature class should contain at least one record for each Letter of Map Revision incorporated into the NFHL. Multipart polygons are not allowed. The spatial entities representing LOMRs are polygons. The spatial information contains the bounding polygon for each LOMR area, broken on panel boundaries.Technical Reference - http://www.fema.gov/media-library-data/1449862521789-e97ed4c7b7405faa7c3691603137ec40/FIRM_Database_Technical_Reference_Nov_2015.pdfFlood hazard and supporting data are developed using specifications for horizontal control consistent with 1:12,000–scale mapping. If you plan to display maps from the National Flood Hazard Layer with other map data for official purposes, ensure that the other information meets FEMA’s standards for map accuracy. The minimum horizontal positional accuracy for base map hydrographic and transportation features used with the NFHL is the NSSDA radial accuracy of 38 feet. USGS imagery and map services that meet this standard can be found by visiting the Knowledge Sharing Site (KSS) for Base Map Standards (420). Other base map standards can be found at https://riskmapportal.msc.fema.gov/kss/MapChanges/default.aspx. You will need a username and password to access this information.The NFHL data are from FEMA’s Flood Insurance Rate Map (FIRM) databases. New data are added continually. The NFHL also contains map changes to FIRM data made by Letters of Map Revision (LOMRs). The NFHL is stored in North American Datum of 1983, Geodetic Reference System 80 coordinate system, though many of the NFHL GIS web services support the Web Mercator Sphere projection commonly used in web mapping applications.

  5. a

    NAPSG Situational Awareness Web Map

    • cest-cusec.hub.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +2more
    Updated Aug 29, 2017
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    NAPSG Foundation (2017). NAPSG Situational Awareness Web Map [Dataset]. https://cest-cusec.hub.arcgis.com/maps/8f16acb5bddd4045a6d518e80bcaf9da
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    Dataset updated
    Aug 29, 2017
    Dataset authored and provided by
    NAPSG Foundation
    Area covered
    Description

    Purpose: This is a web map used for a situational awareness viewer. Click on links below for more information, this is just a summary of the layers in this map as of 09/14/2018.Live Data Live Feed - Storm Reports (NOAA) - This map contains continuously updated U.S. tornado reports, wind storm reports and hail storm reports. You can click on each to receive information about the specific location and read a short description about the issue. Live Feed - Observed Weather (NOAA METAR) - Current wind and weather conditions at all METAR stations.Live Feed: Open Shelters (FEMA / Red Cross National Shelter System) - his web service displays data from the FEMA National Shelter System database. The FEMA NSS database is synchronized every morning with the American Red Cross shelter database. After this daily refresh, FEMA GIS connects every 20 minutes to the FEMA NSS database looking for any shelter updates that occur throughout the day in the the FEMA NSS.Live Feed: Active Hurricanes - Hurricane tracks and positions provide information on where the storm has been, where is it going, where it is currently located and the category as defined by wind speed. This data is provided by NOAA National Hurricane Center (NHC).Live Feed Action Level Stream Gauges (USGS) - This map service shows those gauges from the Live Stream Gauge layer that are currently flooding. It only includes those gauges where flood stages have been defined by the contributing agencies. Action stage represents the river depth at which the agency begins preparing for a flood and taking mitigative action.Live Feed: USA Short-Term Weather Warnings - This layer presents continuously updated US weather warnings. You can click on each to receive information about the specific location and read a short description about the issue. Each layer is updated every minute with data provided by NOAA’s National Weather Service - http://www.nws.noaa.gov/regsci/gis/shapefiles/.Live Feed: Power Outages - Current power outage data reported by the EARSS system.Live Feed: Radar (NOAA) - Quality Controlled 1km x 1km CONUS Radar Base Reflectivity. This data is provided by Mutil-Radar-Multi-Sensor (MRMS) algorithm.Flood Prediction / Simulation (Created on 09/13 by Pacific Northwest National Laboratory RIFT Model) - Pacific Northwest National Laboratory RIFT Model: The simulations, based on NOAA weather forecasts, are used to improve understanding of the storm and its potential flood impacts. The simulations were created with PNNL's Rapid Inundation Flood Tool, a two-dimensional hydrodynamic computer model.Base Data - FEMA National Flood Hazard Layer - The National Flood Hazard Layer (NFHL) dataset represents the current effective flood data for the country, where maps have been modernized. It is a compilation of effective Flood Insurance Rate Map (FIRM) databases and Letters of Map Change (LOMCs). The NFHL is updated as studies go effective. For more information, visit FEMA's Map Service Center (MSC). Base Data - Storm Surge Scenarios (NOAA) - This mapping service displays near worst case storm surge flooding (inundation) scenarios for the Gulf and Atlantic coasts. This map service was derived from an experimental storm surge data product developed by the National Hurricane Center (NHC).

