Protocol for identifying and managing point-in-polygon aggregation uncertainty.

This GIS dataset is a result of the compilation of all existing Alberta Geological Survey sand and gravel geology and resource data into digital format. Data sources include Alberta Geological Survey maps and reports produced between 1976 and 2006. References are provided as an attribute so the user can refer back to the original maps and reports. Attributes include study level, material description, references, area, sand and gravel thickness, and gravel and sand volumes. In 2009, data from newly mapped area NTS 83N/NE were added.

Jurisdictional Unit, 2022-05-21. For use with WFDSS, IFTDSS, IRWIN, and InFORM.This is a feature service which provides Identify and Copy Feature capabilities. If fast-drawing at coarse zoom levels is a requirement, consider using the tile (map) service layer located at https://nifc.maps.arcgis.com/home/item.html?id=3b2c5daad00742cd9f9b676c09d03d13.OverviewThe Jurisdictional Agencies dataset is developed as a national land management geospatial layer, focused on representing wildland fire jurisdictional responsibility, for interagency wildland fire applications, including WFDSS (Wildland Fire Decision Support System), IFTDSS (Interagency Fuels Treatment Decision Support System), IRWIN (Interagency Reporting of Wildland Fire Information), and InFORM (Interagency Fire Occurrence Reporting Modules). It is intended to provide federal wildland fire jurisdictional boundaries on a national scale. The agency and unit names are an indication of the primary manager name and unit name, respectively, recognizing that:There may be multiple owner names.Jurisdiction may be held jointly by agencies at different levels of government (ie State and Local), especially on private lands, Some owner names may be blocked for security reasons.Some jurisdictions may not allow the distribution of owner names. Private ownerships are shown in this layer with JurisdictionalUnitIdentifier=null,JurisdictionalUnitAgency=null, JurisdictionalUnitKind=null, and LandownerKind="Private", LandownerCategory="Private". All land inside the US country boundary is covered by a polygon.Jurisdiction for privately owned land varies widely depending on state, county, or local laws and ordinances, fire workload, and other factors, and is not available in a national dataset in most cases.For publicly held lands the agency name is the surface managing agency, such as Bureau of Land Management, United States Forest Service, etc. The unit name refers to the descriptive name of the polygon (i.e. Northern California District, Boise National Forest, etc.).These data are used to automatically populate fields on the WFDSS Incident Information page.This data layer implements the NWCG Jurisdictional Unit Polygon Geospatial Data Layer Standard.Relevant NWCG Definitions and StandardsUnit2. A generic term that represents an organizational entity that only has meaning when it is contextualized by a descriptor, e.g. jurisdictional.Definition Extension: When referring to an organizational entity, a unit refers to the smallest area or lowest level. Higher levels of an organization (region, agency, department, etc) can be derived from a unit based on organization hierarchy.Unit, JurisdictionalThe governmental entity having overall land and resource management responsibility for a specific geographical area as provided by law.Definition Extension: 1) Ultimately responsible for the fire report to account for statistical fire occurrence; 2) Responsible for setting fire management objectives; 3) Jurisdiction cannot be re-assigned by agreement; 4) The nature and extent of the incident determines jurisdiction (for example, Wildfire vs. All Hazard); 5) Responsible for signing a Delegation of Authority to the Incident Commander.See also: Unit, Protecting; LandownerUnit IdentifierThis data standard specifies the standard format and rules for Unit Identifier, a code used within the wildland fire community to uniquely identify a particular government organizational unit.Landowner Kind & CategoryThis data standard provides a two-tier classification (kind and category) of landownership. Attribute Fields JurisdictionalAgencyKind Describes the type of unit Jurisdiction using the NWCG Landowner Kind data standard. There are two valid values: Federal, and Other. A value may not be populated for all polygons.JurisdictionalAgencyCategoryDescribes the type of unit Jurisdiction using the NWCG Landowner Category data standard. Valid values include: ANCSA, BIA, BLM, BOR, DOD, DOE, NPS, USFS, USFWS, Foreign, Tribal, City, County, OtherLoc (other local, not in the standard), State. A value may not be populated for all polygons.JurisdictionalUnitNameThe name of the Jurisdictional Unit. Where an NWCG Unit ID exists for a polygon, this is the name used in the Name field from the NWCG Unit ID database. Where no NWCG Unit ID exists, this is the “Unit Name” or other specific, descriptive unit name field from the source dataset. A value is populated for all polygons.JurisdictionalUnitIDWhere it could be determined, this is the NWCG Standard Unit Identifier (Unit ID). Where it is unknown, the value is ‘Null’. Null Unit IDs can occur because a unit may not have a Unit ID, or because one could not be