The ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) Project Package includes all of the layers that are in the NTIA Permitting and Environmental Information Application as well as the APPEIT Tool which will allow users to input a project area and determine what layers from the application overlap with it. An overview of the project package and the APPEIT tool is provided below. User instructions on how to use the tool are available here. Instructions now include how to customize the tool by adding your own data. A video explaining how to use the Project Package is also available here. Project Package OverviewThis map package includes all of the layers from the NTIA Permitting and Environmental Information Application. The layers included are all feature services from various Federal and State agencies. The map package was created with ArcGIS Pro 3.4.0. The map package was created to allow users easy access to all feature services including symbology. The map package will allow users to avoid downloading datasets individually and easily incorporate into their own GIS system. The map package includes three maps.1. Permitting and Environmental Information Application Layers for GIS Analysis - This map includes all of the map tabs shown in the application, except State Data which is provided in another tab. This map includes feature services that can be used for analysis with other project layers such as a route or project area. 2. Permitting and Environmental Information Application Layers – For Reference Only - This map includes layers that cannot be used for analysis since they are either imagery or tile layers.3. State Data - Reference Only - This map includes all relevant state data that is shown in the application.The NTIA Permitting and Environmental Information Application was created to help with your permitting planning and environmental review preparation efforts by providing access to multiple maps from publicly available sources, including federal review, permitting, and resource agencies. The application should be used for informational purposes only and is intended solely to assist users with preliminary identification of areas that may require permits or planning to avoid potentially significant impacts to environmental resources subject to the National Environmental Policy Act (NEPA) and other statutory requirements. Multiple maps are provided in the application which are created from public sources. This application does not have an exhaustive list of everything you need for permitting or environmental review for a project but is an initial starting point to see what might be required.APPEIT Tool OverviewThe Department of Commerce’s National Telecommunications and Information Administration (NTIA) is providing the ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) to help federal broadband grant recipients and subgrantees identify permits and environmental factors as they plan routes for their broadband deployments. Identifying permit requirements early, initiating pre-application coordination with permitting agencies, and avoiding environmental impacts help drive successful infrastructure projects. NTIA’s public release of the APPEIT tool supports government-wide efforts to improve permitting and explore how online and digital technologies can promote efficient environmental reviews. This Esri ArcGIS Pro tool is included in the map package and was created to support permitting, planning, and environmental review preparation efforts by providing access to data layers from publicly available sources, including federal review, permitting, and resource agencies. An SOP on how to use the tool is available here. For the full list of APPEIT layers, see Appendix Table 1 in the SOP. The tool is comprised of an ArcGIS Pro Project containing a custom ArcGIS Toolbox tool, linked web map shared by the NTIA’s National Broadband Map (NBAM), a report template, and a Tasks item to guide users through using the tool. This ArcGIS Pro project and its contents (maps and data) are consolidated into this (.ppkx) project file. To use APPEIT, users will input a project area boundary or project route line in a shapefile or feature class format. The tool will return as a CSV and PDF report that lists any federal layers from the ArcGIS Pro Permitting and Environmental Information Web Map that intersect the project. Users may only input a single project area or line at a time; multiple projects or project segments will need to be screened separately. For project route lines, users are required to specify a buffer distance. The buffer distance that is used for broadband projects should be determined by the area of anticipated impact and should generally not exceed 500 feet. For example, the State of Maryland recommends a 100-foot buffer for broadband permitting. The tool restricts buffers to two miles to ensure relevant results. DisclaimerThis document is intended solely to assist federal broadband grant recipients and subgrantees in better understanding Infrastructure Investment and Jobs Act (IIJA) broadband grant programs and the requirements set forth in the Notice of Funding Opportunity (NOFO) for this program. This document does not and is not intended to supersede, modify, or otherwise alter applicable statutory or regulatory requirements, the terms and conditions of the award, or the specific application requirements set forth in the NOFO. In all cases, statutory and regulatory mandates, the terms and conditions of the award, the requirements set forth in the NOFO, and follow-on policies and guidance, shall prevail over any inconsistencies contained in this document. NTIA’s ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) should be used for informational purposes only and is intended solely to assist users with preliminary identification of broadband deployments that may require permits or planning to avoid potentially significant impacts to environmental resources subject to the National Environmental Policy Act (NEPA) and other statutory requirements. The tool is not an exhaustive or complete resource and does not and is not intended to substitute for, supersede, modify, or otherwise alter any applicable statutory or regulatory requirements, or the specific application requirements set forth in any NTIA NOFO, Terms and Conditions, or Special Award Condition. In all cases, statutory and regulatory mandates, and the requirements set forth in NTIA grant documents, shall prevail over any inconsistencies contained in these templates. The tool relies on publicly available data available on the websites of other federal, state, local, and Tribal agencies, and in some instances, private organizations and research institutions. Layers identified with a double asterisk include information relevant to determining if an “extraordinary circumstance” may warrant more detailed environmental review when a categorical exclusion may otherwise apply. While NTIA continues to make amendments to its websites to comply with Section 508, NTIA cannot ensure Section 508 compliance of federal and non-federal websites or resources users may access from links on NTIA websites. All data is presented “as is,” “as available” for informational purposes. NTIA does not warrant the accuracy, adequacy, or completeness of this information and expressly disclaims liability for any errors or omissions. Please e-mail NTIAanalytics@ntia.gov with any questions.