  6. n

    FEMA National Flood Hazard Layer Viewer

    • data.gis.ny.gov
    Updated Mar 29, 2023
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    ShareGIS NY (2023). FEMA National Flood Hazard Layer Viewer [Dataset]. https://data.gis.ny.gov/datasets/fema-national-flood-hazard-layer-viewer
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    Dataset updated
    Mar 29, 2023
    Dataset authored and provided by
    ShareGIS NY
    Description

    The National Flood Hazard Layer (NFHL) is a geospatial database that contains current effective flood hazard data. FEMA provides the flood hazard data to support the National Flood Insurance Program. You can use the information to better understand your level of flood risk and type of flooding.The NFHL is made from effective flood maps and Letters of Map Change (LOMC) delivered to communities. NFHL digital data covers over 90 percent of the U.S. population. New and revised data is being added continuously. If you need information for areas not covered by the NFHL data, there may be other FEMA products which provide coverage for those areas.In the NFHL Viewer, you can use the address search or map navigation to locate an area of interest and the NFHL Print Tool to download and print a full Flood Insurance Rate Map (FIRM) or FIRMette (a smaller, printable version of a FIRM) where modernized data exists. Technical GIS users can also utilize a series of dedicated GIS web services that allow the NFHL database to be incorporated into websites and GIS applications. For more information on available services, go to the NFHL GIS Services User Guide.You can also use the address search on the FEMA Flood Map Service Center (MSC) to view the NFHL data or download a FIRMette. Using the “Search All Products” on the MSC, you can download the NFHL data for a County or State in a GIS file format. This data can be used in most GIS applications to perform spatial analyses and for integration into custom maps and reports. To do so, you will need GIS or mapping software that can read data in shapefile format.FEMA also offers a download of a KMZ (keyhole markup file zipped) file, which overlays the data in Google Earth™. For more information on using the data in Google Earth™, please see Using the National Flood Hazard Layer Web Map Service (WMS) in Google Earth™.

  7. C

    UniGR - Formation transfrontalière: Physique (M.Sc.)

    • grandest-moissonnage.data4citizen.com
    • grandestprod-backoffice.data4citizen.com
    • +1more
    Updated Jul 11, 2025
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    sig-grande-region (2025). UniGR - Formation transfrontalière: Physique (M.Sc.) [Dataset]. https://grandest-moissonnage.data4citizen.com/dataset/4a64e95d-f868-4ba1-8b83-cc3b9ac3cf66
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    Dataset updated
    Jul 11, 2025
    Dataset provided by
    sig-grande-region
    Description

    Formation transfrontalière UniGR: Physique (M.Sc.) - Source: UniGR

  8. d

    National Flood Hazard - FIRM Panels

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Apr 13, 2023
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    Louisville/Jefferson County Information Consortium (2023). National Flood Hazard - FIRM Panels [Dataset]. https://catalog.data.gov/dataset/national-flood-hazard-firm-panels-17159
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    Dataset updated
    Apr 13, 2023
    Dataset provided by
    Louisville/Jefferson County Information Consortium
    Description

    The S_FIRM_Pan table contains information about the FIRM panel area. A spatial file with location information also corresponds with this data table. The spatial entities representing FIRM panels are polygons. The polygon for the FIRM panel corresponds to the panel neatlines. Panel boundaries are generally derived from USGS DOQQ boundaries. As a result, the panels are generally rectangular. In situations where a portion of a panel lies outside the jurisdiction being mapped, the user must refer to the S_Pol_Ar table to determine the portion of the panel area where the FIRM Database shows the effective flood hazard data for the mapped jurisdiction. This information is needed for the FIRM Panel Index and the following tables in the FIS report: Listing of NFIP Jurisdictions, Levees, Incorporated Letters of Map Change, and Coastal Barrier Resources System Information. The spatial entities representing FIRM panels are polygons. The polygon for the FIRM panel corresponds to the panel neatlines. Panel boundaries are generally derived from USGS DOQQ boundaries. As a result, the panels are generally rectangular. FIRM panels must not overlap or have gaps within a study. In situations where a portion of a panel lies outside the jurisdiction being mapped, the user must refer to the S_Pol_Ar table to determine the portion of the panel area where the FIRM Database shows the effective flood hazard data for the mapped jurisdiction. This information is needed for the FIRM Panel Index and the following tables in the FIS report: Listing of NFIP Jurisdictions, Levees, Incorporated Letters of Map Change, and Coastal Barrier Resources System Information.Flood hazard and supporting data are developed using specifications for horizontal control consistent with 1:12,000–scale mapping. If you plan to display maps from the National Flood Hazard Layer with other map data for official purposes, ensure that the other information meets FEMA’s standards for map accuracy. The minimum horizontal positional accuracy for base map hydrographic and transportation features used with the NFHL is the NSSDA radial accuracy of 38 feet. USGS imagery and map services that meet this standard can be found by visiting the Knowledge Sharing Site (KSS) for Base Map Standards (420). Other base map standards can be found at https://riskmapportal.msc.fema.gov/kss/MapChanges/default.aspx. You will need a username and password to access this information.The NFHL data are from FEMA’s Flood Insurance Rate Map (FIRM) databases. New data are added continually. The NFHL also contains map changes to FIRM data made by Letters of Map Revision (LOMRs). The NFHL is stored in North American Datum of 1983, Geodetic Reference System 80 coordinate system, though many of the NFHL GIS web services support the Web Mercator Sphere projection commonly used in web mapping applications.

