FlowMapper.org is a web-based framework for automated production and design of origin-destination flow maps. FlowMapper has four major features that contribute to the advancement of existing flow mapping systems. First, users can upload and process their own data to design and share customized flow maps. The ability to save data, cartographic design and map elements in a project file allows users to easily share their data and/or cartographic design with others. Second, users can generate customized flow symbols to support different flow map reading tasks such as comparing flow magnitudes and directions and identifying flow and location clusters that are strongly connected with each other. Third, FlowMapper supports supplementary layers such as node symbols, choropleth, and base maps to contextualize flow patterns with location references and characteristics. Finally, the web-based architecture of FlowMapper supports server-side computational capabilities to process and normalize large flow data and reveal natural patterns of flows.

This map charts out EPA Level 3 ecoregions that are considered deserts in North America. Furthermore, decades of climate data from NOAA have been clipped and measured for each desert, the data was then used to generate Walter-Leith Climate Summary Diagrams which are a double-y axis chart that normalizes precipitation and temperature to identify months of general humidity or aridity.Artwork/Illustrations of Desert Flora & Fauna by Marissa WallData:CMAP Precipitation & Temperature data provided by the NOAA PSL, Boulder, Colorado, USA from their website at https://psl.noaa.gov

When people think about geography, one of the first things that come to mind are maps. Maps are familiar and are viewed and used every day. When people think of maps, they usually think of reference maps that help them navigate from one place to another. If you ask someone to think a little more about maps, they will often tell you about the weather maps they see on the news or the internet. However, those maps are just scratching the surface of maps and mapping. Consider for a moment the maps that pop-up when you use a rideshare app to get around a city or the maps embedded in the websites you buy goods from. If you have ever watched coverage of a national election, you will have seen dozens of maps depicting voting patterns. Watch the following video to learn more.

The Human Geography Map (World Edition) web map provides a detailed vector basemap with a monochromatic style and content adjusted to support Human Geography information. Where possible, the map content has been adjusted so that it observes WCAG contrast criteria.This basemap, included in the ArcGIS Living Atlas of the World, uses 3 vector tile layers:Human Geography Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography Detail, a detail reference layer including administrative boundaries, roads and highways, and larger bodies of water. This layer is designed to be used with a high degree of transparency so that the detail does not compete with your information. It is set at approximately 50% in this web map, but can be adjusted.Human Geography Base, a simple basemap consisting of land areas in a very light gray only.The vector tile layers in this web map are built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Learn more about this basemap from the cartographic designer in Introducing a Human Geography Basemap.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map.

The Audio Cartography project investigated the influence of temporal arrangement on the interpretation of information from a simple spatial data set. I designed and implemented three auditory map types (audio types), and evaluated differences in the responses to those audio types.

The three audio types represented simplified raster data (eight rows x eight columns). First, a "sequential" representation read values one at a time from each cell of the raster, following an English reading order, and encoded the data value as loudness of a single fixed-duration and fixed-frequency note. Second, an augmented-sequential ("augmented") representation used the same reading order, but encoded the data value as volume, the row as frequency, and the column as the rate of the notes play (constant total cell duration). Third, a "concurrent" representation used the same encoding as the augmented type, but allowed the notes to overlap in time.

Participants completed a training session in a computer-lab setting, where they were introduced to the audio types and practiced making a comparison between data values at two locations within the display based on what they heard. The training sessions, including associated paperwork, lasted up to one hour. In a second study session, participants listened to the auditory maps and made decisions about the data they represented while the fMRI scanner recorded digital brain images.

The task consisted of listening to an auditory representation of geospatial data ("map"), and then making a decision about the relative values of data at two specified locations. After listening to the map ("listen"), a graphic depicted two locations within a square (white background). Each location was marked with a small square (size: 2x2 grid cells); one square had a black solid outline and transparent black fill, the other had a red dashed outline and transparent red fill. The decision ("response") was made under one of two conditions. Under the active listening condition ("active") the map was played a second time while participants made their decision; in the memory condition ("memory"), a decision was made in relative quiet (general scanner noises and intermittent acquisition noise persisted). During the initial map listening, participants were aware of neither the locations of the response options within the map extent, nor the response conditions under which they would make their decision. Participants could respond any time after the graphic was displayed; once a response was entered, the playback stopped (active response condition only) and the presentation continued to the next trial.