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

This dataset contains 50-ft contours for the Hot Springs shallowest unit of the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric-surface shows altitude at which the water level would have risen in tightly-cased wells and represents synoptic conditions during the summer of 2017. Contours were constructed from 59 water-level measurements measured in selected wells (locations in the well point dataset). Major streams and creeks were selected in the study area from the USGS National Hydrography Dataset (U.S. Geological Survey, 2017), and the spring point dataset with 18 spring altitudes calculated from 10-meter digital elevation model (DEM) data (U.S. Geological Survey, 2015; U.S. Geological Survey, 2016). After collecting, processing, and plotting the data, a potentiometric surface was generated using the interpolation method Topo to Raster in ArcMap 10.5 (Esri, 2017a). This tool is specifically designed for the creation of digital elevation models and imposes constraints that ensure a connected drainage structure and a correct representation of the surface from the provided contour data (Esri, 2017a). Once the raster surface was created, 50-ft contour interval were generated using Contour (Spatial Analyst), a spatial analyst tool (available through ArcGIS 3D Analyst toolbox) that creates a line-feature class of contours (isolines) from the raster surface (Esri, 2017b). The Topo to Raster and contouring done by ArcMap 10.5 is a rapid way to interpolate data, but computer programs do not account for hydrologic connections between groundwater and surface water. For this reason, some contours were manually adjusted based on topographical influence, a comparison with the potentiometric surface of Kresse and Hays (2009), and data-point water-level altitudes to more accurately represent the potentiometric surface. Select References: Esri, 2017a, How Topo to Raster works—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/how-topo-to-raster-works.htm. Esri, 2017b, Contour—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro Raster Surface toolset at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/contour.htm. Kresse, T.M., and Hays, P.D., 2009, Geochemistry, Comparative Analysis, and Physical and Chemical Characteristics of the Thermal Waters East of Hot Springs National Park, Arkansas, 2006-09: U.S. Geological Survey 2009–5263, 48 p., accessed November 28, 2017, at https://pubs.usgs.gov/sir/2009/5263/. U.S. Geological Survey, 2015, USGS NED 1 arc-second n35w094 1 x 1 degree ArcGrid 2015, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html. U.S. Geological Survey, 2016, USGS NED 1 arc-second n35w093 1 x 1 degree ArcGrid 2016, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html.

Inspired by the book, Dirkzwager’s Guide to the New-Waterway, Rotterdam, Dordrecht, Europoort and Botlek for 1978, this style re-creates its crisp modernist colors balanced with charming hand-drawn landcover features and incorporates the tangible variability of print ink and aged paper.I was shown a wonderful example, provided by Eelco Berghuis, which was a gift from his grandfather.So I sampled colors and created fill and line symbol features with a print-like texture and bleed. When applied (admittedly pretty haphazardly) to New York City (New Amsterdam), for example, the style looks like this... And here are the style elements that comprise it... Find this and other styles by browsing this gallery. Happy Harbor Mapping! John Nelson

This layer visualizes over 60,000 commercial flight paths. The data was obtained from openflights.org, and was last updated in June 2014. The site states, "The third-party that OpenFlights uses for route data ceased providing updates in June 2014. The current data is of historical value only. As of June 2014, the OpenFlights/Airline Route Mapper Route Database contains 67,663 routes between 3,321 airports on 548 airlines spanning the globe. Creating and maintaining this database has required and continues to require an immense amount of work. We need your support to keep this database up-to-date."To donate, visit the site and click the PayPal link.Routes were created using the XY-to-line tool in ArcGIS Pro, inspired by Kenneth Field's work, and following a modified methodology from Michael Markieta (www.spatialanalysis.ca/2011/global-connectivity-mapping-out-flight-routes).Some cleanup was required in the original data, including adding missing location data for several airports and some missing IATA codes. Before performing the point to line conversion, the key to preserving attributes in the original data is a combination of the INDEX and MATCH functions in Microsoft Excel. Example function: =INDEX(Airlines!$B$2:$B$6200,MATCH(Routes!$A2,Airlines!$D$2:Airlines!$D$6200,0))                                                