reliably determined from the source data. Not every land ownership has an NWCG Unit ID. Unit ID assignment rules are available from the Unit ID standard, linked above.LandownerKindThe landowner category value associated with the polygon. May be inferred from jurisdictional agency, or by lack of a jurisdictional agency. A value is populated for all polygons. There are three valid values: Federal, Private, or Other.LandownerCategoryThe landowner kind value associated with the polygon. May be inferred from jurisdictional agency, or by lack of a jurisdictional agency. A value is populated for all polygons. Valid values include: ANCSA, BIA, BLM, BOR, DOD, DOE, NPS, USFS, USFWS, Foreign, Tribal, City, County, OtherLoc (other local, not in the standard), State, Private.DataSourceThe database from which the polygon originated. Be as specific as possible, identify the geodatabase name and feature class in which the polygon originated.SecondaryDataSourceIf the Data Source is an aggregation from other sources, use this field to specify the source that supplied data to the aggregation. For example, if Data Source is "PAD-US 2.1", then for a USDA Forest Service polygon, the Secondary Data Source would be "USDA FS Automated Lands Program (ALP)". For a BLM polygon in the same dataset, Secondary Source would be "Surface Management Agency (SMA)."SourceUniqueIDIdentifier (GUID or ObjectID) in the data source. Used to trace the polygon back to its authoritative source.MapMethod:Controlled vocabulary to define how the geospatial feature was derived. Map method may help define data quality. MapMethod will be Mixed Method by default for this layer as the data are from mixed sources. Valid Values include: GPS-Driven; GPS-Flight; GPS-Walked; GPS-Walked/Driven; GPS-Unknown Travel Method; Hand Sketch; Digitized-Image; DigitizedTopo; Digitized-Other; Image Interpretation; Infrared Image; Modeled; Mixed Methods; Remote Sensing Derived; Survey/GCDB/Cadastral; Vector; Phone/Tablet; OtherDateCurrentThe last edit, update, of this GIS record. Date should follow the assigned NWCG Date Time data standard, using 24 hour clock, YYYY-MM-DDhh.mm.ssZ, ISO8601 Standard.CommentsAdditional information describing the feature. GeometryIDPrimary key for linking geospatial objects with other database systems. Required for every feature. This field may be renamed for each standard to fit the feature.JurisdictionalUnitID_sansUSNWCG Unit ID with the "US" characters removed from the beginning. Provided for backwards compatibility.JoinMethodAdditional information on how the polygon was matched information in the NWCG Unit ID database.LocalNameLocalName for the polygon provided from PADUS or other source.LegendJurisdictionalAgencyJurisdictional Agency but smaller landholding agencies, or agencies of indeterminate status are grouped for more intuitive use in a map legend or summary table.LegendLandownerAgencyLandowner Agency but smaller landholding agencies, or agencies of indeterminate status are grouped for more intuitive use in a map legend or summary table.DataSourceYearYear that the source data for the polygon were acquired.Data InputThis dataset is based on an aggregation of 4 spatial data sources: Protected Areas Database US (PAD-US 2.1), data from Bureau of Indian Affairs regional offices, the BLM Alaska Fire Service/State of Alaska, and Census Block-Group Geometry. NWCG Unit ID and Agency Kind/Category data are tabular and sourced from UnitIDActive.txt, in the WFMI Unit ID application (https://wfmi.nifc.gov/unit_id/Publish.html). Areas of with unknown Landowner Kind/Category and Jurisdictional Agency Kind/Category are assigned LandownerKind and LandownerCategory values of "Private" by use of the non-water polygons from the Census Block-Group geometry.PAD-US 2.1:This dataset is based in large part on the USGS Protected Areas Database of the United States - PAD-US 2.`. PAD-US is a compilation of authoritative protected areas data between agencies and organizations that ultimately results in a comprehensive and accurate inventory of protected areas for the United States to meet a variety of needs (e.g. conservation, recreation, public health, transportation, energy siting, ecological, or watershed assessments and planning). Extensive documentation on PAD-US processes and data sources is available.How these data were aggregated:Boundaries, and their descriptors, available in spatial databases (i.e. shapefiles or geodatabase feature classes) from land management agencies are the desired and primary data sources in PAD-US. If these authoritative sources are unavailable, or the agency recommends another source, data may be incorporated by other aggregators such as non-governmental organizations. Data sources are tracked for each record in the PAD-US geodatabase (see below).BIA and Tribal Data:BIA and Tribal land management data are not available in PAD-US. As such, data were aggregated from BIA regional offices. These data date from 2012 and were substantially updated in 2022. Indian Trust Land affiliated with Tribes, Reservations, or BIA Agencies: These data are not considered the system of record and are not intended to be used as such. The Bureau of Indian Affairs (BIA), Branch of Wildland Fire Management (BWFM) is not the originator of these data. The