Data was collected in accordance with a protocol approved by the Institutional Review Board at the University of Oregon.

• Additional details about the specific maps used in this are available through University of Oregon's ScholarsBank (DOI 10.7264/3b49-tr85).

• Details of the design process and evaluation are provided in the associated dissertation, which is available from ProQuest and University of Oregon's ScholarsBank.

• Scripts that created the experimental stimuli and automated processing are available through University of Oregon's ScholarsBank (DOI 10.7264/3b49-tr85).

Preparation of fMRI Data

Conversion of the DICOM files produced by the scanner to NiFTi format was performed by MRIConvert (LCNI). Orientation to standard axes was performed and recorded in the NiFTi header (FMRIB, fslreorient2std). The excess slices in the anatomical images that represented tissue in the next were trimmed (FMRIB, robustfov). Participant identity was protected through automated defacing of the anatomical data (FreeSurfer, mri_deface), with additional post-processing to ensure that no brain voxels were erroneously removed from the image (FMRIB, BET; brain mask dilated with three iterations "fslmaths -dilM").

Preparation of Metadata

The dcm2niix tool (Rorden) was used to create draft JSON sidecar files with metadata extracted from the DICOM headers. The draft sidecar file were revised to augment the JSON elements with additional tags (e.g., "Orientation" and "TaskDescription") and to make a more human-friendly version of tag contents (e.g., "InstitutionAddress" and "DepartmentName"). The device serial number was constant throughout the data collection (i.e., all data collection was conducted on the same scanner), and the respective metadata values were replaced with an anonymous identifier: "Scanner1".

Preparation of Behavioral Data

The stimuli consisted of eighteen auditory maps. Spatial data were generated with the rgeos, sp, and spatstat libraries in R; auditory maps were rendered with the Pyo (Belanger) library for Python and prepared for presentation in Audacity. Stimuli were presented using PsychoPy (Peirce, 2007), which produced log files from which event details were extracted. The log files included timestamped entries for stimulus timing and trigger pulses from the scanner.

• Log files are available in "sourcedata/behavioral".
• Extracted event details accompany BOLD images in "sub-NN/func/*events.tsv".
• Three column explanatory variable files are in "derivatives/ev/sub-NN".

References

Audacity® software is copyright © 1999-2018 Audacity Team. Web site: https://audacityteam.org/. The name Audacity® is a registered trademark of Dominic Mazzoni.

FMRIB (Functional Magnetic Resonance Imaging of the Brain). FMRIB Software Library (FSL; fslreorient2std, robustfov, BET). Oxford, v5.0.9, Available: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/

FreeSurfer (mri_deface). Harvard, v1.22, Available: https://surfer.nmr.mgh.harvard.edu/fswiki/AutomatedDefacingTools)

LCNI (Lewis Center for Neuroimaging). MRIConvert (mcverter), v2.1.0 build 440, Available: https://lcni.uoregon.edu/downloads/mriconvert/mriconvert-and-mcverter

Peirce, JW. PsychoPy–psychophysics software in Python. Journal of Neuroscience Methods, 162(1–2):8 – 13, 2007. Software Available: http://www.psychopy.org/

Python software is copyright © 2001-2015 Python Software Foundation. Web site: https://www.python.org

Pyo software is copyright © 2009-2015 Olivier Belanger. Web site: http://ajaxsoundstudio.com/software/pyo/.

R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available: https://www.R-project.org/.

rgeos software is copyright © 2016 Bivand and Rundel. Web site: https://CRAN.R-project.org/package=rgeos

Rorden, C. dcm2niix, v1.0.20171215, Available: https://github.com/rordenlab/dcm2niix

spatstat software is copyright © 2016 Baddeley, Rubak, and Turner. Web site: https://CRAN.R-project.org/package=spatstat

sp software is copyright © 2016 Pebesma and Bivand. Web site: https://CRAN.R-project.org/package=sp

