This style comprises 20 distinct hues, plus a white version, of the firefly symbol family for points, lines, and polygons.Points have two flavors of symbols. One is a standard radial opacity decay with a molten white core. The other is a variant with a shimmer effect, if that's what you need.Line symbols are available in solid or dashed. Lines are a stack of colorized semitransparent strokes beneath a white stroke, to create a glow effect.Polygons are also available in two versions. One version applies the glow to the perimeter of the polygon in both inner and outer directions, with a semi-transparent fill. This is effective for non-adjacent polygons. The alternate version only applies an inner glow, to prevent blending and overlapping of adjacent polygons.This is an early version of these symbols and only the points respond to color selection.Learn how to install this style by visiting this salacious blog post.Learn more about Firefly Cartography here.Happy Firefly Mapping! John

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.

Download In State Plane Projection Here. Landmark (Facility Site) point and polygons utilize the Esri Local Government Information model to structure the attribute data. Polygon features are mapped by tax parcel with updates occurring on a weekly basis as either parcel or feature changes are detected.

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

recsite_pub_poly_point: On small-scale maps the generally small polygons of RECSITE_POLY are not easily seen. Centroid points are automatically generated from RECSITE_POLY and stored in the feature class RECSITE_POLY_POINT

“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.

Geodetic Control Points. The dataset contains polygons representing planimetric geodetic control points, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO). These features were originally captured in 1999 and updated in 2005, 2008, and 2010. The following planimetric layers were updated: - Building Polygons (BldgPly) - Bridge and Tunnel Polygons (BrgTunPly) - Horizontal and Vertical Control Points (GeoControlPt) - Obscured Area Polygons (ObsAreaPly) - Railroad Lines (RailRdLn) - Road, Parking, and Driveway Polygons (RoadPly) - Sidewalk Polygons (SidewalkPly) - Wooded Areas (WoodPly) Two new layers were added: - Basketball and Other Recreation Courts (RecCourtPly) - Wheelchair Ramps (TransMiscPt).

November 2025 will be the last update to the Public Safety ArcGIS Pro Style 2.x.Esri has developed a modern set of cartographic symbols for emergency management, fire service, and law enforcement agencies. They relate to damage assessment, debris reporting, preparedness, response activities, etc. These symbols are designed to be used in ArcGIS Pro. The style includes point, line, polygon, and text symbols, as well as colors and color schemes. This style is compatible with the most recent released version of ArcGIS Pro. You can view a PDF of the symbols here.This style is not compatible with ArcGIS Pro 1.x version.3.x version of this style can be downloaded here.

This resource contains the test data for the GeoServer OGC Web Services tutorials for various GIS applications including ArcGIS Pro, ArcMap, ArcGIS Story Maps, and QGIS. The contents of the data include a polygon shapefile, a polyline shapefile, a point shapefile, and a raster dataset; all of which pertain to the state of Utah, USA. The polygon shapefile is of every county in the state of Utah. The polyline is of every trail in the state of Utah. The point shapefile is the current list of GNIS place names in the state of Utah. The raster dataset covers a region in the center of the state of Utah. All datasets are projected to NAD 1983 Zone 12N.

WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:

• Metadata is missing or incomplete for some layers at this time and will be continuously improved.
  
• We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.

Purpose

County and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, the coastline is used to separate coastal buffers from the land-based portions of jurisdictions. This feature layer is for public use.

Related Layers

This dataset is part of a grouping of many datasets:

1. Cities: Only the city boundaries and attributes, without any unincorporated areas
   • With Coastal Buffers
   • Without Coastal Buffers
2. Counties: Full county boundaries and attributes, including all cities within as a single polygon
   • With Coastal Buffers
   • Without Coastal Buffers
3. Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.
   • With Coastal Buffers (this dataset)
   • Without Coastal Buffers
4. Place Abbreviations
5. Unincorporated Areas (Coming Soon)
6. Census Designated Places (Coming Soon)
   
7. Cartographic Coastline
   • Polygon
   • Line source (Coming Soon)

Point of Contact

California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov

Field and Abbreviation Definitions

• COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system
• Place Name: CDTFA incorporated (city) or county name
• County: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.
• Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
• GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
• GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information System
• Place Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area names
• CNTY Abbr: CalTrans Division of Local Assistance abbreviations of county names
• Area_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.
• COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".
• GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.