  9. C

    UniGR - Formation transfrontalière: AMASE - Erasmus Mundus Master in...

    • grandest-moissonnage.data4citizen.com
    • datagrandest.fr
    Updated Jul 11, 2025
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    sig-grande-region (2025). UniGR - Formation transfrontalière: AMASE - Erasmus Mundus Master in Advanced Material Science and Engineering (M.Sc.) [Dataset]. https://grandest-moissonnage.data4citizen.com/en/dataset/7542c173-d6fb-4ffd-82d3-923a3bdf6552
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    Dataset updated
    Jul 11, 2025
    Dataset provided by
    sig-grande-region
    Description

    Formation transfrontalière UniGR: AMASE - Erasmus Mundus Master in Advanced Material Science and Engineering (M.Sc.) - Source: UniGR

  10. Datasets (raw) used for MSc Thesis

    • figshare.com
    application/x-rar
    Updated Apr 18, 2021
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    Yannis Paraskevopoulos (2021). Datasets (raw) used for MSc Thesis [Dataset]. http://doi.org/10.6084/m9.figshare.14237705.v1
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    application/x-rarAvailable download formats
    Dataset updated
    Apr 18, 2021
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Yannis Paraskevopoulos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Raw data used in MSc Thesis. Available for reproducing methodology

  11. p

    UniGR - cross-border study programme: Physics (M.Sc.)

    • data.public.lu
    • geocatalogue.geoportail.lu
    Updated Sep 27, 2023
    + more versions
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    SIG-GR @ Ministère du Logement et de l'Aménagement du territoire - Département de l’aménagement du territoire (2023). UniGR - cross-border study programme: Physics (M.Sc.) [Dataset]. https://data.public.lu/en/datasets/unigr-cross-border-study-programme-physics-m-sc-1/
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    wms, zip(1842), application/geo+json(2240)Available download formats
    Dataset updated
    Sep 27, 2023
    Dataset authored and provided by
    SIG-GR @ Ministère du Logement et de l'Aménagement du territoire - Département de l’aménagement du territoire
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    UniGR cross-border study programme: Physics (M.Sc.) Source: UniGR

  12. r

    GIS database of archaeological remains on Samoa

    • researchdata.se
    • demo.researchdata.se
    Updated Dec 19, 2023
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    Olof Håkansson (2023). GIS database of archaeological remains on Samoa [Dataset]. http://doi.org/10.5878/003012
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    (10994657)Available download formats
    Dataset updated
    Dec 19, 2023
    Dataset provided by
    Uppsala University
    Authors
    Olof Håkansson
    Area covered
    Samoa
    Description

    Data set that contains information on archaeological remains of the pre historic settlement of the Letolo valley on Savaii on Samoa. It is built in ArcMap from ESRI and is based on previously unpublished surveys made by the Peace Corps Volonteer Gregory Jackmond in 1976-78, and in a lesser degree on excavations made by Helene Martinsson Wallin and Paul Wallin. The settlement was in use from at least 1000 AD to about 1700- 1800. Since abandonment it has been covered by thick jungle. However by the time of the survey by Jackmond (1976-78) it was grazed by cattle and the remains was visible. The survey is at file at Auckland War Memorial Museum and has hitherto been unpublished. A copy of the survey has been accessed by Olof Håkansson through Martinsson Wallin and Wallin and as part of a Masters Thesis in Archeology at Uppsala University it has been digitised.

