This dataset provides the Country (Pays) level administrative boundaries for Monaco in GeoJSON and Shape file formats. Rendered in the industry-standard coordinate reference system, EPSG:4326 (WGS84), this dataset ensures precision and compatibility.

Summary- These data products present vector files for different representations of land area from the moirai land data system. Vector files are generated at 3 main spatial levels, namely country, region, basin. In addition to this, files are generated for different intersections for the 3 main categories, intersections for country and basin boundaries (country_basin), region and basin boundaries (region_basin) and region and country boundaries (region_country). Since the land data system does not generate land area information for all cells within the above mentioned boundaries (for water bodies for example), the vectors are presented for 3 main classes for each spatial category, land cells, cells with no land and combined. With all of the above mentioned combinations, the data products contain 18 different vector files.

Methodology- In generating these vector files, we used the land outputs from moirai as inputs along with separate inputs for the boundaries for the main spatial levels (country, basin and region). Combining the spatial boundaries with land inputs we generated 3 raster outputs (land, no land and combined) for each of the main spatial levels along with all the intersections. A unique key is assigned for each unique spatial boundary. We then converted these rasters to vectors through a process of polygonization where polygons were dissolved using the key and finally added all metadata (basin names, region names, country names) to each of the vector files. We also check and correct geometry errors in the polygons themselves.

CONTENTS:

gcam_boundaries_moirai_3p1_0p5arcmin_wgs84 folder contains the following,

input_files contain the following,

moirai_valid_land_area.bsq: raster file containing actual land area by grid cell globally.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins

Global235_CLM_5arcmin.bil: raster file containing basin boundaries for all cells output by moirai

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins

GCAM_32_w_Taiwan.shp – vector file containing boundaries for GCAM regions.

GCAM_region_names.csv- Mapping file with details on GCAM region names (Used to fill in metadata)

iso_GCAM_regID.csv- Mapping file containing details on individual country names by iso code. (Used to fill in metadata)

basin_to_country_mapping.csv – Mapping file containing details on basin names by country and region. (Used to fill in metadata)

main_outputs contain the following,

Contains files for each spatial boundary (country, region, country_basin etc), for each land category (land cells, no land and combined)

_boundaries_moirai_3p1_0p5arcmin.shp

column names in outputs:

key: Unique identifier for feature

reg_id: Unique identifier for region (region number)

ctry_id: Unique identifier for country (country number)

basin_id: Unique identifier for basin (basin number)

reg_nm: Region name

ctry_nm: Country name

basin_nm: Basin name

See README in the zipped directory for a full reference.

Data to illustrate our geographic RD methodological framework. Illustration is a a re-examination of the effects of political advertisements on voter turnout during a presidential campaign, exploiting the exogenous variation in the volume of presidential ads that is created by media market boundaries. We rely on two data sources. Our main source is the New Jersey voter file. This dataset has measures of party registration, gender and age directly from the voter file, and imputed values of education, income, poverty status, and employment status. The voter file also contains the address of each voter, which allows us to find each voter's geographic location and avoid the use of naive distances. Our second data source is property sales records. We acquired records for all houses sold in the appropriate zip codes in New Jersey from January 2006 to November 2008. In this time period, nearly 3,000 homes were sold in this area -- although we only used the 1,800 house sales inside one specific school district, see below. The housing sales data allow us to conduct a fine-grained analysis of the sales price differential along the boundary of interest.

Watershed boundaries for eight sub-watersheds within the Baltimore Ecosystem Study LTER were delineated at 1-meter and 30-meter spatial resolutions. Watershed boundaries were used to calculate total area and extract and summarize existing land cover data (1m 2016 Chesapeake Conservancy Land Cover Data Project; 30m 2011 USGS National Land Cover Database). Two spatial resolutions are included to accommodate the needs of studies with different input requirements. In addition, providing data at both spatial scales highlights the importance of spatial resolution on study results.

This dataset provides the Country level administrative boundaries for Andorra in GeoJSON and Shape file formats. Rendered in the industry-standard coordinate reference system, EPSG:4326 (WGS84), this dataset ensures precision and compatibility.

Please note this dataset is the most recent version of the Administrative Boundaries (AB). For previous versions of the AB please go to this url: https://data.gov.au/dataset/ds-dga-b4ad5702-ea2b-4f04-833c-d0229bfd689e/details?q=previous

Geoscape Administrative Boundaries is Australia’s most comprehensive national collection of boundaries, including government, statistical and electoral boundaries. It is built and maintained by Geoscape Australia using authoritative government data. Further information about contributors to Administrative Boundaries is available here.