Cut to clipboard Dataset Groups Paweł Kowalski Research and teaching employee at the Department of Cartography since 1994. Specialization in: geographic information systems, topographic databases, multimedia techniques in cartography, social cartography, neocartography and the methodology of designing geoinformation websites. Over 70 publications, i.a. in Polish Cartographical Review, Przegląd Geodezyjny, Magazyn Geoinformacyjny Geodeta, Acta Scientiarum Polonorum. Geodesia et Descriptio Terrarium. 8 chapters in monographs and collected works. Participation in scientific research and implementation work, e.g. within the following projects: “Digital technology of topographic map production 1:10 000”, “Administrative boundaries of Poland”, "Topographic information system of the country: theoretical and methodical conceptual development", “Methodology and procedures for the integration, visualization, generalization and standardization of reference databases available in geodetic and cartographic resources”. From 2009 to 2011, a member of the expert team of the Head Office of Geodesy and Cartography. Deputy chairman of the Association of Polish Cartographers, the organizer and commissioner of its annual contest for the Internet Map of the Year.

This dataset consists of cartographic data in digital line graph (DLG) form for the northeastern states (Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island and Vermont). Information is presented on two planimetric base categories, political boundaries and administrative boundaries, each available in two formats: the topologically structured format and a simpler format optimized for graphic display. These DGL data can be used to plot base maps and for various kinds of spatial analysis. They may also be combined with other geographically referenced data to facilitate analysis, for example the Geographic Names Information System.

BTA layer (reference year 2017) containing the surface elements of the railway tracks for the entire territory of Navarra at 1:5,000 scale. The BTA is an adaptation to the production of the National Cartographic Base (BCN) of the National Geographic Institute (IGN). BTA is the acronym for "Harmonized Topographic Base". It is a data model agreed by the Autonomous Communities (ACs) and approved by the Superior Geographical Council (CSG) of which there is a v1 version dated 2008.

Learn the key factors to consider when planning a cartography project and preparing data that supports your map's purpose, audience, and format.

- 01_RAW_DATA contains 2 CSV files: the first contains all drawings used for the analyse, the second all participations. We made attribute join on session

- 02_MAP_DRAWING contains all drawings split by view (location, style, zoom).

- 03_DRAWING_ANCHORS split drawings by view after manual selection and assignment (Location, style, zoom, drawings_anchor).

- 04_ANCHORS contains the vector delineation of pan-scalar anchors (Location, style, zoom,anchor). See workflow_QGIS AllProcess.excalidraw with excalidraw website

- 05_STATISTIC_DRAWING contains statictical attribute information calculte in xls of drawings (Location, style, zoom,drawings_statistics) See workflow_QGIS AllProcess.excalidraw with excalidraw website

- 06_BOUNDED_ANCHOR contains vector data for anchor lines that have been drawn in the same hue (Location, style, zoom,bounded_anchor). See workflow_QGIS AllProcess.excalidraw- with excalidraw website

- 07_WORFLOW_ANCHOR : Contains all QGIS workflows used for AnchorWhat analysis + See workflow_QGIS AllProcess.excalidraw with excalidraw website

- 08_ILLUSTATIONS contains most of the illustrations for the script

- 09_INITIAL_VIEWS: Contain all the view one wich participants were drawings

- 10_3D_VIEWS : Contain the views where drawing were extruded. The height of each pixel corresponds to the number of drawing divided by the number of participant See workflow_QGIS AllProcess.excalidraw- with excalidraw website

- 11_ANNOTED_VIEWS : Contain the 3D view annoted with the anchors.Linked to the illustration folder.

This repository contains the example datasets used in the following article by Caglar Koylu, Geng Tian and Mary Windsor: FlowMapper.org: A web-based framework for designing origin-destination flow maps

This layer contains the following map information at a scale of 1.1000 for the municipalities of Navarra: communication routes, buildings, hydrography, themed soil, altimetry, unique buildings, mapped area, infrastructure networks and other place names. The list of municipalities mapped is in the following url: https://idena.navarra.es/downloads/List_of_municipalities_map_1000.pdf

Raw and Processed Data in the article Cartography of Hate Expressions on Web Pages and Social Networks of Spanish News Media, whose objective is to establish a cartography of the hatred spread based on the comments sent by users to various social networks after the publication of information through different digital media in Spain.The processed data is based on the collection of 10,111,321 messages published in five of the main Spanish digital media (El Mundo, ABC, El País, La Vanguardia, and 20 Minutos) between January 2021 and July 2022 on X, Facebook, and its web portals. Of this total, 929,625 messages containing hate expressions were identified.This work is a result of the Cartodiocom Project (PID2019-105613GB-C31) and Hatemedia Project (PID2020-114584GB-I00), funded by MCIN/AEI /10.13039/501100011033.