    Olof Håkansson has built the data base structure in the software from ESRI, and digitised the data in 2015 to 2017. One of the aims of the Masters Thesis was to discuss hierarchies. To do this, subsets of the data have been displayed in various ways on maps. Another aim was to discuss archaeological methodology when working with spatial data, but the data in itself can be used without regard to the questions asked in the Masters Thesis. All data that was unclear has been removed in an effort to avoid errors being introduced. Even so, if there is mistakes in the data set it is to be blamed on the researcher, Olof Håkansson. A more comprehensive account of the aim, questions, purpose, method, as well the results of the research, is to be found in the Masters Thesis itself. Direkt link http://uu.diva-portal.org/smash/record.jsf?pid=diva2%3A1149265&dswid=9472

    Purpose:

    The purpose is to examine hierarchies in prehistoric Samoa. The purpose is further to make the produced data sets available for study.

    Prehistoric remains of the settlement of Letolo on the Island of Savaii in Samoa in Polynesia

  13. a

    Flood Haz Areas 2016

    • hub.arcgis.com
    Updated Jun 1, 2016
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    County of Monterey (2016). Flood Haz Areas 2016 [Dataset]. https://hub.arcgis.com/datasets/2949161b8cb94780b86ea052f7ff9d42
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    Dataset updated
    Jun 1, 2016
    Dataset authored and provided by
    County of Monterey
    Area covered
    Description

    The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.This dataset published by FEMA on 5/18/2016. Available for download at https://msc.fema.gov.This GIS data is provided "AS IS." The County of Monterey (COUNTY) makes no warranties, express or implied, including without limitation, any implied warranties of merchantability and/or fitness for a particular purpose, regarding the accuracy, completeness, value, quality, validity, merchantability, suitability, and/or condition, of the GIS data. The COUNTY also specifically does not guarantee that the information is free from harmful effects or viruses and that it will not harm the users’ computer. By using this GIS, users accept sole responsibility for ensuring the protection of their own computer equipment and specifically hold COUNTY harmless from any damage or liability that might ensue do the use of the data. Users of COUNTY's GIS data are hereby notified that current public primary information sources should be consulted for verification of the data and information contained herein. Since the GIS data is dynamic, it will by its nature be inconsistent with the official COUNTY assessment roll file, surveys, maps and/or other documents produced by the County Office of the Assessor, the County Surveyor, and/or other relevant County Offices. Any use of COUNTY's GIS data is done exclusively at the risk of the party making such use.

  14. p

    DFHI-ISFATES - cross-border study programme: Computer Science (M.Sc.)

    • data.public.lu
    Updated Jan 15, 2025
    + more versions
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    SIG-GR @ Ministère du Logement et de l'Aménagement du territoire - Département de l’aménagement du territoire (2025). DFHI-ISFATES - cross-border study programme: Computer Science (M.Sc.) [Dataset]. https://data.public.lu/en/datasets/dfhi-isfates-cross-border-study-programme-computer-science-m-sc-1/
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    application/geopackage+sqlite3(90112), zip(1673), application/geo+json(1608)Available download formats
    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    SIG-GR @ Ministère du Logement et de l'Aménagement du territoire - Département de l’aménagement du territoire
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    UniGR cross-border study DFHI-ISFATES: Computer Science (M.Sc.) Source: DFHI-ISFATES Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=2273&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/0214a3be-688b-4bac-b174-724c62857ff8 This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Cross_border_programmes_science_mathematics_computing_2023_WMS/guest with layer name(s): -DFHI_ISFATES_Computer_Science_MSc

  15. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Masters%20Of%20Science%20In%20Gis%20Technology
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    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Masters Of Science In Gis Technology from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Masters Of Science In Gis Technology relative to other fields. This data is essential for students assessing the return on investment of their education in Masters Of Science In Gis Technology, providing a clear picture of financial prospects post-graduation.

  16. a

    FEMA's National Flood Hazard Layer Viewer

    • opendata-volusiacountyfl.hub.arcgis.com
    Updated May 21, 2025
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    County of Volusia (2025). FEMA's National Flood Hazard Layer Viewer [Dataset]. https://opendata-volusiacountyfl.hub.arcgis.com/datasets/femas-national-flood-hazard-layer-viewer
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    Dataset updated
    May 21, 2025
    Dataset authored and provided by
    County of Volusia
    Description

    In the NFHL Viewer, you can use the address search or map navigation to locate an area of interest and the NFHL Print Tool to download and print a full Flood Insurance Rate Map (FIRM) or FIRMette (a smaller, printable version of a FIRM) where NFHL data exists. Technical GIS users can also utilize a series of dedicated GIS web services that allow the NFHL database to be incorporated into websites and GIS applications. For more information on available services, go to the NFHL GIS Services User Guide.You can also use the address search on the FEMA Flood Map Service Center (MSC) to view the NFHL data or download a FIRMette. Using the “Search All Products” on the MSC, you can download the NFHL data for a County or State in a GIS file format. This data can be used in most GIS applications to perform spatial analyses and for integration into custom maps and reports. To do so, you will need GIS or mapping software that can read data in shapefile format.FEMA also offers a download of a KMZ (keyhole markup file zipped) file, which overlays the data in Google Earth™. For more information on using the data in Google Earth™, please see Using the National Flood Hazard Layer Web Map Service (WMS) in Google Earth™.