This dataset comprises seven Geoscape products:

• Localities
• Local Government Areas (LGAs)
• Wards
• Australian Bureau of Statistics (ABS) Boundaries
• Electoral Boundaries
• State Boundaries and
• Town Points

Updated versions of Administrative Boundaries are published on a quarterly basis.

Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.

Notable changes in the May 2025 release

• Victorian Wards have seen almost half of the dataset change now reflecting the boundaries from the 2024 subdivision review. https://www.vec.vic.gov.au/electoral-boundaries/council-reviews/ subdivision-reviews.

  • There have been spatial changes (area) greater than 1 km2 to 66 wards in Victoria.

• One new locality ‘Kenwick Island’ has been added to the local Government area ‘Mackay Regional’ in Queensland.

  • There have been spatial changes(area) greater than 1 km2 to the local government areas 'Burke Shire' and 'Mount Isa City' in Queensland.

• There have been spatial changes(area) greater than 1 km2 to the localities ‘Nicholson’, ‘Lawn Hill’ and ‘Coral Sea’ in Queensland and ‘Calguna’, ‘Israelite Bay’ and ‘Balladonia’ in Western Australia.

• An update to the NT Commonwealth Electoral Boundaries has been applied to reflect the redistribution of the boundaries gazetted on 4 March 2025.

• Geoscape has become aware that the DATE_CREATED and DATE_RETIRED attributes in the commonwealth_electoral_polygon MapInfo TAB tables were incorrectly ordered and did not match the product data model. These attributes have been re-ordered to match the data model for the May 2025 release.

IMPORTANT NOTE: correction of issues with the 22 November 2022 release

• On 28 November 2022, the Administrative Boundaries dataset originally released on 22 November 2022 was amended and re-uploaded after Geoscape identified some issues with the original data for 'Electoral Boundaries'.
• As a result of the error, some shapefiles were published in 3D rather than 2D, which may affect some users when importing data into GIS applications.
• The error affected the Electoral Boundaries dataset, specifically the Commonwealth boundary data for Victoria and Western Australia, including 'All States'.
• Only the ESRI Shapefile formats were affected (both GDA94 and GDA2020). The MapInfo TAB format was not affected.
• Because the datasets are zipped into a single file, once the error was fixed by Geoscape all of Administrative Boundaries shapefiles had to be re-uploaded, rather than only the affected files.
• If you downloaded either of the two Administrative Boundary ESRI Shapefiles between 22 November and 28 November 2022 and plan to use the Electoral Boundary component, you are advised to download the revised version dated 28 November 2022. Apologies for any inconvenience.

Further information on Administrative Boundaries, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on Administrative Boundaries, including software solutions, consultancy and support.

Note: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.

The Australian Government has negotiated the release of Administrative Boundaries to the whole economy under an open CCBY 4.0 licence.

Users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).

Users must also note the following attribution requirements:

Preferred attribution for the Licensed Material:

Administrative Boundaries © Geoscape Australia licensed by the Commonwealth of Australia under Creative Commons Attribution 4.0 International license (CC BY 4.0).

Preferred attribution for Adapted Material:

Incorporates or developed using Administrative Boundaries © Geoscape Australia licensed by the Commonwealth of Australia under Creative Commons Attribution 4.0 International licence (CC BY 4.0).

What to Expect When You Download Administrative Boundaries

Administrative Boundaries is large dataset (around 1.5GB unpacked), made up of seven themes each containing multiple layers.

Users are advised to read the technical documentation including the product change notices and the individual product descriptions before downloading and using the product.

Please note this dataset is the most recent version of the Administrative Boundaries (AB). For previous versions of the AB please go to this url: https://data.gov.au/dataset/ds-dga-b4ad5702-ea2b-4f04-833c-d0229bfd689e/details?q=previous

License Information

Geolocet's Administrative Boundaries Spatial Data serves as the gateway to visualizing geographic distributions and patterns with precision. The comprehensive dataset covers all European countries, encompassing the boundaries of each country, as well as its political and statistical divisions. Tailoring data purchases to exact needs is possible, allowing for the selection of individual levels of geography or bundling all levels for a country with a discount. The seamless integration of administrative boundaries onto digital maps transforms raw data into actionable insights.

