A complete list of live websites using the d3-polygon technology, compiled through global website indexing conducted by WebTechSurvey.

Oregon's Transportation Planning Rule (TPR) mandates that regional and local jurisdictions develop transportation system projects to meet identified transportation needs over the 20-year life of the TSP. This dataset includes the portion of Portland's Transportation System Plan (TSP) project list most appropriately represented as polygons.-- Additional Information: Category: Transportation - Planning Purpose: Represent planned transportation projects. Update Frequency: As Needed-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=54618

This feature service view drives the search function for the Bird Migration Explorer specifically the search under Locations driving the lists of Conservation Sites Near Your Chosen Location and the Audubon Near Your Chosen Location.

A complete list of live websites using the tsparticles-shape-polygon technology, compiled through global website indexing conducted by WebTechSurvey.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. were derived from the NVC. NatureServe developed a preliminary list of potential vegetation types. These data were combined with existing plot data (Cully 2002) to derive an initial list of potential types. Additional data and information were gleaned from a field visit and incorporated into the final list of map units. Because of the park’s small size and the large amount of field data, the map units are equivalent to existing vegetation associations or local associations/descriptions (e.g., Prairie Dog Colony). In addition to vegetation type, vegetation structures were described using three attributes: height, coverage density, and coverage pattern. In addition to vegetation structure and context, a number of attributes for each polygon were stored in the associated table within the GIS database. Many of these attributes were derived from the photointerpretation; others were calculated or crosswalked from other classifications. Table 2.7.2 shows all of the attributes and their sources. Anderson Level 1 and 2 codes are also included (Anderson et al. 1976). These codes should allow for a more regional perspective on the vegetation types. Look-up tables for the names associated with the codes is included within the geodatabase and in Appendix D. The look-up tables contain all the NVC formation information as well as alliance names, unique IDs, and the ecological system codes (El_Code) for the associations. These El_Codes often represent a one-to-many relationship; that is, one association may be related to more than one ecological system. The NatureServe conservation status is included as a separate item. Finally, slope (degrees), aspect, and elevation were calculated for each polygon label point using a digital elevation model and an ArcView script. The slope figure will vary if one uses a TIN (triangulated irregular network) versus a GRID (grid-referenced information display) for the calculation (Jenness 2005). A grid was used for the slope figure in this dataset. Acres and hectares were calculated using XTools Pro for ArcGIS Desktop.

The dataset contains the names of all oceans and seas in the "Limits of Oceans and Seas" (IHO, 1953). An automatic algorithm gives an area centroid for each polygon (ocean or sea). The dataset consists of four columns. The first column contains the name of the ocean or sea, column 2 and 3 contain the position of each polygon point (latitude, longitude). Column 4 contains an area index. With this index a link to the polygons is possible.