“Aggregates” is the term geologists use to describe rocks used for building and construction purposes. Aggregate Potential Mapping aims to identify areas where aggregate is most likely to be found.It is a vector dataset. Vector data portray the world using points, lines, and polygons (areas). The data is shown as points and polygonsPlease read the metadata lineage for each layer for further information.

This dataset is a spatially reaggregated version of the original national Africover multipurpose database. The original full resolution land cover has been produced from visual interpretation of digitally enhanced LANDSAT TM images (Bands 4,3,2) acquired mainly in the year 1999. The data was aggregated by eliminating polygons below a certain area threshold to give priority to the classes belonging to Agriculture. This threshold corresponds to approx. a 30 % reduction in the polygon count. The dataset was then re-aggregated based on area threshold values. For more information on the area thresholds used to spatially aggregate the land cover data, please see the 'spatial-agg-procedure' document included in the zip file available here for download. The land cover classes have been developed using the FAO/UNEP international standard LCCS classification system. The data set is intended for free public access. The shape main attributes correspond to the following fields: -ID -HECTARES -USERLABEL -LCCCODE (unique LCCS code) -CODE1 -CODE2 -CODE3 -LC You can download a zip archive containing: -the dataset er-spatial-agg (.shp) -the Eritrea Classifiers Used (.pdf) -the Eritrea legend (.pdf and .xls) -the Eritrea Legend - LCCS Import file (.xls) -the spatial-agg-procedure (.pdf) -the Userlabel Definitions (.pdf) Note: the document Eritrea Classifiers Used.pdf, is a list of all the LCCS classifiers used in the study area. They are grouped under the 8 major land cover types. In addition to the standard classifiers contained in LCCS the user may find “user defined†classifiers used by the map producer to add additional information to a specific class, not available in LCCS. The user-defined attributes are always coded with the letter “Z†.

This GIS dataset is a result of the compilation of all existing Alberta Geological Survey sand and gravel geology and resource data into digital format. Data sources include Alberta Geological Survey maps and reports produced between 1976 and 2006. References are provided as an attribute so the user can refer back to the original maps and reports. Attributes include study level, material description, references, area, sand and gravel thickness, and gravel and sand volumes. In 2009, data from newly mapped area NTS 83N/NE were added.

The dataset on aggregate extractions in the European seas was created in 2014 by AZTI for the European Marine Observation and Data Network (EMODnet). It is the result of the aggregation and harmonization of datasets provided by several sources from all across Europe. It is available for viewing and download on EMODnet web portal (Human Activities, https://emodnet.ec.europa.eu/en/human-activities). The dataset contains points representing aggregate extraction sites, by year (although some data are indicated by a period of years), in the following countries: Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Lithuania, Poland, Portugal, Spain, Sweden, The Netherlands and United Kingdom. Where available, each point has the following attributes: Id (Identifier), Position Info (e.g.: Estimated, Original, Polygon centroid of dredging area, Estimated polygon centroid of dredging area), Country, Sea basin, Sea, Name of the extraction area, Area of activity (km2), Year (the year when the extraction took place; when a time period is available, the first year of the period is indicated), Permitted Amount (m3) (permitted amount of material to be extracted, in m3), Permitted Amount (t) (permitted amount of material to be extracted, in tonnes), Requested Amount (m3) (requested amount of material to be extracted, in m3), Requested Amount (t) (requested amount of material to be extracted, in tonnes), Extracted Amount (m3) (extracted amount of material, in m3), Extracted Amount (t) (extracted amount of material, in tonnes), Extraction Type (Marine sediment extraction), Purpose (e.g.: Commercial, Others, N/A), End Use (e.g.: Beach nourishment, Construction, Reclamation fill, N/A), Material type (e.g.: sand, gravel, maerl), Notes, Link to Web Sources. In 2018, a feature on areas for aggregate extractions was included. It contains polygons representing areas of seabed licensed for exploration or extraction of aggregates, in the following countries: Belgium, Denmark, Estonia, Finland, France, Germany, Italy, Lithuania, Poland, Portugal, Russia, Spain, Sweden, The Netherlands and United Kingdom. Where available, each polygon has the following attributes: Id (Identifier), Area code, Area name, Country, Sea basin, Sea, Starting year (the year when the license starts), End year (the year when the license ends), Site Type (exploration area, extraction area, extraction area (in use)), License status (Active, not active, expired, unknown), Material type (e.g.: sand, gravel, maerl), Notes, Distance to coast (in metres), Link to Web Sources. In the 2025 update, extraction data until 2024 and new areas have been included.

The Roads database includes an inventory of road assets (roadways, blocks, intersections, sidewalks, curbs) with a spatial representation and various attached information. Aggregate pavement assets represent carriageways located in the public domain and that are part of the local or arterial road network. Aggregate pavements are represented by polygons that are aggregated by type of use. Among the information associated with a pavement object is the date of construction, the date of resurfacing, the date of survey, the materials of the pavement, the type of foundation, the presence of a bicycle lane, the use, etc. Intersecting road assets represent road crossings located in public areas that are part of the local or arterial road network. Intersections are represented by polygons that are cut according to the number of traffic axes. Information associated with an intersecting object includes the construction date, resurfacing date, survey date, intersection materials, foundation type, presence of bike lanes, etc. Data is also available in separate sets on the portal to support several uses: - Road asset (complete database) - Sidewalk and island - Off-road zone Warnings - The data released on road assets are those in the possession of the City's geomatics team and are not necessarily up to date throughout the territory. - The data released on road assets is provided for information purposes only and should not be used for the purposes of designing or carrying out works or for the location of assets.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