🌐 Coverage Across European Countries

Geolocet's Administrative Boundaries Data offers coverage across all European countries, ensuring access to the most up-to-date and accurate geographic information. From national borders to the finest-grained administrative units, this data enables informed choices based on verified and official sources.

🔍 Geographic Context for Strategic Decisions

Understanding the geographical context is crucial for strategic decision-making. Geolocet's Administrative Boundaries Spatial Data empowers exploration of geo patterns, planning expansions, analysis of regional demographics, and optimization of operations with precision. Whether it is for establishing new business locations, efficient resource allocation, or policy impact analysis, this data provides the essential geographic context for success.

🌍 Integration with Geolocet’s Demographic Data

The integration of Geolocet's Administrative Boundaries Spatial Data with Geolocet's Demographic Data creates a synergy that enriches insights. The combination of administrative boundaries and demographic information offers a comprehensive understanding of regions and their unique characteristics. This integration enables tailoring of strategies, marketing campaigns, and resource allocation to specific areas with confidence.

🌍 Integration with Geolocet’s POI Data

Combining Geolocet's Administrative Boundaries Spatial Data with our POI (Points of Interest) Data unveils not only the administrative divisions but also insights into the local characteristics of these areas. Overlaying POI data on administrative boundaries reveals details about the number and types of businesses, services, and amenities within specific regions. Whether conducting market research, identifying prime locations for retail outlets, or analyzing the accessibility of essential services, this combined data empowers a holistic view of target areas.

🔍 Customized Data Solutions with DaaS

Geolocet's Data as a Service (DaaS) model offers flexibility tailored to specific needs. The transparent pricing model ensures cost-efficiency, allowing payment solely for the required data. Whether nationwide administrative boundary data or specific regional details are needed, Geolocet provides a solution to match individual objectives. Contact us today to explore how Geolocet's Administrative Boundaries Spatial Data can elevate decision-making processes and provide the essential geographic data for success.

Summary- These data products present vector files for different representations of land area from the moirai land data system. Vector files are generated at 3 main spatial levels, namely country, region, basin. In addition to this, files are generated for different intersections for the 3 main categories, intersections for country and basin boundaries (country_basin), region and basin boundaries (region_basin) and region and country boundaries (region_country). Since the land data system does not generate land area information for all cells within the above mentioned boundaries (for water bodies for example), the vectors are presented for 3 main classes for each spatial category, land cells, cells with no land and combined. With all of the above mentioned combinations, the data products contain 18 different vector files.

Methodology- In generating these vector files, we used the land outputs from moirai as inputs along with separate inputs for the boundaries for the main spatial levels (country, basin and region). Combining the spatial boundaries with land inputs we generated 3 raster outputs (land, no land and combined) for each of the main spatial levels along with all the intersections. A unique key is assigned for each unique spatial boundary. We then converted these rasters to vectors through a process of polygonization where polygons were dissolved using the key and finally added all metadata (basin names, region names, country names) to each of the vector files. We check and correct geometry errors in the polygons themselves. We also added various validation tests to the code to account for completeness and accuracy.

CONTENTS:

gcam_boundaries_moirai_3p1_0p5arcmin_wgs84 folder contains the following,

spatial_input_files contain the following,

• valid_land_area.bil: raster file containing actual land area by grid cell globally.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins (Generated by the moirai LDS)

• country_out.bil: raster file containing valid land cells matched to country codes.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins (Generated by the moirai LDS)

• country_out_noland.bil: raster file containing non-land cells matched to country codes.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins (Generated by the moirai LDS)

• glu_raster.bil: raster file containing valid land cells matched to GLU codes.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins (Generated by the moirai LDS)

• glu_raster_noland.bil: raster file containing non-land cells matched to GLU codes.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins (Generated by the moirai LDS)

• region_gcam_out.bil: raster file containing valid land cells matched to GCAM region codes.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins (Generated by the moirai LDS)

• region_gcam_out_noland.bil: raster file containing non-land cells matched to GCAM region codes.