This digital map database provides an areally continuous representation of the Quaternary surficial deposits of the San Francisco Bay region merged from the database files from Knudsen and others (2000) and Witter and others (2006). The more detailed mapping by Witter and others (2006) of the inner part of the region (compiled at a scale of 1:24,000), is given precedence over the less detailed mapping by Knudsen and others (2000) of the outer part of the area (compiled at a scale of 1:100,000). The Quaternary map database is accompanied by a list of the map-unit names represented by polygon identities, a digital map index of the 1:24,000-scale topographic quadrangles of the region, and a figure illustrating the contents of the database. The Quaternary map database includes line work and the identity of the Quaternary map units, but no further description of the map units or how they were mapped. Use of the database should thus be accompanied by consultation with the original reports, which describe the map units and mapping procedures: citation of this database should be accompanied by citation of those original reports. As with all such digital maps, use of this database should attend to the compilation scales involved and not try to extract spatial detail or accuracy beyond those limits. Database layers: SFBQuat-lns: Quaternary map database: unit boundaries and their attributes SFBQuat-pys: Quaternary map database: polygons and their attributes SFBIndex-lns: Boundaries of 7.5-minute quadrangles for the map area, distinguishing those that form boundaries of 15-minute and 30x60-minute quadrangles SFBIndex-pys: 7.5-minute quadrangles, and for those within map area, their names and the names of the 30x60-minute quadrangles that contain them. The liquefaction ratings presented in the original reports for the various Quaternary map units remain valid and can be assigned to the units in this database if desired, with ratings of Witter and others (2006) given precedence. Assembly of the Quaternary map database involved stripping out all the information from the source maps that dealt with liquefaction, a major component of the original reports, and adjusting line work at the common boundary between the two source maps to produce a nearly seamless spatial database. The common boundary between the two sources is retained. Mismatches remaining at that common boundary are of two types: (1) contrasts in the degree of subdivision of the deposits resulting from the different compilation scales, and (2) terminations of narrow bands of water and artificial fill and levees at quadrangle boundaries that resulted from differences in details shown on the 1:24,000-scale topographic maps used as a source of mapping information in the original reports. The illustrative figure accompanying the database shows the content of the database plotted at a scale of 1:275,000, with the different map units distinguished by color and the different types of lines distinguished by symbol and color. An index map in that figure shows the 165 7½-minute quadrangles covering the region and the areas of the two source maps. Knudsen, K.L., Sowers, J.M., Witter, R.C., Wentworth, C.M., Helley, E.J., Nicholson, R.S., Wright, H.M., and Brown, K.M., 2000, Preliminary maps of Quaternary deposits and liquefaction susceptibility, nine-county San Francisco Bay region, California: a digital database: U.S. Geological Survey Open File Report 00-444. http://pubs.usgs.gov/of/2000/of00-444/ Witter, R.C., Knudsen, K.L, Sowers, J.M., Wentworth, C.M., Koehler, R.D., Randolph, C. E., Brooks, S.K., and Gans, K.D., 2006, Maps of Quaternary Deposits and Liquefaction Susceptibility in the Central San Francisco Bay Region, California: U.S. Geological Survey Open-File Report 06-1037 (http://pubs.usgs.gov/of/2006/1037)

The LIST Cadastral Parcels is a spatial index of polygons forming Tasmania's Cadastral framework. These polygons have been formed from The LIST Boundary Segments and the layers of Authority Parcel, …Show full descriptionThe LIST Cadastral Parcels is a spatial index of polygons forming Tasmania's Cadastral framework. These polygons have been formed from The LIST Boundary Segments and the layers of Authority Parcel, Casement, Water areas and Private Parcel from The LIST Cadastral Area spatial table within the Cadastral Data Model. Private parcels will represent an entitlement in fee simple. These layers combine to form a single layer of non-overlapping polygons (with the exception of vertical strata titles and user roads) for the whole of Tasmania. Attributes of the Cadastral Parcels include the PID (Property Identifier) and Volume and Folio, which are the key identifiers to the VISTAS (Valuation Information System for Tasmania and TASFOL (Tasmanian Folio of the Register) systems. These systems hold attributes including property details, valuation, ownership, title and address which can be linked to the cadastral area through these identifiers.

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review),more » as well as here. The dataset is a collection of objects stored within an RDate file, stateWaterRightsHarmonized.RData. Each object either describes how one should interact with the other objects, or contains the harmonized water rights data. Here is each object described in detail: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. The column headers for each data frame are: waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. basinNum - The alpha-numeric identifier of the WMA the record belongs to. priorityDate - The priority date associated with the right. allocatedFlow - The maximum flow of the allocation in cubic feet per second (ft3s-1). source - Whether the right is for surface water or groundwater. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. rightsByState_surface: A list of the cleaned surface water rights collected from each state. See rightsByState_ground for more details on how the data is formatted. fullRightsRecs: A list of the combined groundwater and surface water records for each state. Essentially, these lists are the merging of rightsByState_ground and rightsByState_surface by state. See rightsByState_ground for more details on how the data is formatted. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page.« less

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.

This shapefile was constructed by combining crown TSR spatial data, information gathered from Rural Lands Protection Board (RLPB) rangers, and surveyed Conservation and Biodiversity data to compile a layer within 30 RLPB districts in NSW. The layer attempts to spatially reflect current TSRs as accurately as possible with conservation attributes for each one.