“Aggregates” is the term geologists use to describe rocks used for building and construction purposes. Aggregate Potential Mapping aims to identify areas where aggregate is most likely to be found.This map shows the granular aggregate potential across Ireland. To produce this map, scores from 1 to 10 were given to each area based on several factors: Genesis-Petrology (2)Number of pits (1.2)Area (2)*Thickness (2)*Elevation (0.5)Markets (1.2)*In the case of ‘alluvium’ the factor is 1.0.The factors were weighted by a multiplication factor (in brackets after the listed factors above). The final score is obtained by summing the weighted scores to give a final score ranging from 3.5 to 100. This map shows the scores sorted into five different ranges:Very High potential - redHigh potential - orangeModerate Potential - yellowLow Potential - greenVery Low Potential – blueUnlike the crushed rock potential map there are large areas uncoloured because sand or gravel has not been mapped in these areas.This map is to the scale 1:50,000. This means it should be viewed at that scale. When printed at that scale 1cm on the map relates to a distance of 500m.It is a vector dataset. Vector data portray the world using points, lines, and polygons (areas). The data is shown as polygons. Each polygon holds information on the Granular Aggregate Potential, the county it is located in and the area in m2.Please read the metadata lineage for further information.

DescriptionThis is a vector tile layer built from the same data as the Jurisdictional Units Public feature service located here: https://nifc.maps.arcgis.com/home/item.html?id=4107b5d1debf4305ba00e929b7e5971a. This service can be used alone as a fast-drawing background layer, or used in combination with the feature service when Identify and Copy Feature capabilities are needed. At fine zoom levels, the feature service will be needed.OverviewThe Jurisdictional Units dataset outlines wildland fire jurisdictional boundaries for federal, state, and local government entities on a national scale and is used within multiple wildland fire systems including the Wildland Fire Decision Support System (WFDSS), the Interior Fuels and Post-Fire Reporting System (IFPRS), the Interagency Fuels Treatment Decision Support System (IFTDSS), the Interagency Fire Occurrence Reporting Modules (InFORM), the Interagency Reporting of Wildland Fire Information System (IRWIN), and the Wildland Computer-Aided Dispatch Enterprise System (WildCAD-E).In this dataset, agency and unit names are an indication of the primary manager’s name and unit name, respectively, recognizing that:There may be multiple owner names.Jurisdiction may be held jointly by agencies at different levels of government (ie State and Local), especially on private lands, Some owner names may be blocked for security reasons.Some jurisdictions may not allow the distribution of owner names. Private ownerships are shown in this layer with JurisdictionalUnitIID=null, JurisdictionalKind=null, and LandownerKind="Private", LandownerCategory="Private". All land inside the US country boundary is covered by a polygon.Jurisdiction for privately owned land varies widely depending on state, county, or local laws and ordinances, fire workload, and other factors, and is not available in a national dataset in most cases.For publicly held lands the agency name is the surface managing agency, such as Bureau of Land Management, United States Forest Service, etc. The unit name refers to the descriptive name of the polygon (i.e. Northern California District, Boise National Forest, etc.).AttributesField NameDefinitionGeometryIDPrimary key for linking geospatial objects with other database systems. Required for every feature. Not populated for Census Block Groups.JurisdictionalUnitIDWhere it could be determined, this is the NWCG Unit Identifier (Unit ID). Where it is unknown, the value is ‘Null’. Null Unit IDs can occur because a unit may not have a Unit ID, or because one could not be reliably determined from the source data. Not every land ownership has an NWCG Unit ID. Unit ID assignment rules are available in the Unit ID standard.JurisdictionalUnitID_sansUSNWCG Unit ID with the "US" characters removed from the beginning. Provided for backwards compatibility.JurisdictionalUnitNameThe name of the Jurisdictional Unit. Where an NWCG Unit ID exists for a polygon, this is the name used in the Name field from the NWCG Unit ID database. Where no NWCG Unit ID exists, this is the “Unit Name” or other specific, descriptive unit name field from the source dataset. A value is populated for all polygons except for Census Blocks Group and for PAD-US polygons that did not have an associated name.LocalNameLocal name for the polygon provided from agency authoritative data, PAD-US, or other source.JurisdictionalKindDescribes the type of unit jurisdiction using the NWCG Landowner Kind data standard. There are two valid values: Federal, Other, and Private. A value is not populated for Census Block Groups.JurisdictionalCategoryDescribes the type of unit jurisdiction using the NWCG Landowner Category data standard. Valid values include: BIA, BLM, BOR, DOD, DOE, NPS, USFS, USFWS, Foreign, Tribal, City, County, State, OtherLoc (other local, not in the standard), Private, and ANCSA. A value is not populated for Census Block Groups.LandownerKindThe landowner kind value associated with the polygon. May be inferred from jurisdictional agency, or by lack of a jurisdictional agency. Legal values align with the NWCG Landowner Kind data standard. A value is populated for all polygons.LandownerCategoryThe landowner category value associated with the polygon. May be inferred from