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins (Generated by the moirai LDS)

• Global235_CLM_5arcmin.bil: raster file containing basin boundaries for all cells output by moirai

crs: EPSG:4326 WGS84 - World Geodetic System 1984

resolution: 0.5 arc mins

• GCAM_region_names.csv- Mapping file with details on GCAM region names (Used to fill in metadata)
• iso_GCAM_regID.csv- Mapping file containing details on individual country names by iso code. (Used to fill in metadata)
• basin_to_country_mapping.csv – Mapping file containing details on basin names by country and region. (Used to fill in metadata),

main_outputs contains the following,

column names in outputs:

• key: Unique identifier for feature
• reg_id: Unique identifier for region (region number)
• ctry_id: Unique identifier for country (country number)
• glu_id: Unique identifier for basin (basin number)
• reg_nm: Region name
• ctry_nm: Country name
• glu_nm: Basin name

See the README for more details on the data

This dataset provides the country, states, district, and sub-district levels administrative boundaries for India in a Shape file format. Rendered in the industry-standard coordinate reference system, EPSG:4326 (WGS84), this dataset ensures precision and compatibility.

Download In State Plane Projection Here. Municipal boundaries are based on annexations, court orders and other legal documents filed in the office of the Recorder of Deeds. Mapping is based on the legal descriptions from those documents, which relate to existing parcel boundaries or to the underlying PLSS. Important attributes include "Type" which contains an "I" if the polygon represents an incorporated area, and a "U" if unincorporated. The municipality name for "I" type polygons is included in the attribute "NAME1."

Update Frequency: This dataset is updated on a weekly basis.

This article traces the history of New York City’s geographic school subdistrict boundaries throughout the 20th century, exploring the historical relationship between race, space, and schooling in New York City and beyond. It seeks to both make the case for studying the spatial history of within-district education boundaries and put the results of our historical mapping project into the public domain. Ultimately we hope that researchers will use our data to explore their own questions about the history of New York City, its neighborhoods, and its schools, and that some may embark upon similar boundary-mapping projects for other cities, counties and school systems.​

This data set is one of many developed in support of The High Plains Groundwater Availability Project and the U.S. Geological Survey Data Series Report: Geodatabase Compilation of Hydrogeologic, Remote Sensing, and Water-Budget-Component data for the High Plains aquifer, 2011 (DS 777). The creation of the model grid is an important first step in developing a groundwater-flow model, because all model inputs including properties, wells, and boundary conditions are assigned to the model cells. The northern High Plains groundwater-flow model boundary feature dataset contains three feature classes; the model grid cells for the northern High Plains groundwater-flow model in both polygon (cell) and point (centroid) format and the external boundary of the model. The model grid contains 449,175 cells, 565 rows and 795 columns. Each cell is 1,000 feet per side. The model grid is not rotated. The external boundary includes the active and inactive areas of the model. The projection for the model grid and all feature classes in all geodatabases for this study are Albers Equal-Area Conic coordinate system, North American Datum1983.

Pennsylvania county spatial data for use in showing county boundary lines in mapping visualizations. County boundaries within Pennsylvania as delineated for the PennDOT Type 10 general highway map. Originator:Pennsylvania Department of Transportation, Bureau of Planning and Research, Cartographic Information Division Publication_Date:202106 Title: PennDOT - Pennsylvania County Boundaries Geospatial_Data_Presentation_Form:vector digital data Publication_Information: Publication_Place:Harrisburg, PA Publisher:Pennsylvania Department of Transportation

Use_Constraints: The user shall indemnify, save harmless, and, if requested, defend the COMMONWEALTH, their officers, agents, and employees from and against any suits, claims, or actions for injury, death, or property damage arising out of the use of or any defect in the FILES or any accompanying documentation.

The COMMONWEALTH excludes any and all implied warranties, including warranties or merchantability and fitness for a particular purpose.

The COMMONWEALTH makes no warranty or representation, either express or implied, with respect to the FILES or accompanying documentation, including its quality, performance, merchantability, or fitness for a particular purpose. The FILES and documentation are provided "as is" and the USER assumes the entire risk as to its quality and performance.

The COMMONWEALTH will not be liable for any direct, indirect, special, incidental, or consequential damages arising out of the use or inability to use the FILES or any accompanying documentation.

The USER is granted permission to translate and add value to the FILES for the use of the FILES on its computer hardware; provided, however, that the USER annually notify the COMMONWEALTH of any customizing or value-adding work done.

Any customized or value added versions of the files will contain the following disclaimer:

THIS IS NOT A PENNSYLVANIA DEPARTMENT OF TRANSPORTATION APPROVED FILE. THE DEPARTMENT OF TRANSPORTATION RETAINS THE MASTER FILES.

THE USER AGREES AND UNDERSTANDS THAT IT MAY NOT FURTHER DISTRIBUTE THE FILES TO A THIRD PARTY.