Dataset History

The initial process in production involved using the most up to date extract of TSR from the crown spatial layer as a base map, as this layer should reasonably accurately spatially reflect the location, size, and attributes of TSR in NSW. This crown spatial layer from which the TSR were extracted is maintained by the NSW Department of Lands. The TSR extract is comprised of approximately 25,000 polygons in the study area. These polygons were then attributed with names, IDs and other attributes from the Long Paddock (LP) points layer produced by the RLPB State Council, which contains approximately 4000 named reserves throughout the study area. This layer reflects the names and ID number by which the reserves were or are currently managed by the RLPB's. This layer was spatially joined with the TSR polygon layer by proximity to produce a polygon layer attributed with RLPB reserve names and ID numbers. This process was repeated for other small datasets in order to link data with the polygon layer and LP reserve names. The next and by far the most time consuming and laborious process in the project was transferring the data gathered from surveys undertaken with RLPB rangers about each reserve (location, spatial extent, name, currency conservation value and biodiversity). This spatial information was annotated on hard copy maps and referenced against the spatial join making manual edits where necessary. Edits were conducted manually as the reference information was only on hard copy paper maps. Any corrections were made to the merged layer to produce an accurate spatial reflection of the RLPB reserves by name and ID. This manual editing process composed the bulk of the time for layer production as all reserves in each RLPB district in the study area had to be checked manually. Any necessary changes had to then be made to correct the spatial location of the reserve and ensure the correct ID was assigned for attributing the conservation data. In approximately 80% of cases the spatial join was correct, although this figure would be less where long chains of TSR polygons exist. The majority of time was devoted to making the numerous additions that needed to be incorporated. A spreadsheet based on the LP point layer was attributed with the LP point \[OBJECTID\] in order to produce a unique reference for each reserve so that conservation and biodiversity value data could be attributed against each reserve in the spatial layer being produced. Any new reserves were allocated \[OBJECTID\] number both in the GIS and the spreadsheet in order to create this link. All relevant data was entered into the spreadsheet and then edited to a suitable level to be attached as an attribute table. Field names were chosen and appropriate an interpretable data formats each field. The completed spreadsheet was then linked to the shapefile to produce a polygon TSR spatial layer containing all available conservation and biodiversity information. Any additional attribute were either entered manually or obtained by merging with other layers. Attributes for the final layer were selected for usability by those wishing to query valuable Conservation Value (CV) data for each reserve, along with a number of administrative attributes for locating and querying certain aspects of each parcel. Constant error checking was conducted throughout the process to ensure minimal error being transferred to the production. This was done manually, and also by running numerous spatial and attribute based queries to identify potential errors in the spatial layer being produced. Follow up phone calls were made to the rangers to identify exact localities of reserves where polygons could not be allocated due to missing or ambiguous information. If precise location data was provided, polygons could be added in, either from other crown spatial layers or from cadastre. These polygons were also attributed with the lowest confindex rating, as their status as crown land is unknown or doubtful. In some cases existing GIS layers had been created for certain areas. Murray RLPB has data where 400+ polygons do not exist in the current crown TSR extract. According to the rangers interviewed it was determined the majority of these TSR exist. This data was incorporated in the TSR polygon by merging the two layers and then assigning attributes in the normal way, ie by being given a LP Name and ID and then updated from the marked up hard copy maps. In the confidence index these are given a rating of 1 (see confindex matrix) due to the unknown source of the data and no match with any other crown spatial data. A confidence index matrix (confindex) was produced in order to give the end user of the GIS product an idea as to how the data for each reserve was obtained, its purpose, and an indication to whether it is likely to be a current TSR. The higher the confindex, the more secure the user can be in the data. (See Confidence Index Matrix) This was necessary due to conflicting information from a number of datasets, usually the RLPB ranger (mark up on hard copy map) conflicting with the crown spatial data. If these conflicting reserves were to be deleted, this would lead to a large amount of information loss during the project. If additions were made without sufficient data to determine its crown status, currency, location, etc (which was not available in all cases) the end user may rely on data that has a low level of accuracy. The confindex was produced by determining the value of information and scoring it accordingly, compounding its value if data sources showed a correlation. Where an RLPB LP Name and ID point was not assigned to a polygon due to other points being in closer proximity these names and ID are effectively deleted from the polygon layer. In a number of cases this was correct due to land being revoked, relinquished and/or now freehold. In a number of cases where the TSR is thought to exist and a polygon could not be assigned due to no info available (Lot/DP, close proximity to a crown reserve, further ranger interview provided no info, etc etc). For these cases to ensure no information loss a points layer was compiled from the LP points layer with further info from the marked up hard copy maps to place the point in the most accurate approximate location to where the reserve is though to exist and then all CV data attached to the point. In many of these cases some further investigation could provide an exact location and inclusion in the TSR poly layer. The accuracy of the point is mentioned in the metadata, so that the location is not taken as an absolute location and is only to be used as a guide for the approximate location of the reserve. Topology checks were conducted to eliminate slivers in the layer and to remove duplicate polygons. Where two crown reserves existed on the same land parcel, the duplicate polygon was deleted and unique attributes (Crown Reserve Number, Type, and Purpose) were transferred. Once the polygon layer was satisfactorily completed, a list of the LP points not allocated to polygons was compiled. Any points (reserves) that were said to have been revoked or relinquished were then removed from this list to provide a list of those that are said to be current. An extract of the LP points layer was then produced with only the aforementioned points. These points were then attributed with the same conservation and biodiversity data as the polygon layer, in an attempt to minimise the amount of information loss.