jurisdictional agency, or by lack of a jurisdictional agency. Legal values align with the NWCG Landowner Category data standard. A value is populated for all polygons.LandownerDepartmentFederal department information that aligns with a unit’s landownerCategory information. Legal values include: Department of Agriculture, Department of Interior, Department of Defense, and Department of Energy. A value is not populated for all polygons.DataSourceThe database from which the polygon originated. An effort is made to be as specific as possible (i.e. identify the geodatabase name and feature class in which the polygon originated).SecondaryDataSourceIf the DataSource field is an aggregation from other sources, use this field to specify the source that supplied data to the aggregation. For example, if DataSource is "PAD-US 4.0", then for a TNC polygon, the SecondaryDataSource would be " TNC_PADUS2_0_SA2015_Public_gdb ".SourceUniqueIDIdentifier (GUID or ObjectID) in the data source. Used to trace the polygon back to its authoritative source.DataSourceYearYear that the source data for the polygon were acquired.MapMethodControlled vocabulary to define how the geospatial feature was derived. MapMethod will be Mixed Methods by default for this layer as the data are from mixed sources. Valid Values include: GPS-Driven; GPS-Flight; GPS-Walked; GPS-Walked/Driven; GPS-Unknown Travel Method; Hand Sketch; Digitized-Image; DigitizedTopo; Digitized-Other; Image Interpretation; Infrared Image; Modeled; Mixed Methods; Remote Sensing Derived; Survey/GCDB/Cadastral; Vector; Phone/Tablet; Other.DateCurrentThe last edit, update, of this GIS record. Date should follow the assigned NWCG Date Time data standard, using the 24-hour clock, YYYY-MM-DDhh.mm.ssZ, ISO8601 Standard.CommentsAdditional information describing the feature.JoinMethodAdditional information on how the polygon was matched to information in the NWCG Unit ID database.LegendJurisdictionalCategoryJurisdictionalCategory values grouped for more intuitive use in a map legend or summary table. Census Block Groups are classified as “No Unit”.LegendLandownerCategoryLandownerCategory values grouped for more intuitive use in a map legend or summary table.Other Relevant NWCG Definition StandardsUnitA generic term that represents an organizational entity that only has meaning when it is contextualized by a descriptor, e.g. jurisdictional.Definition Extension: When referring to an organizational entity, a unit refers to the smallest area or lowest level. Higher levels of an organization (region, agency, department, etc.) can be derived from a unit based on organization hierarchy.Unit, JurisdictionalThe governmental entity having overall land and resource management responsibility for a specific geographical area as provided by law.Definition Extension: 1) Ultimately responsible for the fire report to account for statistical fire occurrence; 2) Responsible for setting fire management objectives; 3) Jurisdiction cannot be re-assigned by agreement; 4) The nature and extent of the incident determines jurisdiction (for example, Wildfire vs. All Hazard); 5) Responsible for signing a Delegation of Authority to the Incident Commander.See also: Protecting Unit; LandownerData SourcesThis dataset is an aggregation of multiple spatial data sources: • Authoritative land ownership records from BIA, BLM, NPS, USFS, USFWS, and the Alaska Fire Service/State of Alaska• The Protected Areas Database US (PAD-US 4.0)• Census Block-Group Geometry BIA and Tribal Data:BIA and Tribal land management data were aggregated from BIA regional offices. These data date from 2012 and were reviewed/updated in 2024. Indian Trust Land affiliated with Tribes, Reservations, or BIA Agencies: These data are not considered the system of record and are not intended to be used as such. The Bureau of Indian Affairs (BIA), Branch of Wildland Fire Management (BWFM) is not the originator of these data. The spatial data coverage is a consolidation of the best available records/data received from each of the 12 BIA Regional Offices. The data are no better than the original sources from which they were derived. Care was taken when consolidating these files. However, BWFM cannot accept any responsibility for errors, omissions, or positional accuracy in the original digital data. The information contained in these data is dynamic and is continually changing. Updates to these data will be made whenever such data are received from a Regional Office. The BWFM gives no guarantee, expressed, written, or implied, regarding the accuracy, reliability, or completeness of these data.Alaska:The state of Alaska and Alaska Fire Service (BLM) co-manage a process to aggregate authoritative land ownership, management, and jurisdictional boundary data, based on Master Title Plats. Data ProcessingTo compile this dataset, the authoritative land ownership records and the PAD-US data mentioned above were crosswalked into the Jurisdictional Unit Polygon schema and aggregated through a series of python scripts and FME models. Once aggregated, steps were taken to reduce overlaps within the data. All overlap areas larger than 300 acres were manually examined and removed with the assistance of fire management SMEs. Once overlaps were removed, Census Block Group geometry were crosswalked to the Jurisdictional Unit Polygon schema and appended in areas in which no jurisdictional boundaries were recorded within the authoritative land ownership records and the PAD-US data. Census Block Group geometries represent areas of unknown Landowner Kind/Category and Jurisdictional Kind/Category and were assigned LandownerKind and LandownerCategory values of "Private".Update