This dataset combines Brisbane City Council property information with the Queensland Government Digital Cadastral Database (DCDB) to show property holdings in Brisbane City Council area.A property holding is a Council-defined and managed information entity. Its boundaries are generally based on land parcels. A property holding may consist of one or multiple land parcels.The Digital Cadastral Database (DCDB) is the spatial representation of every current parcel of land in Queensland, and its legal Lot on Plan description and relevant attributes. It provides the map base for systems dealing with land related information. The DCDB is considered to be the point of truth for the graphical representation of property boundaries. It is not the point of truth for the legal property boundary or related attribute information, this will always be the plan of survey or the related titling information and administrative data sets.

This geospatial dataset was created by uploading a shapefile through the new import experience (DSMUI). The original shapefile is attached and was downloaded from https://data-seattlecitygis.opendata.arcgis.com/datasets/municipal-boundaries.

The list of study sites, meteorological stations and locations of interest that are shown on the Bonanza Creek Long Term Ecological Research site (BNZ LTER) internet map server (IMS, available at http://www.lter.uaf.edu/ims_intro.cfm) is generated from the LTER study sites database. The information is converted into a shapefile and posted to the IMS. Some study sites shown on the main LTER website will not appear on the IMS because they do not have location coordinates. In all cases the most up-to-date information will be found on the (study sites website ).

The spatial information represented on the IMS is available to the public according to the restrictions outlined in the LTER data policy. The dataset represented here consists of the map layers shown on the IMS. The information consists of shapefiles in Environmental Systems Research Institute (ESRI) format. Users of this dataset should be aware that the contents are dynamic. Portions of the information shown on the IMS are derived from the Bonanza Creek LTER databank and are constantly being updated.

The Watershed Boundary Dataset (WBD) from The National Map (TNM) defines the perimeter of drainage areas formed by the terrain and other landscape characteristics. The drainage areas are nested within each other so that a large drainage area, such as the Upper Mississippi River, is composed of multiple smaller drainage areas, such as the Wisconsin River. Each of these smaller areas can further be subdivided into smaller and smaller drainage areas. The WBD uses six different levels in this hierarchy, with the smallest averaging about 30,000 acres. The WBD is made up of polygons nested into six levels of data respectively defined by Regions, Subregions, Basins, Subbasins, Watersheds, and Subwatersheds. For additional information on the WBD, go to https://nhd.usgs.gov/wbd.html. The USGS National Hydrography Dataset (NHD) service is a companion dataset to the WBD. The NHD is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD is available nationwide in two seamless datasets, one based on 1:24,000-scale maps and referred to as high resolution NHD, and the other based on 1:100,000-scale maps and referred to as medium resolution NHD. Additional selected areas in the United States are available based on larger scales, such as 1:5,000-scale or greater, and referred to as local resolution NHD. For more information on the NHD, go to https://nhd.usgs.gov/index.html. Hydrography data from The National Map supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. Hydrography data is commonly combined with other data themes, such as boundaries, elevation, structures, and transportation, to produce general reference base maps. The National Map viewer allows free downloads of public domain WBD and NHD data in either Esri File or Personal Geodatabase, or Shapefile formats. The Watershed Boundary Dataset is being developed under the leadership of the Subcommittee on Spatial Water Data, which is part of the Advisory Committee on Water Information (ACWI) and the Federal Geographic Data Committee (FGDC). The USDA Natural Resources Conservation Service (NRCS), along with many other federal agencies and national associations, have representatives on the Subcommittee on Spatial Water Data. As watershed boundary geographic information systems (GIS) coverages are completed, statewide and national data layers will be made available via the Geospatial Data Gateway to everyone, including federal, state, local government agencies, researchers, private companies, utilities, environmental groups, and concerned citizens. The database will assist in planning and describing water use and related land use activities. Resources in this dataset:Resource Title: Watershed Boundary Dataset (WBD). File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/water/watersheds/dataset/?cid=nrcs143_021630 Web site for the Watershed Boundary Dataset (WBD), including links to:

Review Data Availability (Status Maps) Obtain Data by State, County, or Other Area Obtain Seamless National Data offsite link image
Geospatial Data Tools National Technical and State Coordinators Information about WBD dataset