Dataset Citation

"NSW Department of Environment, Climate Change and Water" (2010) Travelling Stock Route Conservation Values. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/198900d5-0d06-4bd0-832b-e30a7c4e8873.

Overview The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.4 (published 24 February 2025). The 11.4 release contains updated boundary lines and data refinements designed to extend the functionality of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control. National Geospatial Data Asset This dataset is a National Geospatial Data Asset (NGDAID 194) managed by the Department of State. It is a part of the International Boundaries Theme created by the Federal Geographic Data Committee. Dataset Source Details Sources for these data include treaties, relevant maps, and data from boundary commissions, as well as national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process includes analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground. Cartographic Visualization The LSIB is a geospatial dataset that, when used for cartographic purposes, requires additional styling. The LSIB download package contains example style files for commonly used software applications. The attribute table also contains embedded information to guide the cartographic representation. Additional discussion of these considerations can be found in the Use of Core Attributes in Cartographic Visualization section below. Additional cartographic information pertaining to the depiction and description of international boundaries or areas of special sovereignty can be found in Guidance Bulletins published by the Office of the Geographer and Global Issues: https://data.geodata.state.gov/guidance/index.html Contact Direct inquiries to internationalboundaries@state.gov. Direct download: https://data.geodata.state.gov/LSIB.zip Attribute Structure The dataset uses the following attributes divided into two categories: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | Core CC1_GENC3 | Extension CC1_WPID | Extension COUNTRY1 | Core CC2 | Core CC2_GENC3 | Extension CC2_WPID | Extension COUNTRY2 | Core RANK | Core LABEL | Core STATUS | Core NOTES | Core LSIB_ID | Extension ANTECIDS | Extension PREVIDS | Extension PARENTID | Extension PARENTSEG | Extension These attributes have external data sources that update separately from the LSIB: ATTRIBUTE NAME | ATTRIBUTE STATUS CC1 | GENC CC1_GENC3 | GENC CC1_WPID | World Polygons COUNTRY1 | DoS Lists CC2 | GENC CC2_GENC3 | GENC CC2_WPID | World Polygons COUNTRY2 | DoS Lists LSIB_ID | BASE ANTECIDS | BASE PREVIDS | BASE PARENTID | BASE PARENTSEG | BASE The core attributes listed above describe the boundary lines contained within the LSIB dataset. Removal of core attributes from the dataset will change the meaning of the lines. An attribute status of “Extension” represents a field containing data interoperability information. Other attributes not listed above include “FID”, “Shape_length” and “Shape.” These are components of the shapefile format and do not form an intrinsic part of the LSIB. Core Attributes The eight core attributes listed above contain unique information which, when combined with the line geometry, comprise the LSIB dataset. These Core Attributes are further divided into Country Code and Name Fields and Descriptive Fields. County Code and Country Name Fields “CC1” and “CC2” fields are machine readable fields that contain political entity codes. These are two-character codes derived from the Geopolitical Entities, Names, and Codes Standard (GENC), Edition 3 Update 18. “CC1_GENC3” and “CC2_GENC3” fields contain the corresponding three-character GENC codes and are extension attributes discussed below. The codes “Q2” or “QX2” denote a line in the LSIB representing a boundary associated with areas not contained within the GENC standard. The “COUNTRY1” and “COUNTRY2” fields contain the names of corresponding political entities. These fields contain names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the ‘"Independent States in the World" and "Dependencies and Areas of Special Sovereignty" lists maintained by the Department of State. To ensure maximum compatibility, names are presented without diacritics and certain names are rendered using common cartographic abbreviations. Names for lines associated with the code "Q2" are descriptive and