“Aggregates” is the term geologists use to describe rocks used for building and construction purposes. Aggregate Potential Mapping aims to identify areas where aggregate is most likely to be found.This map shows the granular aggregate potential across Ireland. To produce this map, scores from 1 to 10 were given to each area based on several factors: Genesis-Petrology (2)Number of pits (1.2)Area (2)*Thickness (2)*Elevation (0.5)Markets (1.2)*In the case of ‘alluvium’ the factor is 1.0.The factors were weighted by a multiplication factor (in brackets after the listed factors above). The final score is obtained by summing the weighted scores to give a final score ranging from 3.5 to 100. This map shows the scores sorted into five different ranges:Very High potential - redHigh potential - orangeModerate Potential - yellowLow Potential - greenVery Low Potential – blueUnlike the crushed rock potential map there are large areas uncoloured because sand or gravel has not been mapped in these areas.This map is to the scale 1:50,000. This means it should be viewed at that scale. When printed at that scale 1cm on the map relates to a distance of 500m.It is a vector dataset. Vector data portray the world using points, lines, and polygons (areas). The data is shown as polygons. Each polygon holds information on the Granular Aggregate Potential, the county it is located in and the area in m2.Please read the metadata lineage for further information.

“Aggregates” is the term geologists use to describe rocks used for building and construction purposes. Aggregate Potential Mapping (APM) aims to identify areas where aggregate is most likely to be found. In this project, “pits” are excavations into Quaternary sediments, and the gravel pit inventory is used to score Granular Aggregate Potential, “quarries” are excavations into bedrock, and the quarry inventory is used to score Crushed Rock Aggregate Potential.Evidence of extraction over time is a key indicator of aggregate potential. While older pits and quarries are important to include, the generally larger operations of recent times receive the highest scores in the APM process. These latter are also of more relevance in that they reflect the demands of modern aggregates production, both in market type and in material standards.This map shows the areas where pits and quarries occur across Ireland. The areas are displayed according to the period of activity.It is a vector dataset. Vector data portray the world using points, lines, and polygons (areas). The data is shown as polygons. Each polygon holds information on the county it is located, Pit or Quarry, Local Authority Reference, Site name, Site address, Operator, Status, Mineral, Processing, Products, Additional Details, Hours of operation, Source dataset and Activity Period.This map shows the locations where pits and quarries occur across Ireland. The areas are displayed according to type.It is a vector dataset. Vector data portray the world using points, lines, and polygons (areas). The data is shown as points. Each point holds information on the ID, Coordinates, Pit or Quarry Type, Age, Notes and Mineral Location Number.Please read the metadata lineage for further information.Please zoom in beyond 1:400,000 to see the data.

These service area polygons are derived from the FCC's National Broadband Map. Data are downloaded monthly from the BDC API, aggregated to the H3 level 8 polygons identified in the data, and then spatially dissolved to create individual polygons for each provider's technologies and max advertised speeds. Thus, each polygon represents the area a particular provider claims served by a given technology and up/down speeds.Because the data are aggregated by H3 ID and max speeds advertised by the provider for the given tech, each hexagon in the service area has at least one location where the provider advertises those speeds and technology. It does not guarantee all locations in that hexagon have that advertised service.The FCC data are updated on a twice-yearly schedule. We update monthly to catch any mid-cycle updates that may be released.Individual availability records are based on the “Location Fabric,” which is a collection of Broadband Serviceable Locations (BSLs) that identify individual locations that are served by mass-market broadband service or could conceivably order mass-market broadband service. This fabric is created and owned by a third-party consultant and licensed to the FCC and participating entities. This license prevents sharing the locations of the BSL to non-licensees but does allow aggregated data to be shared; hence why we aggregate the data to H3 level 8 polygons.

The data is used to determine the day of sanitation collection (rubbish and recycling) for a given location and set of households in the City of Philadelphia. The file is also used to aggregate data such as households, tonnage, and mileage. This polygon layer has an accompanying arc layer. Certain arcs in the arc layer contain data signifying information relating it to the polygon layer. It can tell you if both sides of the arc belong to one of the bounding polygons. All the arcs, including those with no boundary info, have naming attributes for labeling the polygon borders.

The Roads database includes an inventory of road assets (roadways, blocks, intersections, sidewalks, curbs) with a spatial representation and various attached information. Aggregate pavement assets represent roadways located in public areas that are part of the local or arterial road network. Aggregate pavements are represented by polygons that are aggregated by type of use. Among the information associated with a pavement object is the construction date, resurfacing date, survey date, survey date, pavement materials, foundation type, bicycle lane presence, use, etc. Intersecting road assets represent intersections of roadways located in the public domain and that are part of the local or arterial road network. Intersections are represented by polygons that are cut according to the number of traffic axes. Among the information associated with an intersecting object is the date of construction, the date of resurfacing, the date of survey, the date of survey, the materials of the intersection, the type of foundation, the presence of a bicycle path, etc. The data is also available in separate sets on the portal to support several uses: - Street asset (complete database) - [Sidewalk and island] lot] (/city-of-montreal/roadway-sidewalk-island) - Off-street zone Warnings - The data released on road assets are those in the possession of the City's geomatics team and are not necessarily up to date throughout the country. - The data released on road assets is provided for information purposes only and should not be used for the purposes of designing or carrying out works or for the location of assets.This third party metadata element was translated using an automated translation tool (Amazon Translate).