Keeping track of locations across self-motion is possible by continuously updating spatial representations or by encoding and later instantaneously retrieving spatial representations. In virtual reality (VR), sensory cues to self-motion used in continuous updating are typically reduced. In passive translation compared to real walking in VR, optic flow is available but body-based (idiothetic) cues are missing. With both kinds of translation, boundaries and landmarks as static visual cues can be used for instantaneous updating. In two experiments, we let participants encode two target locations, one of which had to be reproduced by pointing after forward translation in immersive VR (HMD). We increased sensory cues to self-motion in comparison to passive translation either by strengthening optic flow or by real walking. Furthermore, we varied static visual cues in the form of boundaries and landmarks inside boundaries. Increased optic flow and real walking did not reliably increase performance suggesting that optic flow even in a sparse environment was sufficient for continuous updating or that merely instantaneous updating took place. Boundaries and landmarks, however, did support performance as quantified by decreased bias and increased precision, particularly if they were close to or even enclosed target locations. Thus, enriched spatial context is a viable method to support spatial updating in VR and synthetic environments (teleoperation). Spatial context does not only provide a static visual reference in offline updating and continuous allocentric self-location updating but also, according to recent neuroscientific evidence on egocentric bearing cells, contributes to continuous egocentric location updating as well.

Data documentation: GCAM USA state-glu spatial boundaries with mapping/aggregation file

Summary: These data products present a vector file which represents the intersections of state boundaries for USA with GCAM basin boundaries within USA and a mapping file that can be used to

1. map basin level data to states within the USA region (based on area)
2. map state level data to basins within the USA region (based on area)

The vector file presents metadata to the user regarding the state name, state id, glu name and glu id along with a unique key for each polygon. These spatial boundaries can be reproduced/updated by updating the inputs and making use of the methodology described below.

CONTENTS:

gcamusa_state_glu_wgs84 folder contains the following,

shape_file folder contains the following,

gcamusa_state_glu_wgs84.shp

column names in outputs:

• key: Unique identifier for feature
• state_id: Unique identifier for state (state geo id)
• glu_id: Unique identifier for basin (basin number)
• state_nm: State name
• glu_nm: Basin name

mapping_file folder contains the following,

state_glu_mapping_WGS84.csv

column names in outputs:

• state_id: Unique identifier for state (state geo id)
• glu_id: Unique identifier for basin (basin number)
• state_nm: State name
• glu_nm: Basin name
• state_area: Geometric area calculated for each state
• glu_area: Geometric area calculated for basin/glu
• intersection_area: Geometric area calculated for each basin-glu intersection
• state_proportion: Share of glu value in a state
• glu_proportion: Share of state value in a glu

input_files folder contains the following,

• glu_boundaries_moirai_combined_3p1_0p5arcmin : A shape file containing boundaries for the GCAM glu’s. source: https://zenodo.org/record/4014308#.X6nkQ2hKhaR
• tl_2019_us_state.shp : A shape file containing boundaries for USA states. Source: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html

Methodology and reproducibility: The vector and mapping files were generated using the function located here- https://github.com/JGCRI/rgis/pull/7/commits/32ccb8cf8a30a66a84044da317b9041f492777be

In order to reproduce or update the outputs the user would have to follow the following steps:

1. Clone the rgis package from GitHub - https://github.com/JGCRI/rgis

Use the get_intersection_fractions() function. Set the shpfile_1 parameter to the path to the latest state boundaries and set shpfile_2 parameter to the path to the glu boundaries shape file. Set the out_csv parameter to the desired mapping file name and set the out_shape_file parameter name to the desired vector output name.

This data release contains fractional intersectional weights used to crosswalk data from the National Water Use Program to the National Integrated Water Availability Assessment (IWAAs) projects. The Watershed Boundary Dataset (WBD; https://www.usgs.gov/national-hydrography/watershed-boundary-dataset) is a companion dataset to the National Hydrography Dataset and contains polygons that define the spatial boundaries of hydrologic units (i.e., the area of land the landscape that drains into a portion of the stream network). These are periodically updated as these boundary definitions are refined by incorporating better, more localized data. When aggregating data from multiple sources that rely on data from the WBD, a situation can occur where different datasets rely on different versions (or “snapshots”) of the WBD. This was the case for the IWAAs National Report which relied upon data using a version of the WBD found in the Mainstem Rivers data release (https://doi.org/10.5066/P92U7ZUT) as well as data that relied upon a version used by the National Water Use Program (https://doi.org/10.5066/P9FUL880). This dataset is the output of a pipeline of R code published as a software release (https://doi.org/10.5066/P1UANON8) and contains the fraction of spatial overlap (i.e., weights) between the subwatershed (HUC12) boundaries from these two versions of the WBD. These weights can be used as a crosswalk between the two snapshots of the WBD.