-- DEMO Version v0.5--***Updated to include Errors Identified in the Split line feature class tool***Introducing the Address Management Solution - an ArcGIS Pro Desktop Application Template designed to revolutionize your address data management process!With this ArcGIS Pro Project template, you can efficiently create and manage address points and road centerlines, ensuring data accuracy and completeness. Powered by custom attribute rules, data creation becomes a breeze, automatically populating mandatory fields for seamless data integration.Key Features:Address Points: Easily create new address points with attribute rules that automate the generation of related attributes for comprehensive data.Road Centerlines: Benefit from attribute rules that streamline data editing, simplifying the process of splitting and recalculating address ranges for accurate data maintenance.NG911 Ready: Align your data with the NENA GIS Data Model and National standards, ensuring compatibility and efficient integration with Next Generation 9-1-1 services.User-Friendly: The template comes with targeted training modules, guiding users through introductory, advanced, and master levels to master ArcGIS Pro's powerful address management capabilities.Statewide Dataset: Leverage our comprehensive state-wide datasets, custom domains, and dynamic labels, tailored to cater to Arizona's geographic requirements.Empower your team with the tools and knowledge needed to succeed in creating a more resilient, efficient, and reliable address management system. Download the Desktop Application Template and review the Training Materials to get started!

Everything is awesome!Of course I don't need to convince you of the charm, educational utility, considered minimalism, and pure joy that Lego brings to the world. So why would I need to convince you that making maps in a Lego aesthetic is worth your while?This ArcGIS Pro style makes any vector point, line, or polygon layer look like a grid of little plastic nobly studs, ready to capture eyeballs and whip up unbridled excitement for skeuomorphic cartography! Plus it always re-sorts itself as you zoom in and out, always looking nice and blocky.Created in collaboration with Warren Davison, this style is ready to assemble your map into little Lego wonders.Here are some snapshots for you to peruse.Based mainly on these two texture overlays (sitting atop a dynamically colorable background element: Happy assembling! John Nelson

GIS data digitised from 2 DigitalGlobe images at a scale of 1:1000.
The features were digitised using ArcGIS Pro and were created within a topology to ensure the spatial integrity of the data. Line data include coastlines, ice fronts and grounding lines. Polygon data include continent, island, ice tongue and rock features.

The images and data are of the Bølingen Islands and surrounding area, in the Prydz Bay region of Antarctica.
(18FEB23042505-P2AS-017311657010_01_P001.TIL; 18FEB23042504-M2AS-017311657010_01_P001.TIL)
(24MAR16035205-P2AS-017311660010_01_P001.TIL; 24MAR16035205-M2AS-017311660010_01_P001.TIL)
Copyright 2024 DigitalGlobe Incorporated, Longmont CO USA 80503-6493

This map package includes the official Tribal areas that NTIA recognizes for their grant programs. The map package includes the following layers. Alaska Native Villages - this layer represents Alaska Native Villages and is created by Census. The layer was downloaded on Jan. 28, 2025, from here: TIGER/Line® Shapefiles.Native Hawaiian Areas - this layer represents Native Hawaiian Areas and is created by Census. The layer was downloaded on Jan. 28, 2025, from here: TIGER/Line® Shapefiles and has been filtered to only include Native Hawaiian Areas. BIA AIAN National LAR - this layer represents American Indian Lands and is created by the BIA. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025. The layer was filtered to only include lands across the continental U.S. BIA AIAN LAR Supplemental - this layer is a supplemental dataset to the LAR. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025.BIA AIAN Tribal Statistical Areas - this layer represents Tribal Statistical Areas located in Oklahoma. The layer was accessed here: BIA Access Open Data and was exported on Jan. 28, 2025.This map package was created on Jan. 28, 2025 and was created using ArcGIS Pro 3.4.0. If you have any questions regarding the map package please e-mail NTIAanalytics@ntia.gov.ResourcesCensus DataBIA Open DataBIA Data DisclaimerBy using this product, the user agrees to the below terms and conditions:No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes. These data have been developed from the best available sources. Although efforts have been made to ensure that the data are accurate and reliable, errors and variable conditions originating from source documents and/or the translation of information from source documents to the systems of record continue to exist. Users must be aware of these conditions and bear responsibility for the appropriate use of the information with respect to possible errors, scale, resolution, rectification, positional accuracy, development methodology, time period, environmental and climatic conditions and other circumstances specific to these data. The user is responsible for understanding the accuracy limitations of the data provided herein. The burden for determining fitness for use lies entirely with the user. The user should refer to the accompanying metadata notes for a description of the data and data development procedures.Census Use RestraintsThe TIGER/Line Shapefile products are not copyrighted however TIGER/Line and Census TIGER are registered trademarks of the U.S. Census Bureau. These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source. The boundary information in the TIGER/Line Shapefiles are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions. Coordinates in the TIGER/Line shapefiles have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest.