“Aggregates” is the term geologists use to describe rocks used for building and construction purposes. Aggregate Potential Mapping aims to identify areas where aggregate is most likely to be found.This map shows the crushed rock aggregate potential across Ireland. To produce this map, scores from 1 to 10 were given to each area based on several factors: Rock Type Suitability (2.8) - This tells us if the rock in an area is suitable for building purposes.Deleterious Substances (0.7) – This tells us if there is anything within the rock that might make it unsuitable for building purposes.Number of quarries (1.2) – This tells us if this rock is already being used for building purposes.Area (0.5) – This tells us if there is enough rock available to be worthwhile opening a quarry.Overburden thickness (2.0) – This tells us how much soil and other material needs to be removed to get to the rock.Elevation (0.8) – This tells us the height above sea level.Markets (1.2) – This tells us how close the area is to places where there will be a high demand for building materials.The final score is a number between 5 and 100. Final scores are classified into ten ranks (1-10) on an equal area basis. The ranks are grouped in twos to produce five Potentials, from Very High to Very Low. This map shows the scores sorted into five different Potentials:Very High potential - redHigh potential - orangeModerate Potential - yellowLow Potential - greenVery Low Potential - blueThis map is to the scale 1:100,000. This means it should be viewed at that scale. When printed at that scale 1cm on the map relates to a distance of 1km.It is a vector dataset. Vector data portray the world using points, lines, and polygons (areas). The data is shown as polygons. Each polygon holds information on the potential range value, the county it is located in, the rock unit name, primary rock type, all the scores used in the algorithm, rank, potential and the area in m2.Please read the lineage for further information.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The Geofabric Surface Catchments product is derived from the National Catchment Boundaries (NCB) V1.1.4. This data defines a catchment for every stream segment contained within the Geofabric Surface Network product according to the GEODATA Nine Second Digital Elevation Model (DEM-9S) Version 3. These stream segment level boundaries may be used individually or in aggregation. The product is designed to represent geographic surface boundaries that have a hydrological relationship to surface water features. The NCB Level 1 and NCB Level 2 features are the top two levels in the NCB Catchment hierarchy and have been provided as polygon boundaries. This product contains one Geofabric feature type called Catchment. It also contains three NCB feature types including: NCBLevel1Drainage Division, NCBLevel2Drainage Basin and NCBPfafstetter.

(http://www.bom.gov.au/water/geofabric/download.shtml )

Purpose

This product is intended to support the creation of or definition of topologically consistent and hydrologically enforced streamflow aggregation boundaries. The catchment attributes can be extending by linking the NCB Pfafstetter table to include the Pfafstetter reference system for identifying and aggregating catchments.

This product is intended to supplement the Geofabric Surface Cartography and Geofabric Surface Network data products. This product is also used to as the basis for building contracted catchments in the Geofabric Hydrology Reporting Catchments product and provides a spatial framework for analysis and assessment of streams and their catchments.

Dataset History

Geofabric Surface Catchments is part of a suite of Geofabric products produced by the Australian Bureau of Meteorology. The geometry of this product is largely derived from the National Catchment Boundaries (NCB) V1.1.4. It consists of catchments, NCB Level 1 Drainage Divisions, NCB Level 2 Drainage Basins and the NCB Pfafstetter table. The feature class terminology for Geofabric Surface Catchment components has been modified to distinguish it in terms of the products underlying data model.

The AHGFCatchments are based upon polygons converted from a regular 9 second grid delineating the NCBs for the Australian continent. The NCBs delineate hierarchically-nested catchments derived using an automated drainage analysis procedure based on a multi-flow extension of the version 3.1 flow direction grid associated with the 9 second DEM (GEODATA National 9 Second Digital Elevation Model (DEM-9S) Version 3, ANZLIC unique identifier: ANZCW0703011541).

At the highest levels in the hierarchy the NCBs aggregate the 9 second drainage basins (9 second Basins product name and ANZLIC identifier to be inserted) into 12 topographically-defined Drainage Divisions (Level 1) and 191 Drainage Basins (Level 2) approximating the Australian Water Resources Council (AWRC) River Basins (Australia's River Basins, Geoscience Australia, 1997 ANZLIC identifier: ANZCW0703005427) where possible. At lower levels, the Level 2 units are sub-divided into successively finer sub-catchments using a modified version of the Pfafstetter procedure (Verdin, K. L. and Verdin, J. P. (1999) A topological system for delineation and codification of the Earth's river basins. Journal of Hydrology, 218(1-2), 1-12).