  17. v

    FEMA Flood Zones - 2015

    • gis.data.vbgov.com
    Updated Apr 18, 2016
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    VBCGIS_OrgAcct1 (2016). FEMA Flood Zones - 2015 [Dataset]. https://gis.data.vbgov.com/datasets/7f061dd6bfd74380a9a284990b526ca2
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    Dataset updated
    Apr 18, 2016
    Dataset authored and provided by
    VBCGIS_OrgAcct1
    Area covered
    Description

    Flood zones are geographic areas that FEMA has defined according to varying levels of flood risk. Each Zone reflects the severity or type of flooding in the area. These zones are depicted on a community FEMA Flood Insurance Rate Map (FIRM) or Flood Hazard Boundary Map. For more information go to: U.S. Department of Homeland Security, FEMA Map Service Center at http://www.msc.fema.gov Version 2.0

  18. e

    GIS database of archaeological remains on Samoa

    • data.europa.eu
    unknown
    Updated Mar 11, 2018
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    Uppsala universitet (2018). GIS database of archaeological remains on Samoa [Dataset]. https://data.europa.eu/data/datasets/https-doi-org-10-5878-003012?locale=en
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    unknownAvailable download formats
    Dataset updated
    Mar 11, 2018
    Dataset authored and provided by
    Uppsala universitet
    Description

    Data set that contains information on archaeological remains of the pre historic settlement of the Letolo valley on Savaii on Samoa. It is built in ArcMap from ESRI and is based on previously unpublished surveys made by the Peace Corps Volonteer Gregory Jackmond in 1976-78, and in a lesser degree on excavations made by Helene Martinsson Wallin and Paul Wallin. The settlement was in use from at least 1000 AD to about 1700- 1800. Since abandonment it has been covered by thick jungle. However by the time of the survey by Jackmond (1976-78) it was grazed by cattle and the remains was visible. The survey is at file at Auckland War Memorial Museum and has hitherto been unpublished. A copy of the survey has been accessed by Olof Håkansson through Martinsson Wallin and Wallin and as part of a Masters Thesis in Archeology at Uppsala University it has been digitised.

    Olof Håkansson has built the data base structure in the software from ESRI, and digitised the data in 2015 to 2017. One of the aims of the Masters Thesis was to discuss hierarchies. To do this, subsets of the data have been displayed in various ways on maps. Another aim was to discuss archaeological methodology when working with spatial data, but the data in itself can be used without regard to the questions asked in the Masters Thesis. All data that was unclear has been removed in an effort to avoid errors being introduced. Even so, if there is mistakes in the data set it is to be blamed on the researcher, Olof Håkansson. A more comprehensive account of the aim, questions, purpose, method, as well the results of the research, is to be found in the Masters Thesis itself. Direkt link http://uu.diva-portal.org/smash/record.jsf?pid=diva2%3A1149265&dswid=9472

    Purpose:

    The purpose is to examine hierarchies in prehistoric Samoa. The purpose is further to make the produced data sets available for study.

    Prehistoric remains of the settlement of Letolo on the Island of Savaii in Samoa in Polynesia

  19. c

    Nodes

    • data.cityofrochester.gov
    Updated Apr 27, 2018
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    City of Rochester, NY (2018). Nodes [Dataset]. https://data.cityofrochester.gov/datasets/nodes
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    Dataset updated
    Apr 27, 2018
    Dataset authored and provided by
    City of Rochester, NY
    Area covered
    Description