Pursuant to Section 7-100l of the Connecticut General Statutes, each municipality is required to transmit a digital parcel file and an accompanying assessor’s database file (known as a CAMA report), to its respective regional council of governments (COG) by May 1 annually. The dataset has combined the Parcels and Computer-Assisted Mass Appraisal (CAMA) data for 2025 into a single dataset. This dataset is designed to make it easier for stakeholders and the GIS community to use and access the information as a geospatial dataset. Included in this dataset are geometries for all 169 municipalities and attribution from the CAMA data for all but one municipality. These data were gathered from the CT municipalities by the COGs and then submitted to CT OPM. This dataset was created on September 2025 from data collected in 2024-2025. Data was processed using Python scripts and ArcGIS Pro for standardization and integration of the data. To learn more about Parcel and CAMA in CT visit our Parcels Page in the Geodata Portal.

Coordinate system:

This dataset is provided in NAD 83 Connecticut State Plane (2011) (EPSG 2234) projection as it was for 2024. Prior versions were provided at WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857).

Ownership Suppression:

The updated dataset includes parcel data for all towns across the state, with some towns featuring fully suppressed ownership information. In these instances, the owner’s name was replaced with the label "Current Owner," the co-owner’s name will be listed as "Current Co-Owner," and the mailing address will appear as the property address itself. For towns with fully suppressed ownership data, please note that no "Suppression" field was included in the submission to confirm these details and this labeling approach was implemented as the solution.

New Data Fields:

The new dataset introduces the “Property Zip” and “Mailing Zip” fields, which will display the zip codes for the owner and property.

Service URL:

In 2024, we implemented a stable URL to maintain public access to the most up-to-date data layer. Users are strongly encouraged to transition to the new service as soon as possible to ensure uninterrupted workflows. This URL will remain persistent, providing long-term stability for your applications and integrations. Once you’ve transitioned to the new service, no further URL changes will be necessary.

CAMA Notes:

The CAMA underwent several steps to standardize and consolidate the information. Python scripts were used to concatenate fields and create a unique identifier for each entry. The resulting dataset contains 1,354,720 entries and information on property assessments and other relevant attributes.

• CAMA was provided by the towns.

Spatial Data Notes:

Data processing involved merging the parcels from different municipalities using ArcGIS Pro and Python. The resulting dataset contains 1,282,833 parcels.

• No alteration has been made to the spatial geometry of the data.

• Fields that are associated with CAMA data were provided by towns.

• The data fields that have information from the CAMA were sourced from the towns’ CAMA data.

• If no field for the parcels was provided for linking back to the CAMA by the town a new field within the original data was selected if it had a match rate above 50%, that joined back to the CAMA.

• Linking fields were renamed to "Link".

• All linking fields had a census town code added to the beginning of the value to create a unique identifier per town.

• Any field that was not town name, Location, Editor, Edit Date, or a field associated back to the CAMA, was not used in the creation of this Dataset.

• Only the fields related to town name, location, editor, edit date, and link fields associated with the towns’ CAMA were included in the creation of this dataset. Any other field provided in the original data was deleted or not used.

• Field names for town (Muni, Municipality) were renamed to "Town Name".

Attributes included in the data:

• Town Name

• Owner

• Co-Owner

• Link

• Editor

• Edit Date

• Collection year – year the parcels were submitted

• Location

• Property Zip

• Mailing Address

• Mailing City

• Mailing State

• Mailing Zip

• Assessed Total

• Assessed Land

• Assessed Building

• Pre-Year Assessed Total

• Appraised Land

• Appraised Building

• Appraised Outbuilding

• Condition

• Model

• <p style='margin-bottom:1.5rem;

Dataset SummaryAbout this data:This is a polygon feature layer with the border of the city of RochesterThe City of Rochester maintains an official city map that defines the corporate boundaries as well as all public rights-of-way. Records and information relating to the official map and other survey data are available to the public. Data Dictionary:Note - many of these fields are auto generated when creating a polygon in ArcGIS Pro. Area: The area of the polygon in meters. Perimeter: The total length of the boundary line of the polygon in meters. Outline_ID: An auto created identifier for this boundary. Acres: Area of the polygon converted to acres. RuleID: Associated with a validation rule in a geodatabase. SqMiles: Area of the polygon converted to square miles. RuleID_1: A secondary rule applied to this boundary. Name: The name of the city. Shape_Area: The built-in geometry field that holds the area of the shape. Shape_Length: The built-in geometry field that holds the area of the shape. Source: This data is maintained by the City's GIS Coordinator.