not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS denote independent states. Names rendered in normal text represent dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user. Descriptive Fields The following text fields are a part of the core attributes of the LSIB dataset and do not update from external sources. They provide additional information about each of the lines and are as follows: ATTRIBUTE NAME | CONTAINS NULLS RANK | No STATUS | No LABEL | Yes NOTES | Yes Neither the "RANK" nor "STATUS" fields contain null values; the "LABEL" and "NOTES" fields do. The "RANK" field is a numeric expression of the "STATUS" field. Combined with the line geometry, these fields encode the views of the United States Government on the political status of the boundary line. ATTRIBUTE NAME | | VALUE | RANK | 1 | 2 | 3 STATUS | International Boundary | Other Line of International Separation | Special Line A value of “1” in the “RANK” field corresponds to an "International Boundary" value in the “STATUS” field. Values of ”2” and “3” correspond to “Other Line of International Separation” and “Special Line,” respectively. The “LABEL” field contains required text to describe the line segment on all finished cartographic products, including but not limited to print and interactive maps. The “NOTES” field contains an explanation of special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, limitations regarding the purpose of the lines, or the original source of the line. Use of Core Attributes in Cartographic Visualization Several of the Core Attributes provide information required for the proper cartographic representation of the LSIB dataset. The cartographic usage of the LSIB requires a visual differentiation between the three categories of boundary lines. Specifically, this differentiation must be between: International Boundaries (Rank 1); Other Lines of International Separation (Rank 2); and Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Please consult the style files in the download package for examples of this depiction. The requirement to incorporate the contents of the "LABEL" field on cartographic products is scale dependent. If a label is legible at the scale of a given static product, a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field contains the preferred description for the three LSIB line types when they are incorporated into a map legend but is otherwise not to be used for labeling. Use of the “CC1,” “CC1_GENC3,” “CC2,” “CC2_GENC3,” “RANK,” or “NOTES” fields for cartographic labeling purposes is prohibited. Extension Attributes Certain elements of the attributes within the LSIB dataset extend data functionality to make the data more interoperable or to provide clearer linkages to other datasets. The fields “CC1_GENC3” and “CC2_GENC” contain the corresponding three-character GENC code to the “CC1” and “CC2” attributes. The code “QX2” is the three-character counterpart of the code “Q2,” which denotes a line in the LSIB representing a boundary associated with a geographic area not contained within the GENC standard. To allow for linkage between individual lines in the LSIB and World Polygons dataset, the “CC1_WPID” and “CC2_WPID” fields contain a Universally Unique Identifier (UUID), version 4, which provides a stable description of each geographic entity in a boundary pair relationship. Each UUID corresponds to a geographic entity listed in the World Polygons dataset. These fields allow for linkage between individual lines in the LSIB and the overall World Polygons dataset. Five additional fields in the LSIB expand on the UUID concept and either describe features that have changed across space and time or indicate relationships between previous versions of the feature. The “LSIB_ID” attribute is a UUID value that defines a specific instance of a feature. Any change to the feature in a lineset requires a new “LSIB_ID.” The “ANTECIDS,” or antecedent ID, is a UUID that references line geometries from which a given line is descended in time. It is used when there is a feature that is entirely new, not when there is a new version of a previous feature. This is generally used to reference countries that have dissolved. The “PREVIDS,” or Previous ID, is a UUID field that contains old versions of a line. This is an additive field, that houses all Previous IDs. A new version of a feature is defined by any change to the