Accuracy

CDTFA"s source data notes the following about accuracy:

City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated

This item contains points of interest from OSM (OpenStreetMap) in India and contains information about bank, ATM, alpine hut, bakery etc.OSM is a collaborative, open project to create a freely available and editable map of the world. Geographic information about streets, rivers, borders, points of interest and areas are collected worldwide and stored in a freely accessible database. Everyone can participate and contribute to OSM. The geographic information available on OSM relies entirely on volunteers or contributors.The attributes are given below:Alpine HutArchaeologicalArts CentreArtworkATMAttractionBakeryBankBarBattlefieldBeauty ShopBenchBeveragesBicycle RentalBicycle ShopBiergartenBookshopButcherCafeCamera SurveillanceThese map layers are offered by Esri India Content. If you have any questions or comments, please let us know via content@esri.in.

Esri has developed a modern set of cartographic symbols for emergency management, fire service, and law enforcement agencies. They relate to damage assessment, debris reporting, preparedness, response activities, etc. These symbols are designed to be used in ArcGIS Pro.The style includes point, line, polygon, and text symbols, as well as colors and color schemes. This style is compatible with the most recent released version of ArcGIS Pro. You can view a PDF of the symbols here.This style is not compatible with ArcGIS Pro 1.x and 2.x versions.2.x version of this style can be downloaded here.

This style consists of two, and only two, symbols. One pin point symbol and one paper polygon symbol.But they can be dynamically colored in the symbology panel. Here's a one-minute how to.

This specialized location dataset delivers detailed information about marina establishments. Maritime industry professionals, coastal planners, and tourism researchers can leverage precise location insights to understand maritime infrastructure, analyze recreational boating landscapes, and develop targeted strategies.

How Do We Create Polygons?

-All our polygons are manually crafted using advanced GIS tools like QGIS, ArcGIS, and similar applications. This involves leveraging aerial imagery, satellite data, and street-level views to ensure precision. -Beyond visual data, our expert GIS data engineers integrate venue layout/elevation plans sourced from official company websites to construct highly detailed polygons. This meticulous process ensures maximum accuracy and consistency. -We verify our polygons through multiple quality assurance checks, focusing on accuracy, relevance, and completeness.

What's More?

-Custom Polygon Creation: Our team can build polygons for any location or category based on your requirements. Whether it’s a new retail chain, transportation hub, or niche point of interest, we’ve got you covered. -Enhanced Customization: In addition to polygons, we capture critical details such as entry and exit points, parking areas, and adjacent pathways, adding greater context to your geospatial data. -Flexible Data Delivery Formats: We provide datasets in industry-standard GIS formats like WKT, GeoJSON, Shapefile, and GDB, making them compatible with various systems and tools. -Regular Data Updates: Stay ahead with our customizable refresh schedules, ensuring your polygon data is always up-to-date for evolving business needs.

Unlock the Power of POI and Geospatial Data

With our robust polygon datasets and point-of-interest data, you can: -Perform detailed market and location analyses to identify growth opportunities. -Pinpoint the ideal locations for your next store or business expansion. -Decode consumer behavior patterns using geospatial insights. -Execute location-based marketing campaigns for better ROI. -Gain an edge over competitors by leveraging geofencing and spatial intelligence.

Why Choose LocationsXYZ?

LocationsXYZ is trusted by leading brands to unlock actionable business insights with our accurate and comprehensive spatial data solutions. Join our growing network of successful clients who have scaled their operations with precise polygon and POI datasets. Request your free sample today and explore how we can help accelerate your business growth.

This style contains a generic set of 2D and 3D symbols which are used in the ArcGIS Explorer application. It includes point symbols, line symbols, and polygon symbols. Point symbols are designed from picture markers. Categories include transportation, civic, points of interest, weather, pins, recreation, and marine. Symbol names, categories, tags, and keys are in Italian.

A compilation of bedrock outcrops as points and/or polygons from 1:62,500 and 1:24,000 geologic mapping by the Vermont Geological Survey, the United States Geological Survey, and local colleges and universities between 1950-2016.Data was included as points or polygons based the source data.Includes data from VGS Open File Reports, VGS Bulletins, USGS reports, digitized 1:62,500 surficial and bedrock maps, student MS and PhD theses, and some unpublished data.For each point or polygon the NAD 1983 UTM Zone 18N X and Y coordinates are included (for polygons it is the X and Y coordinates of the centroid).A reference and publication year are included when possible.Compiled in January, 2017.