OverviewThis document provides instructions on how to use the data and code associated with the manuscript titled “Beyond absolute space: Modeling disease dispersion and reactive actions from a multi-spatialization perspective”. The following sections will guide you through the setup, data structure, code execution, expected output, and any additional notes necessary for reproducing the results presented in the manuscript.Table of Contents· Requirements· Data files· Code structure· Running the code· Expected Output· Troubleshooting==========================================================RequirementsOperating system· Windows 7 or higher (recommended)· UbuntuSoftware· Python (version 2.7 or higher) or Jupyter NotebookRequired libraries: numpy, pandas, scipy, matplotlib, pgmpyData filesSurvey_data_processed_Anonymized.csvProtectiveAction_Anonymized.csvThese two data files have been pre-processed from the raw survey data to support the Python code for generating Figures 3, 4, 5, and 6. To protect the privacy and confidentiality of human research participants, all personal information has been excluded in the pre-processing.The data files include anonymized individual record IDs, self-reported weekly symptoms (for themselves and others), protective actions taken, and the service places they visited each week (20 types). The data files also include information regarding the daily volume of visits and the presence of infectious visitors at the 20 types of service places.Code structure· / Firstlayer_ModifyandUpload.ipynbThis is the code file for the first layer of the Bayesian network analysis and SHAP analysis.· / SecondLayerProtectiveAction.ipynbThis is the code file for the second layer of the Bayesian network analysis and SHAP analysis.Running the Code· To run the Python code (preferably in Jupyter Notebook), ensure that all dependencies are installed by running: pip install pandas pgmpy. These dependencies are specified at the beginning of the file.Expected Output· Running the provided Python script will generate the specified figures below. Note that the labels and axis text of the figures are adjusted in the manuscript for readability and to ensure consistency with the manuscript.Firstlayer_ModifyandUpload.ipynb· Figure 3 – Generated in the script (Cell 3, line 85).· Figure 4 – Generated in the script (Cell 4, line 101).SecondLayerProtectiveAction.ipynb· Figure5 – Generated in the script (Cell 3, line 65).· Figure 6 – Generated in the script (line 150). Part of the Figure 5 was generated in ArcGIS Pro.Note:· Table 1 is created directly in Microsoft PowerPoint. Refer to Figures & Table.pptx.· Figures 1 and 2 is created directly in Microsoft PowerPoint. Refer to Figures & Table.pptx.TroubleshootingIf you encounter issues while running the script, check the following:· Missing Data Files: Ensure all required data files are in the same directory as the script or that the correct file paths are specified.· Library/Package Errors: Ensure that all necessary libraries and packages are installed. Use pip install as needed.

This dataset consists of topographic features across the East Antarctic coastal region, extending from 33°E to 168°E and from the coast inland to approximately 84°S in some areas.

The features were digitised using ArcGIS Pro and were created within a topology to ensure the spatial integrity of the data. Line data include coastlines, ice fronts and grounding lines. Polygon data include continent features, islands, ice shelfs, ice tongues, icebergs, rocks and lakes.

The features were digitised at a scale of 1:25,000 using Sentinel2 imagery: earthexplorer.usgs.gov, 'Copernicus Sentinel data [2023]'. Note: Individual Sentinel 2 data source images are referenced in the data attribute tables with the exception of the coastline polygon dataset which was derived from the coastline line dataset.

Grounding lines were derived from ASAID_Grounding_line_continent_Sc_dep : Rignot, E., J. Mouginot, and B. Scheuchl. 2016. MEaSUREs Antarctic Grounding Line from Differential Satellite Radar Interferometry, Version 2. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://nsidc.org/data/nsidc-0498/versions/2

The ASAID data were edited using ICESat2 data: Derived Grounding Zone for Antarctic Ice Shelves, United States Antarctic Program Data Center (USAP-DC) www.usap-dc.org ; http://www.usap-dc.org/view/dataset/609469 as well as Sentinel2 imagery and The Reference Elevation Model of Antarctica version 2 (REMA 2): Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P., The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665-674, https://doi.org/10.5194/tc-13-665-2019 , 2019 DEM(s) courtesy of the Polar Geospatial Center.

The Antarctic Iceberg Data were sourced from U.S.National Ice Centre (usicecenter.gov/Products/AntarcIcebergs) in CSV format. The CSV data used in this project is dated 3 Feb 2023. The point data were used to locate and digitise icebergs using Sentinel 2 imagery at a scale of 1:25000.

The 25K topographic features are stored in the Australian Antarctic Division Enterprise GIS and are available for download using the provided links.