This parcels polygons feature class represents current city parcels within the City of Los Angeles. It shares topology with the Landbase parcel lines feature class. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most current geographic information of the public right of way, ownership and land record information. The legal boundaries are determined on the ground by license surveyors in the State of California, and by recorded documents from the Los Angeles County Recorder's office and the City Clerk's office of the City of Los Angeles. Parcel and ownership information are available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works.Associated information about the landbase parcels is entered into attributes. Principal attributes include:PIN and PIND: represents the unique auto-generated parcel identifier and key to related features and tables. This field is related to the LA_LEGAL, LA_APN and LA_HSE_NBR tables. PIN contains spaces and PIND replaces those spaces with a dash (-).LA_LEGAL - Table attributes containing legal description. Principal attributes include the following:TRACT: The subdivision tract number as recorded by the County of Los AngelesMAP_REF: Identifies the subdivision map book reference as recorded by the County of Los Angeles.LOT: The subdivision lot number as recorded by the County of Los Angeles.ENG_DIST: The four engineering Districts (W=Westla, C=Central, V= Valley and H=Harbor).CNCL_DIST: Council Districts 1-15 of the City of Los Angeles. OUTLA means parcel is outside the City.LA_APN- Table attributes containing County of Los Angeles Assessors information. Principal attributes include the following:BPP: The Book, Page and Parcel from the Los Angeles County Assessors office. SITUS*: Address for the property.LA_HSE_NBR - Table attributes containing housenumber information. Principal attributes include the following:HSE_ID: Unique id of each housenumber record.HSE_NBR: housenumber numerical valueSTR_*: Official housenumber addressFor a complete list of attribute values, please refer to Landbase_parcel_polygons_data_dictionary.Landbase parcels polygons data layer was created in geographical information systems (GIS) software to display the location of the right of way. The parcels polygons layer delineates the right of way from Landbase parcels lots. The parcels polygons layer is a feature class in the LACityLandbaseData.gdb Geodatabase dataset. The layer consists of spatial data as a polygon feature class and attribute data for the features. The area inside a polygon feature is a parcel lot. The area outside of the parcel polygon feature is the right of way. Several polygon features are adjacent, sharing one line between two polygons. For each parcel, there is a unique identifier in the PIND and PIN fields. The only difference is PIND has a dash and PIN does not. The types of edits include new subdivisions and lot cuts. Associated legal information about the landbase parcels lots is entered into attributes. The landbase parcels layer is vital to other City of LA Departments, by supporting property and land record operations and identifying legal information for City of Los Angeles. The landbase parcels polygons are inherited from a database originally created by the City's Survey and Mapping Division. Parcel information should only be added to the Landbase Parcels layer if documentation exists, such as a Deed or a Plan approved by the City Council. When seeking the definitive description of real property, consult the recorded Deed or Plan.List of Fields:ID: A unique numeric identifier of the polygon. The ID value is the last part of the PIN field value.ASSETID: User-defined feature autonumber.MAPSHEET: The alpha-numeric mapsheet number, which refers to a valid B-map or A-map number on the Cadastral grid index map. Values: • B, A, -5A - Any of these alpha-numeric combinations are used, whereas the underlined spaces are the numbers. An A-map is the smallest grid in the index map and is used when there is a large amount of spatial information in the map display. There are more parcel lines and annotation than can fit in the B-map, and thus, an A-map is used. There are 4 A-maps in a B-map. In areas where parcel lines and annotation can fit comfortably in an index map, a B-map is used. The B-maps are at a scale of 100 feet, and A-maps are at a scale of 50 feet.OBJECTID: Internal feature number.BPPMAP_REFTRACTBLOCKMODLOTARBCNCL_DIST: LA City Council District. Values: • (numbers 1-15) - Current City Council Member for that District can be found on the mapping website http://navigatela.lacity.org/navigatela, click Council Districts layer name, under Boundaries layer group.SHAPE: Feature geometry.BOOKPAGEPARCELPIND: The value is a combination of MAPSHEET and ID fields, creating a unique value for each parcel. The D in the field name PIND, means "dash", and there is a dash between the MAPSHEET and ID field values. This is a key attribute of the LANDBASE data layer. This field is related to the APN and HSE_NBR tables.ENG_DIST: LA City Engineering District. The boundaries are displayed in the Engineering Districts index map. Values: • H - Harbor Engineering District. • C - Central Engineering District. • V - Valley Engineering District. • W - West LA Engineering District.PIN: The value is a combination of MAPSHEET and ID fields, creating a unique value for each parcel. There are spaces between the MAPSHEET and ID field values. This is a key attribute of the LANDBASE data layer. This field is related to the APN and HSE_NBR tables.