    FEMA provides access to the National Flood Hazards Layer (NFHL) through web mapping services. The maps depict effective flood hazard information and supporting data. The primary flood hazard classification is indicated in the Flood Hazard Zones layer.The NFHL layers include:Flood hazard zones and labelsRiver Miles MarkersCross-sections and coastal transects and their labelsLetter of Map Revision (LOMR) boundaries and case numbersFlood Insurance Rate Map (FIRM) boundaries, labels and effective datesCoastal Barrier Resources System (CBRS) and Otherwise Protected Area (OPA) unitsCommunity boundaries and namesLeveesHydraulic and flood control structuresProfile and coastal transect baselinesLimit of Moderate Wave Action(LiMWA)Not all effective Flood Insurance Rate Maps (FIRM) have GIS data available. To view a list of available county and single-jurisdiction flood study data in GIS format and check the status of the NFHL GIS services, please visit the NFHL Status Page.Preliminary & Pending National Flood Hazard LayersThe Preliminary and Pending NFHL dataset represents the current pre-effective flood data for the country. These layers are updated as new preliminary and pending data becomes available, and data is removed from these layers as it becomes effective.For more information, please visit FEMA's website.To download map panels or GIS Data, go to: NFHL on FEMA GeoPlatform.Preliminary & Pending DataPreliminary data are for review and guidance purposes only. By viewing preliminary data and maps, the user acknowledges that the information provided is preliminary and subject to change. Preliminary data are not final and are presented in this national layer as the best information available at this time. Additionally, preliminary data cannot be used to rate flood insurance policies or enforce the Federal mandatory purchase requirement. FEMA will remove preliminary data once pending data are available.Pending data are for early awareness of upcoming changes to regulatory flood map information. Until the data becomes effective, when it will appear in FEMA's National Flood Hazard Layer (NFHL), the data should not be used to rate flood insurance policies or enforce the Federal mandatory purchase requirement. FEMA will remove pending data once effective data are available.To better understand Preliminary data please see the View Your Community's Preliminary Flood Hazard Data webpage.FEMA GeoPlatformFEMA's GIS flood map services are available through FEMAs GeoPlatform, an ArcGIS Online portal containing a variety of FEMA-related data.To view the NFHL on the FEMA GeoPlatform go to NFHL on FEMA GeoPlatform.To view the Preliminary and Pending national layers on the FEMA Geoplatform go to FEMA's Preliminary & Pending National Flood Hazard Layer.Technical InformationFlood hazard and supporting data are developed using specifications for horizontal control consistent with 1:12,000–scale mapping. If you plan to display maps from the NFHL with other map data for official purposes, ensure that the other information meets FEMA’s standards for map accuracy.The minimum horizontal positional accuracy for base map hydrographic and transportation features used with the NFHL is the NSSDA radial accuracy of 38 feet. United States Geological Survey (USGS) imagery and map services that meet this standard can be found by visiting the Knowledge Sharing Site (KSS) for Base Map Standards (420). Other base map standards can be found at https://riskmapportal.msc.fema.gov/kss/MapChanges/default.aspx. You will need a username and password to access this information.The NFHL data are from FEMA’s FIRM databases. New data are added continually. The NFHL also contains map changes to FIRM data made by LOMRs.The NFHL is stored in North American Datum of 1983, Geodetic Reference System 80 coordinate system, though many of the NFHL GIS web services support the Web Mercator Sphere projection commonly used in web mapping applications.Organization & DisplayThe NFHL is organized into many data layers. The layers display information at map scales appropriate for the data. A layer indicating the availability of NFHL data is displayed at map scales smaller than 1:250,000, regional overviews at map scales between 1:250,000 and 1:50,000, and detailed flood hazard maps at map scales of 1:50,000 and larger. The "Scalehint" item in the Capabilities file for the Web Map Service encodes the scale range for a layer.In addition, there are non-NFHL datasets provided in the GIS web services, such as information about the availability of flood data and maps, the national map panel scheme, and point locations for LOMA and LOMR-Fs. The LOMA are positioned less accurately than are the NFHL data.Layers in the public NFHL GIS services:Use the numbers shown below when referencing layers by number.0. NFHL Availability1. LOMRs2. LOMAs3. FIRM Panels4. Base Index5. PLSS6. Toplogical Low Confidence Areas7. River Mile Markers8. Datum Conversion Points9. Coastal Gages10. Gages11. Nodes12. High Water Marks13. Station Start Points14. Cross-Sections15. Coastal Transects16. Base Flood Elevations17. Profile Baselines18. Transect Baselines19. Limit of Moderate Wave Action20. Water Lines21. Coastal Barrier Resources System Area22. Political Jurisdictions23. Levees24. General Structures25. Primary Frontal Dunes26. Hydrologic Reaches27. Flood Hazard Boundaries28. Flood Hazard Zones29. Submittal Information30. Alluvial Fans31. Subbasins32. Water Areas