🇺🇸 미국 English The Watershed Boundary Dataset (WBD) is a seamless, national hydrologic unit dataset. Hydrologic units represent the area of the landscape that drains to a portion of the stream network. (https://www.usgs.gov/national-hydrography/watershed-boundary-dataset) It is maintained by the U.S. Geological Survey (USGS) in partnership with the states. The Department of Water Resources is the steward for the California portion of this dataset.The hydrologic units (HU) in the WBD form a standardized system for organizing, collecting, managing, and reporting hydrologic information for the nation. The HUs in the WBD are arranged in a nested, hierarchical system with each HU in the system identified using a unique code. Hydrologic unit codes (HUC) are developed using a progressive two-digit system where each successively smaller areal unit is identified by adding two digits to the identifying code the smaller unit is nested within. WBD contains eight levels of progressive hydrologic units identified by unique 2- to 16-digit codes. The dataset is complete for the United States to the 12-digit hydrologic unit. The 8-digit level unit is often referred to as HUC8 and is a commonly used reference framework for planning and environmental assessment. This particular version of the dataset was created by downloading the CA State extract of the National Hydrography Dataset from the USGS website https://www.usgs.gov/national-hydrography/access-national-hydrography-products and then performing a geoprocessing operation in ArcGIS Pro software to clip the HUC8s at the state of California political boundary. (https://data.cnra.ca.gov/dataset/california-county-boundaries2). A web map service was created with this dataset, but at it's original digitized resolution it can take a long time to render in a web map application. This dataset is a simplified version, created by use of the ArcGIS Simplify Polygon tool with the Douglas-Peucker Line simplification algorithm, reducing the vertex count from 1,095,449 to 9108. This dataset was reprojected from the original NAD 83 Geographic Coordinate System to WGS 1984 Web Mercator auxiliary sphere for use in web map applications. Any questions about this dataset may be sent to jane.schafer-kramer@water.ca.gov

NB: The Aotearoa Contour lines are currently in beta and should not be used in production environments.Last updatedSee the vector basemap item details here.See the hillshade item details here.See the contour line item details here.ProjectionNew Zealand Transverse Mercator 2000 (NZTM2000). This vector tile layer provides a detailed basemap for New Zealand in the NZ Transverse Mercator projection. The style is based on the classic Esri Topographic style. This vector tile layer provides unique capabilities for customization and high-resolution display.This map includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries for added context.This is a multisource layer, meaning features from the Aotearoa Contour Lines and NZ Topographic Relief layers are combined into one style file. Multisource layers allow for the drawing order of features to be customised, therefore one layer doesn't need to be draped over the other - features from each layer can instead be integrated together in the proper display order. For example, by moving the layers for Buildings and Roads above the contour lines in the style's JSON file, contour lines will be drawn underneath these features in the map. See Esri's blog on multisource vector tile layers for further context. It also includes 10m interval Contour Lines derived from 1m Digital Elevation Model merged with LINZ contours, where 1m DEM is not available yet.The 1m contours have been processed for visualisation purposes using the Focal Statistics tool (30x30m) prior to creating the contours in ArcGIS Pro, then they have been simplified using Simplify Line with the point remove (Douglas Peucker) method with a tolerance of 0.5m.This map uses the NZ Hillshade layer.Data sourcesLand Information New ZealandContour Lines, Buildings, Parcels, Place Names, Water-bodies, Vegetation, Protected Areas, Airports, Railways & Islands.Statistics New ZealandAdministrative Boundaries & Urban AreasNational Institute of Water & Atmospheric Research (NIWA)River Environment Classification© OpenStreetMap ContributorsRoad Centrelines, Buildings, Landuse Types, Areas of Interest and Points of Interest.Natural EarthBathymetry & Marine LabelsThis map is offered by Eagle Technology (Official Esri Distributor). Eagle Technology offers layers and maps that can be used in the ArcGIS platform. The Content team at Eagle Technology updates the layers on a regular basis and regularly adds new content to the Living Atlas. By using this content and combining it with other data you can create new information products quickly and easily.If you have any questions or remarks about the content, please let us now at livingatlas@eagle.co.nzCustomize this MapBecause this map is delivered as a vector tile layer, users can customize the map to change its content and symbology, including fonts. Users are able to turn on and off layers and change symbols for layers.An easy way to change the style of this map is to use the Vector Basemap Style Editor:https://developers.arcgis.com/vector-tile-style-editor/