(Link to Metadata) RF 5000 NAD83 orthophoto edge lines (4000 x 4000 meter grid cells) were generated automatically from the known corner locations (generated by Gary Smith). Corner tics were added by VCGI. Nodes-intersections at the corner of each ortho tile (polygon) was converted into a point data layer. The Arc/Info NEAR command was then used to transfer tic IDs from the ORTHO data layer to this data layer. These points were then converted to tics and appended to this coverage. These corners apply to only to NAD83 orthophotos (digital and hardcopy). The corners of digital orthophotos DO NOT precisely match the older corners/boundaries in the BoundaryTile_ORTHO27 data layer. Corners and boundaries have been shifted on the X-axis (easting) by approximately 135 meters to the west, and 8 meters in the Y-axis (northing) . Please refer to BoundaryTile_ORTHO27 data layer documentation for additional information. The corner tic IDs and IDTIC attributes contain the same numbering scheme used in the BoundaryTile_ORTHO27 coverage (even though corners and boundaries are not the same). These tics can be used to digitize NAD83 orthophotos . The BoundaryTile_ORTHO27 data layer should be used when digitizing from NAD27 orthophotos. The ORTHO data layer should NOT be used for digitizing.

Esri has developed a modern set of cartographic symbols for land records, public works, fire service, law enforcement, planning and development, elections, health and human services, fish and wildlife, agriculture, natural resources, and economic development. These symbols are designed to be used in ArcGIS Pro.The style includes point, line, polygon, and text symbols, as well as colors and color schemes. This style is compatible with the most recent released version of ArcGIS Pro. You can view a PDF of the symbols here.This style is not compatible with ArcGIS Pro 1.x version.3.x version of this style can be downloaded here.

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. We converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

Watercolor maps are beautiful. Maps made in ArcGIS Pro can use a watercolor style to look realistically watercolory. Therefore, according to the transitive property, we can say that these maps may be beautiful.There are many utilities for a style like this. Mapping local parks and communities, creating your own vector basemaps, transforming digital features into plausibly tangible art, or just getting inspired by the combined wonder of geography and texture.Here are some example swatches of the point, line, and polygon styles available herein.Here are a couple examples of their use in Pro:Happy watercoloring! John Nelson

Summary This feature class documents the fire history on CMR from 1964 - present. This is 1 of 2 feature classes, a polygon and a point. This data has a variety of different origins which leads to differing quality of data. Within the polygon feature class, this contains perimeters that were mapped using a GPS, hand digitized, on-screen digitized, and buffered circles to the estimated acreage. These 2 files should be kept together. Within the point feature class, fires with only a location of latitude/longitude, UTM coordinate, TRS and no estimated acreage were mapped using a point location. GPS started being used in 1992 when the technology became available. Records from FMIS (Fire Management Information System) were reviewed and compared to refuge records. Polygon data in FMIS only occurs from 2012 to current and many acreage estimates did not match. This dataset includes ALL fires no matter the size. This feature class documents the fire history on CMR from 1964 - present. This is 1 of 2 feature classes, a polygon and a point. This data has a variety of different origins which leads to differing quality of data. Within the polygon feature class, this contains perimeters that were mapped using a GPS, hand digitized, on-screen digitized, and buffered circles to the estimated acreage. These 2 files should be kept together. Within the point feature class, fires with only a location of latitude/longitude, UTM coordinate, TRS and no estimated acreage were mapped using a point location. GPS started being used in 1992 when the technology became available. Data origins include: Data origins include: 1) GPS Polygon-data (Best), 2) GPS Lat/Long or UTM, 3)TRS QS, 4)TRS Point, 6)Hand digitized from topo map, 7) Circle buffer, 8)Screen digitized, 9) FMIS Lat/Long. Started compiling fire history of CMR in 2007. This has been a 10 year process.FMIS doesn't include fires polygons that are less than 10 acres. This dataset has been sent to FMIS for FMIS records to be updated with correct information. The spreadsheet contains 10-15 records without spatial information and weren't included in either feature class. Fire information from 1964 - 1980 came from records Larry Eichhorn, BLM, provided to CMR staff. Mike Granger, CMR Fire Management Officer, tracked fires on an 11x17 legal pad and all this information was brought into Excel and ArcGIS. Frequently, other information about the fires were missing which made it difficult to back track and fill in missing data. Time was spent verifiying locations that were occasionally recorded incorrectly (DMS vs DD) and converting TRS into Lat/Long and/or UTM. CMR is divided into 2 different UTM zones, zone 12 and zone 13. This occasionally caused errors in projecting. Naming conventions caused confusion. Fires are frequently names by location and there are several "Soda Creek", "Rock Creek", etc fires. Fire numbers were occasionally missing or incorrect. Fires on BLM were included if they were "Assists". Also, fires on satellite refuges and the district were also included. Acreages from GIS were compared to FMIS acres. Please see documentation in ServCat (URL) to see how these were handled.