  20. o

    NOAFAULTS KMZ layer Version 4.0

    • explore.openaire.eu
    • zenodo.org
    Updated Mar 3, 2022
    + more versions
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    Athanassios Ganas (2022). NOAFAULTS KMZ layer Version 4.0 [Dataset]. http://doi.org/10.5281/zenodo.6326260
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    Dataset updated
    Mar 3, 2022
    Authors
    Athanassios Ganas
    Description

    The NOAFAULTs database of active faults of Greece was first published in 2013 (versions 1.0 & 1.1; http://dx.doi.org/10.12681/bgsg.11079). The version 2.1 was published in 2018 http://doi.org/10.5281/zenodo.3483136). Version 3.0 was published in 2020 http://doi.org/10.5281/zenodo.4304613 NOAFAULTs was created towards compiling a digital database of fault geometry and additional attributes (kinematics, slip rate, associated seismicity etc.) primarily to support seismicity monitoring at the National Observatory of Athens (NOA). It has been constructed from published fault maps in peer-reviewed journals since 1972 while the number of the scientific papers that have contributed with fault data in version 4.0 is 127. The standard commercial software ARCGIS has been used to design and populate the database. The fault layer was produced by on-screen digitization of fault traces at the original map-scale and is available through our web portal application https://arcg.is/04Haer supported by ESRI. In this version, a number of 2751 active faults are included. 93% of the active faults are normal faults, 4% are strike-slip faults and only 3% represent the reverse faults. Also, reliable data on slip rates are available for 106 faults. Data on instrumental and historical seismicity are linked to 171 and 130 active faults, respectively. In addition, a) surface-rupturing geological data and b) data on the proximity of epicentres of strong seismic events to the traces of active faults allows the identification of 101 rupturing faults (seismic faults) that included in this version of the database. The NOAFAULTs database shows that nearly 52% of its active faults imply high seismic risk level in the broader area of Greece. These active faults can generate surface faulting or strong ground motions that can cause serious damage to buildings and infrastructures and therefore represent a significant hazard, particularly in the densely populated and industrialized areas of Greece. {"references": ["Ganas A., Oikonomou I.A. and Tsimi , 2013. NOAfaults: a digital database for active faults in Greece. Bulletin of the Geological Society of Greece, vol. 47 (2), 518-530, \u0394\u03b5\u03bb\u03c4\u03af\u03bf \u0395.\u0393.\u0395., \u03c4\u03cc\u03bc\u03bf\u03c2 XLVII - 13o \u0394\u03b9\u03b5\u03b8\u03bd\u03ad\u03c2 \u03a3\u03c5\u03bd\u03ad\u03b4\u03c1\u03b9\u03bf \u03c4\u03b7\u03c2 \u0395\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ae\u03c2 \u0393\u03b5\u03c9\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae\u03c2 \u0395\u03c4\u03b1\u03b9\u03c1\u03af\u03b1\u03c2, \u03a7\u03b1\u03bd\u03b9\u03ac, 5-8 \u03a3\u03b5\u03c0\u03c4\u03b5\u03bc\u03b2\u03c1\u03af\u03bf\u03c5 2013 p.518-530, http://dx.doi.org/10.12681/bgsg.11079", "Ganas, A., Tsironi, V., Kollia, E., Delagas, M., Tsimi, Ch., Oikonomou, Ath. 2018. Recent upgrades of the NOA database of active faults in Greece (NOAFAULTs). 19th General Assembly of WEGENER, September 2018, Grenoble, sciencesconf.org:wegener2018:219400"]} The following contributors are gratefully acknowledged: Ms Varvara Tsironi MSc, Ms Eirini Efstathiou, Ms Elisavet Kollia MSc, Ms Christina Tsimi, MSc Dr. Sotiris Valkaniotis, Mr George Evangelou, Mr Michael Delagas, MSc, Ms Athanassia Oikonomou, Ms Fotini Kounavi MSc, Ms Vasiliki Kanavou, Ms Emmanuella Konstantakopoulou and Mr Vassilios Georgakopoulos.

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Simon van Lierde; Simon van Lierde (2025). GIS Data and Analysis for Cooling Demand and Environmental Impact in The Hague [Dataset]. http://doi.org/10.5281/zenodo.8344581
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GIS Data and Analysis for Cooling Demand and Environmental Impact in The Hague

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Dataset updated
Apr 24, 2025
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Simon van Lierde; Simon van Lierde
Area covered
The Hague
Description

This dataset contains raw GIS data sourced from the BAG (Basisregistratie Adressen en Gebouwen; Registry of Addresses and Buildings). It provides comprehensive information on buildings, including advanced height data and administrative details. It also contains geographic divisions within The Hague. Additionally, the dataset incorporates energy label data, offering insights into the energy efficiency and performance of these buildings. This combined dataset serves as the backbone of a Master's thesis in Industrial Ecology, analysing residential and office cooling and its environmental impacts in The Hague, Netherlands. The codebase of this analysis can be found in this Github repository: https://github.com/simonvanlierde/msc-thesis-ie