Techical Information: This dataset is the digitized version of the printed 'Limits of Oceans and Seas '(IHO, 1953). The report describes the boundaries of 148 oceans and seas. The given positions were typed into a spreadsheet and were completed to a right ordered polygon by hand using Google Earth. The dataset consists of five columns. The first column contains the name of the ocean or sea, column 2 and 3 contain the position of each polygon point (latitude, longitude). Column 4 contains an area index, column 5 a polygon index. These two indices structurize the dataset.The other version link provides a Google Earth layer in KML format (zipped). This layer consists of all polygons and names of oceans or seas at area centroid position given in dataset doi:10.1594/PANGAEA.777976.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The vegetation classification and mapping processes were conducted essentially in tandem. Mappers and ecologists conferred to review the list of potential associations, as well as the appropriate scale for mapping. Photos were viewed in stereo and preliminary polygon boundaries were delineated with a .30-mm rapidograph pen on polypropylene sleeves placed over the aerial photos. Preliminary polygons were classified and labeled with their appropriate USNVC association using the aerial photograph interpretation key and USNVC descriptions, and by conferring with NatureServe ecologists. The initial line work was also used to determine a sampling scheme for plot and observation data collection, and the USNVC association list resulting from the field work was used to aid polygon classification. Once delineations were groundtruthed and rectified, USNVC association-level polygon line work was transferred to GIS shapefiles via onscreen digitizing in ArcView v.3.2a (ESRI 1992–2000). USNVC association and Anderson Level II (modified) land use names and codes were added to the attribute table of the vegetation shapefile. A separate wetland map for the park was created from the vegetation map polygons belonging to the Saturated Cold-deciduous Forest and Saturated Temperate Perennial Forb Vegetation formations.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The map units assigned to the delineated polygons on the aerial photographs were derived from the preliminary list of NVC types provided by NatureServe. Additional data and information were gleaned from a field visit and incorporated into the final list of map units. Because of the small size of HUTR and the large amount of field data, the map units are equivalent to existing NVC vegetation alliances and associations or local associations/descriptions. Four attributes were associated with each polygon: (1) map unit, (2) height, (3) density, and (4) coverage pattern of the vegetation.

The LIST Cadastral Parcels is a spatial index of polygons forming Tasmania's Cadastral framework. These polygons have been formed from The LIST Boundary Segments and the layers of Authority Parcel, Casement, Water areas and Private Parcel from The LIST Cadastral Area spatial table within the Cadastral Data Model.

Private parcels will represent an entitlement in fee simple. These layers combine to form a single layer of non-overlapping polygons (with the exception of vertical strata titles and user roads) for the whole of Tasmania.

Attributes of the Cadastral Parcels include the PID (Property Identifier) and Volume and Folio, which are the key identifiers to the VISTAS (Valuation Information System for Tasmania and TASFOL (Tasmanian Folio of the Register) systems. These systems hold attributes including property details, valuation, ownership, title and address which can be linked to the cadastral area through these identifiers.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Polygon boundary edits were transferred from the paper maps used in the field to the digital shapefiles each week using ArcMap GIS software. Field edits were also transferred to a set of master paper maps that did not go into the field; these will be archived along with the datasheets. The polygons were contained in a field geodatabase structure (.mdb), enabling topography rules and relationships to be established. The geodatabase was archived each week to ensure no loss of data and to allow for reversion or retrieval if needed. Strict nomenclature was enforced for polygons, and a unique name was assigned to each polygon. The names reflected the verified physiognomic formation type by a prefix of representative letters (W = Woodland, SS = shrub savanna, etc.) followed by a number. In the final map, there are 16 vegetation alliances or associations attributed to 74 polygons (Figure 2-3). For each, there is a oneto- one correlation between the alliance or association and map units (polygons). Table 2-3 shows each vegetation community type, the number of polygons attributed with that type, and the total area.