Please note that this dataset is not an official City of Toronto land use dataset. It was created for personal and academic use using City of Toronto Land Use Maps (2019) found on the City of Toronto Official Plan website at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/official-plan-maps-copy, along with the City of Toronto parcel fabric (Property Boundaries) found at https://open.toronto.ca/dataset/property-boundaries/ and Statistics Canada Census Dissemination Blocks level boundary files (2016). The property boundaries used were dated November 11, 2021. Further detail about the City of Toronto's Official Plan, consolidation of the information presented in its online form, and considerations for its interpretation can be found at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/ Data Creation Documentation and Procedures Software Used The spatial vector data were created using ArcGIS Pro 2.9.0 in December 2021. PDF File Conversions Using Adobe Acrobat Pro DC software, the following downloaded PDF map images were converted to TIF format. 9028-cp-official-plan-Map-14_LandUse_AODA.pdf 9042-cp-official-plan-Map-22_LandUse_AODA.pdf 9070-cp-official-plan-Map-20_LandUse_AODA.pdf 908a-cp-official-plan-Map-13_LandUse_AODA.pdf 978e-cp-official-plan-Map-17_LandUse_AODA.pdf 97cc-cp-official-plan-Map-15_LandUse_AODA.pdf 97d4-cp-official-plan-Map-23_LandUse_AODA.pdf 97f2-cp-official-plan-Map-19_LandUse_AODA.pdf 97fe-cp-official-plan-Map-18_LandUse_AODA.pdf 9811-cp-official-plan-Map-16_LandUse_AODA.pdf 982d-cp-official-plan-Map-21_LandUse_AODA.pdf Georeferencing and Reprojecting Data Files The original projection of the PDF maps is unknown but were most likely published using MTM Zone 10 EPSG 2019 as per many of the City of Toronto's many datasets. They could also have possibly been published in UTM Zone 17 EPSG 26917 The TIF images were georeferenced in ArcGIS Pro using this projection with very good results. The images were matched against the City of Toronto's Centreline dataset found here The resulting TIF files and their supporting spatial files include: TOLandUseMap13.tfwx TOLandUseMap13.tif TOLandUseMap13.tif.aux.xml TOLandUseMap13.tif.ovr TOLandUseMap14.tfwx TOLandUseMap14.tif TOLandUseMap14.tif.aux.xml TOLandUseMap14.tif.ovr TOLandUseMap15.tfwx TOLandUseMap15.tif TOLandUseMap15.tif.aux.xml TOLandUseMap15.tif.ovr TOLandUseMap16.tfwx TOLandUseMap16.tif TOLandUseMap16.tif.aux.xml TOLandUseMap16.tif.ovr TOLandUseMap17.tfwx TOLandUseMap17.tif TOLandUseMap17.tif.aux.xml TOLandUseMap17.tif.ovr TOLandUseMap18.tfwx TOLandUseMap18.tif TOLandUseMap18.tif.aux.xml TOLandUseMap18.tif.ovr TOLandUseMap19.tif TOLandUseMap19.tif.aux.xml TOLandUseMap19.tif.ovr TOLandUseMap20.tfwx TOLandUseMap20.tif TOLandUseMap20.tif.aux.xml TOLandUseMap20.tif.ovr TOLandUseMap21.tfwx TOLandUseMap21.tif TOLandUseMap21.tif.aux.xml TOLandUseMap21.tif.ovr TOLandUseMap22.tfwx TOLandUseMap22.tif TOLandUseMap22.tif.aux.xml TOLandUseMap22.tif.ovr TOLandUseMap23.tfwx TOLandUseMap23.tif TOLandUseMap23.tif.aux.xml TOLandUseMap23.tif.ov Ground control points were saved for all georeferenced images. The files are the following: map13.txt map14.txt map15.txt map16.txt map17.txt map18.txt map19.txt map21.txt map22.txt map23.txt The City of Toronto's Property Boundaries shapefile, "property_bnds_gcc_wgs84.zip" were unzipped and also reprojected to EPSG 26917 (UTM Zone 17) into a new shapefile, "Property_Boundaries_UTM.shp" Mosaicing Images Once georeferenced, all images were then mosaiced into one image file, "LandUseMosaic20211220v01", within the project-generated Geodatabase, "Landuse.gdb" and exported TIF, "LandUseMosaic20211220.tif" Reclassifying Images Because the original images were of low quality and the conversion to TIF made the image colours even more inconsistent, a method was required to reclassify the images so that different land use classes could be identified. Using Deep learning Objects, the images were re-classified into useful consistent colours. Deep Learning Objects and Training The resulting mosaic was then prepared for reclassification using the Label Objects for Deep Learning tool in ArcGIS Pro. A training sample, "LandUseTrainingSamples20211220", was created in the geodatabase for all land use types as follows: Neighbourhoods Insitutional Natural Areas Core Employment Areas Mixed Use Areas Apartment Neighbourhoods Parks Roads Utility Corridors Other Open Spaces General Employment Areas Regeneration Areas Lettering (not a land use type, but an image colour (black), used to label streets). By identifying the letters, it then made the reclassification and vectorization results easier to clean up of unnecessary clutter caused by the labels of streets. Reclassification Once the training samples were created and saved, the raster was then reclassified using the Image Classification Wizard tool in ArcGIS Pro, using the Support...