The dataset includes a background research spreadsheet containing supporting calculations. It also presents geopackages with results from the cooling demand model (CDM) for various scenarios: Status quo (SQ), 2030, and 2050 scenarios (Low, Medium, and High)

Background research data

The background_research_data.xlsx spreadsheet contains comprehensive background research calculations supporting the shaping of input parameters used in the model. It contains several sheets:

  • Cooling Technologies: Details the various cooling technologies examined in the study, summarizing their characteristics and the market penetration mixes used in the analysis.
  • LCA Results of Ventilation Systems: Provides an overview of the ecoinvent processes serving as proxies for the life-cycle impacts of cooling equipment, along with calculations of the weight of cooling systems and contribution tables from the LCA-based assessment.
  • Material Scarcity: A detailed examination of the critical raw material content in the material footprint of ecoinvent processes, representing cooling equipment.
  • Heat Plans per Neighbourhood: Forecasts of future heating solutions for each neighbourhood in The Hague.
  • Building Stock: Analysis of the projected growth trends in residential and office building stocks in The Hague. AC Market: Market analysis covering air conditioner sales in the Netherlands from 2002 to 2022.
  • Climate Change: Computations of climate-related parameters based on KNMI climate scenarios.
  • Electricity Mix Analysis: Analysis of future projections for the Dutch electricity grid and calculations of life-cycle carbon intensities of the grid.

Input data

Geographic divisions

  • The outline of The Hague municipality through the Municipal boundaries (Gemeenten) layer, sourced from the Administrative boundaries (Bestuurlijke Gemeenten) dataset on the PDOK WFS service.
  • District (Wijken) and Neighbourhood (Buurten) layers were downloaded from the PDOK WFS service (from the CBS Wijken en Buurten 2022 data package) and clipped to the outline of The Hague.
  • The 4-digit postcodes layer was downloaded from PDOK WFS service (CBS Postcode4 statistieken 2020) and clipped to The Hague's outline. The postcodes within The Hague were subsequently stored in a csv file.
  • The census block layer was downloaded from the PDOK WFS service (from the CBS Vierkantstatistieken 100m 2021 data package) and also clipped to the outline of The Hague.
  • These layers have been combined in the GeographicDivisions_TheHague GeoPackage.

BAG data

  • BAG data was acquired through the download of a BAG GeoPackage from the BAG ATOM download page.
  • In the resulting GeoPackage, the Residences (Verblijfsobject) and Building (Pand) layers were clipped to match The Hague's outline.
  • The resulting residence data can be found in the BAG_buildings_TheHague GeoPackage.

3D BAG

  • Due to limitations imposed by the PDOK WFS service, which restricts the number of downloadable buildings to 10,000, it was necessary to acquire 145 individual GeoPackages for tiles covering The Hague from the 3D BAG website.
  • These GeoPackages were merged using the ogr2ogr append function from the GDAL library in bash.
  • Roof elevation data was extracted from the LoD 1.2 2D layer from the resulting GeoPackage.
  • Ground elevation data was obtained from the Pand layer.
  • Both of these layers were clipped to match The Hague's outline.
  • Roof and ground elevation data from the LoD 1.2 2D and Pand layers were joined to the Pand layer in the BAG dataset using the BAG ID of each building.
  • The resulting data can be found in the BAG_buildings_TheHague GeoPackage.

Energy labels

  • Energy labels were downloaded from the Energy label registry (EP-online) and stored in energy_labels_TheNetherlands.csv.

UHI effect data

  • A bitmap with the UHI effect intensity in The Hague was retrieved from the from the Dutch Natural Capital Atlas (Atlas Natuurlijk Kapitaal) and stored in UHI_effect_TheHague.tiff.

Output data

  • The residence-level data joined to the building layer is contained in the BAG_buildings_with_residence_data_full GeoPackage.
  • The results for each building, according to different scenarios, are compiled in the buildings_with_CDM_results_[scenario]_full GeoPackages. The scenarios are abbreviated as follows:
    • SQ: Status Quo, covering the 2018-2022 reference period.
    • 2030: An average scenario projected for the year 2030.
    • 2050_L: A low-impact, best-case scenario for 2050.
    • 2050_M: A medium-impact, moderate scenario for 2050.
    • 2050_H: A high-impact, worst-case scenario for 2050.

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