This layer delineates the lowest level catchment units being the sub-catchments draining directly to a stream segment in the ANUDEM stream layer or, where there are no ANUDEM Derived Streams (ANUDEM Streams), the 9 second drainage basin. The higher level catchment membership of each of these sub-catchments is derived from its NCB code.

Processing steps:

1. ANUDEM v1.1.4 National Catchment Boundaries (NCBs) dataset is received and loaded into the Geofabric development GIS environment.

2. feature classes from ANUDEM NCBs are recomposed into composited Geofabric Framework Dataset feature classes in the Geofabric Maintenance Geodatabase.

3. re-composited feature classes in the Geofabric Maintenance Geodatabase Feature Dataset are assigned unique Hydro-IDs using ESRI ArcHydro for Surface Water (ArcHydro: 1.4.0.180 and ApFramework: 3.1.0.84)

4. feature classes from the Geofabric Maintenance Geodatabase Feature Dataset are extracted and reassigned to the Geofabric Surface Catchment Feature Dataset within the Geofabric Surface Catchment Geodatabase.

A complete set of data mappings, from input source data to Geofabric Products, is included in the Geofabric Product Guide, Appendices.

Dataset Citation

Bureau of Meteorology (2011) Geofabric Surface Catchments - V2.1. Bioregional Assessment Source Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/ea1b6f6c-e8a3-4c78-a463-044c89857fc0.

This metadata refers to the 'Corine Land Cover Plus Backbone' (CLCplus Backbone), a spatially detailed, large-scale, Earth Observation-based land cover inventory which is produced by the Copernicus Land Monitoring Service (CLMS). The CLCplus Backbone vector is a land cover map that contains vector polygon geometries (minimum mapping unit: 0.5 ha; minimum mapping width: 20 m) and is based on Sentinel satellite time series and a combination of existing reference datasets for geometries containing transportation and hydrological networks. Each polygon represents aggregated landscape objects and contains their dominant land cover among the 18 basic land cover classes. See polygon class codes in the additional information section. In addition, polygons are enriched with land cover fractions from the CLCplus Backbone raster as well as aggregated attributes based on other CLMS and Copernicus products (e.g. topography).

CLCplus Backbone vector is an independent product and its thematic and geometric contents differ from CLCplus Backbone raster and Corine Land Cover.

The CLCplus Backbone vector is available for the 2018 reference year.

This aggregate national dataset identifies allotment polygons within BLM managed public lands. Allotment polygon features are derived from the pasture polygons.

This map service is a synthesis of the baseline characterization of kelp and shallow rock ecosystems inside and outside of several North Central Coast (NCC) MPAs at the time of their implementation. MPAs in the NCC study region (NCCSR) were implemented on May 1, 2010. Baseline characterizations were conducted by the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) between August and October of 2010 and 2011. Visual SCUBA surveys took place at sites within MPAs and at their associated reference sites (sites outside MPA) to establish quantitative baselines for measuring future MPA effects (i.e., changes in community structure due to MPA implementation). This particular map service focuses on PISCO's characterization of fish communities aimed at estimating fish densities and fish size distribution. Refer to the following link for specifics regarding PISCO's “fish survey design” and “fish sampling methodology”: https://piscoweb.org/kelp-forest-sampling-protocols.Surveys for baseline characterization of kelp forest communities focused on the following MPAs: Point Arena SMR; Sea Lion Cove SMCA; Saunders Reef SMCA; Del Mar SMR; Stewarts Point SMR/SMCA; and Salt Point SMCA. From Point Arena to Salt Point, 35 cells (fundamental sampling units) were sampled via fish transects (inside and outside of MPAs) using stratified sampling across shore and at various depths in the kelp forests (5m, 10m, 15m and 20m). Utilizing PISCO's GPS coordinates of the 35 study cells (points), and details from PISCO's methods (see link above), we created estimated footprints of the areas in which these transects were surveyed (the 35 fundamental sampling units). From there, we also estimated the aggregated site polygons (aggregate sampling units) that comprise either an MPA or an MPA reference site; this resulted in 12 new polygons that were representative of the kelp and shallow rock ecosystems surveyed by PISCO. Stewarts Point SMR and SMCA are combined in the survey summaries to make up one of the ‘aggregate sampling units’ and therefore those feature classes have 11 instead of 12 features.These estimated study areas (fundamental and aggregate sampling units) were then used to synthesize and represent PISCO's fish survey results into the following map service product. The map service is a conglomeration of fish density and fish length metrics for the regions most abundant rockfish and non-rockfish species. The original PISCO data set used to comprise this map service can be found and downloaded at the following Ocean Spaces link: http://oceanspaces.org/data/north-central-coast-pisco-surveys-fish-shallow-rocky-reefs-and-kelp-forest-habitats-2010-2011.The complete ESRI ArcMap project and source summary data can be downloaded at the following California Department of Fish and Wildlife link: ftp://ftp.wildlife.ca.gov/R7_MR/BIOLOGICAL/NCCSR_MPAbaseline_PISCOsubtidal_2010-2011.zip