The polygon data in the geodatabase represent range-wide habitat suitability model predictions for five species of herpetofauna: gopher tortoise (Gopherus polyphemus), southern hognose snake (Heterodon simus), Florida pine snake (Pituophis melanoleucus mugitus), gopher frog (Lithobates capito), and striped newt (Notophthalmus perstriatus). Collectively, the habitat suitability polygon layers extend across the range of these species in the Southeast US, including areas in Louisiana, Mississippi, Alabama, Florida, Georgia, South Carolina, and North Carolina. This assessment was conducted by the USGS Cooperative Fish & Wildlife Research Unit at the University of Georgia in collaboration with other partners. Habitat suitability models were developed to 1) identify habitat features that best predict species presence and 2) estimate the amount and distribution of suitable habitat across each species’ range under current conditions. Habitat suitability models were created using comprehensive datasets of species occurrence records maintained by natural heritage programs, U.S. Fish & Wildlife Service (USFWS), U.S. Forest Service (USFS), U.S. Department of Defense (DoD), State agencies, academic researchers, and HerpMapper.org. Each species' final model included between four and nine predictors representing geospatial datasets of landscape attributes that were publicly available from various sources. These predictors included soil drainage from gridded SSURGO (raster) data from NRCS, land cover classification and canopy cover data from the National Land Cover Dataset (NLCD), fire frequency from the National Aeronautics and Space Administration MODIS data of annual fire detections and U.S. Department of Agriculture Forest Service and U.S. Department of the Interior LANDFIRE fuel disturbance data, compatible wetlands classified from USGS National Wetland Inventory database, climate data using 30-year (1981-2010) averages from the University of Idaho Gridded Surface Meteorological Data, and local relative elevation using the USGS Digital Elevation Model (DEM). The resulting layers represent all areas within species' ranges with low, medium, and high predicted habitat suitability, based on predicted Habitat Suitability Index that could range from 0 (least suitable for the species) to 1 (most suitable). The set of habitat suitability layers are named using five letter codes based on the species name (e.g., Gopherus polyphemus = GOPOL). For layers with "100" at the end of their database names, only polygons of large areas (> 1 square-km) are included in the polygon layer. Finally, the geodatabase includes a layer whose value indicates the number of species out of five for which the area was predicted to be suitable (named "HSI_all_overlap100", see accompanying publication). Habitat suitability for all species was strongly influenced by soil characteristics, land cover, and fire interval. Suitable habitat was distributed on known species strongholds, as well as private lands without known species records. A full discussion of the compilation methodology and sources used to develop the habitat suitability data is available in the accompanying publication: Crawford, B.A., J.C. Maerz, & C.T. Moore. 2019. Expert-informed habitat suitability analysis for at-risk species assessment and conservation planning. Journal of Fish and Wildlife Management. in review.

The Geomark datasets are spatial reference files that describe the feature, its location and its name. Examples of the types of features included in these datasets are: rivers, water bodies, railway lines, parks, airports, hospitals, education centres, emergency facilities, sport facilities, mountains, transport infrastructure, power facilities and community venues (but not road names). The data contained within the individual Geomark datasets has been sourced from Vicmap Elevation, Vicmap Hydro, Vicmap Features of Interest and Vicmap Transport. The difference between the features in these Vicmap datasets and Geomark is that the Geomark features have been combined to create one piece of geometry based on its name and type.\r GEOMARK_POINT : A statewide point dataset containing information for “named” or “could be named” features. Points represent relatively small area features that have been generalised or larger features where the spatial source is a coordinate or an address. Examples of small area point entities include wind turbines, snow poles, and emergency markers.\r GEOMARK_LINE : A statewide line dataset containing information for “named” or “could be named” features. Linear features include rivers, power lines, chairlifts and pipelines among others.\r GEOMARK_POLYGON : A statewide polygon dataset containing information for “named” or “could be named” features. Polygons represent larger area features that have been captured in more detail. Examples include lakes, sports grounds, gardens, parks and shopping precincts.\r GEOMARK_INDEX_CENTROID : A statewide centroid dataset holding one centroid record for each feature (unique feature id) held within the Geomark Index Extent table. \r GEOMARK_INDEX_EXTENT : A statewide polygon dataset holding one polygon or multi part polygon record for each feature (unique feature id) held within the Geomark Point, Line and Polygon tables. Note: point and line features are represented as polygons.