Three feature layers of Unites States internal state boundaries at different scales: 1:500K, 1:5M, and 1:20M. These layers are intended for use as a cartographic product. It is up to the user to determine which layer is most appropriate for their map.Derived from 2019 US Census Bureau Cartographic Boundary Files for state boundaries using ArcGIS Pro 2.4.3. Process:Original files were downloaded from US Census for the three different scales.Polygons were then converted to lines using the Polygon-to-Line tool.To remove the coastlines, all rows not having a LEFT_FID or RIGHT_FID attribute equal to -1 were then exported to a new geodatabase feature class.The geodatabase was zipped and uploaded to ArcGIS Online.For more information on Cartographic Boundary Files visit https://www.census.gov/programs-surveys/geography/technical-documentation/naming-convention/cartographic-boundary-file.html and https://www.census.gov/geographies/mapping-files/time-series/geo/cartographic-boundary.html.Created by Ryan Davis (RDavis9@cdc.gov) on behalf of CDC/ATSDR/DTHHS/GRASP.

AbstractA continuous contour dataset at 100 m intervals for all land south of 60°S, excluding the Balleny Islands. The vertical datum of the contours is EGM2008. Contours are extracted primarily from the PGC Reference Elevation Model of Antarctica (REMA) v1.1 with certain islands filled from Copernicus WorldDEM. Further small areas are interpreted from satellite imagery, and Peter I Øy contours are from the Norwegian Polar Institute. Sources of individual line segments are contained in the attribute table and full compilation information is given in the lineage statement.Note: contours overlap the coastline in small areas, due to resolution of the data used in creation of the lines, and potential errors in coastline and/or contour data. Certain areas are known to contain erroneous data due to faults in the original DEM data.Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.Further information and useful linksMap projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap.The currency of this dataset is November 2022 and will be reviewed every 6 months. This feature layer will always reflect the most recent version.For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue.A related medium resolution dataset at 500 m intervals is also published via Living Atlas.For background information on the ADD project, please see the British Antarctic Survey ADD project page.LineageAll processing described here was performed in ArcGIS Pro version 2.6.A composite Digital Elevation Model (DEM) was created comprising of three datasets from the Reference Elevation Model of Antarctica v1.1: ‘REMA_100m_peninsula_dem_filled’, ‘REMA_100m_dem’ and ‘REMA_200m_dem_filled’. These DEMs were first converted from ellipsoidal height to height above EGM2008 geoid and then mosaicked together in respective order at 100 m spatial resolution. This 100 m DEM was smoothed by performing ‘Focal Statistics’ using a 3x3 cell size.100 m contours were extracted and all contours with a height <1m were deleted, as well as erroneous offshore contours. All contour ‘dangles’ were identified and then fixed to create a continuous dataset. They were fixed either by interpreting the correct line from satellite imagery or from ‘Copernicus WorldDEM 90m’ contours. Such lines are attributed with ‘interpreted’ in the source field and should be treated with caution. In other locations where the contours significantly overlapped the coastline, contours were redrawn/interpreted to not go offshore. In certain locations, primarily some islands on the Antarctic Peninsula, REMA data was insufficient to produce contours. In these places, contours were produced from the ‘Copernicus WorldDEM 90m’ DEM and smoothed by 300 m using a PAEK smoothing algorithm. Contours for Peter I Øy were incorporated from the Norwegian Polar Institute Data at 100 m intervals. The source of every line is written in the attribute table.All contours were merged together and lines <150 m in length were deleted. Further lines <1500 m were deleted in ‘non-mountainous’ regions, so as to avoid deleting small mountain peak contours but to still simplify the main dataset. These regions were interpreted manually using the hillshade of the DEM used to produce the contours.Original DEM sources and citations:REMA: Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P.: The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665-674, https://doi.org/10.5194/tc-13-665-2019, 2019.Copernicus WorldDEM: produced using Copernicus WorldDEM™-90 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved.Norwegian Polar Institute (2014). Map data / kartdata Peter I Øy 1:50 000 (P50 Kartdata). Norwegian Polar Institute. https://doi.org/10.21334/npolar.2014.29105abcCitationPlease cite this item as: 'Gerrish, L., Fretwell, P., & Cooper, P. (2020). High resolution vector contours for Antarctica (7.3) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/4bd20a2b-df7d-46a2-acdf-5104c82ff4c7'If using for a graphic or if short on space, please cite as 'data from the SCAR Antarctic Digital Database, accessed [year]'

The Missoula Community Resource Map identifies programs and organizations that provide a range of services to our community members. The ESRI Arc Pro program was used to create the base layer and design for the map. Missoula organizations and program information and location data were gathered by Jordan Lestina. Mountain Line provided the GIS layers for the bus routes included on the map. Jordan Lestina, UM forestry graduate student and Food Bank volunteer, created the map and finalized the map layout using Adobe Photoshop. The most current map update was completed on August 8th, 2022. The pdf page sizes are 8.5 by 11 inches.