HazMatMapper is an online and interactive geographic visualization tool designed to facilitate exploration of transnational flows of hazardous waste in North America (http://geography.wisc.edu/hazardouswaste/map/). While conventional narratives suggest that wealthier countries such as Canada and the United States (US) export waste to poorer countries like Mexico, little is known about how waste trading may affect specific sites within any of the three countries. To move beyond anecdotal discussions and national aggregates, we assembled a novel geographic dataset describing transnational hazardous waste shipments from 2007 to 2012 through two Freedom of Information Act requests for documents held by the US Environmental Protection Agency. While not yet detailing all of the transnational hazardous waste trade in North America, HazMatMapper supports multiscale and site-specific visual exploration of US imports of hazardous waste from Canada and Mexico. It thus enables academic researchers, waste regulators, and the general public to generate hypotheses on regional clustering, transnational corporate structuring, and environmental justice concerns, as well as to understand the limitations of existing regulatory data collection itself. Here, we discuss the dataset and design process behind HazMatMapper and demonstrate its utility for understanding the transnational hazardous waste trade.

Continuing the tradition of the best-selling Getting to Know series, Getting to Know ArcGIS Pro 2.6 teaches new and existing GIS users how to get started solving problems using ArcGIS Pro. Using ArcGIS Pro for these tasks allows you to understand complex data with the leading GIS software that many businesses and organizations use every day.Getting to Know ArcGIS Pro 2.6 introduces the basic tools and capabilities of ArcGIS Pro through practical project workflows that demonstrate best practices for productivity. Explore spatial relationships, building a geodatabase, 3D GIS, project presentation, and more. Learn how to navigate ArcGIS Pro and ArcGIS Online by visualizing, querying, creating, editing, analyzing, and presenting geospatial data in both 2D and 3D environments. Using figures to show each step, Getting to Know ArcGIS Pro 2.6 demystifies complicated process like developing a geoprocessing model, using Python to write a script tool, and the creation of space-time cubes. Cartographic techniques for both web and physical maps are included.Each chapter begins with a prompt using a real-world scenario in a different industry to help you explore how ArcGIS Pro can be applied for operational efficiency, analysis, and problem solving. A summary and glossary terms at the end of every chapter help reinforce the lessons and skills learned.Ideal for students, self-learners, and seasoned professionals looking to learn a new GIS product, Getting to Know ArcGIS Pro 2.6 is a broad textbook and desk reference designed to leave users feeling confident in using ArcGIS Pro on their own.AUDIENCEProfessional and scholarly. Higher education.AUTHOR BIOMichael Law is a cartographer and GIS professional with more than a decade of experience. He was a cartographer for Esri, where he developed cartography for books, edited and tested GIS workbooks, and was the editor of the Esri Map Book. He continues to work with GIS software, writing technical documentation, teaching training courses, and designing and optimizing user interfaces.Amy Collins is a writer and editor who has worked with GIS for over 16 years. She was a technical editor for Esri, where she honed her GIS skills and cultivated an interest in designing effective instructional materials. She continues to develop books on GIS education, among other projects.Pub Date: Print: 10/6/2020 Digital: 8/18/2020 ISBN: Print: 9781589486355 Digital: 9781589486362 Price: Print: $84.99 USD Digital: $84.99 USD Pages: 420 Trim: 7.5 x 9.25 in.Table of ContentsPrefaceChapter 1 Introducing GISExercise 1a: Explore ArcGIS OnlineChapter 2 A first look at ArcGIS Pro Exercise 2a: Learn some basics Exercise 2b: Go beyond the basics Exercise 2c: Experience 3D GISChapter 3 Exploring geospatial relationshipsExercise 3a: Extract part of a dataset Exercise 3b: Incorporate tabular data Exercise 3c: Calculate data statistics Exercise 3d: Connect spatial datasetsChapter 4 Creating and editing spatial data Exercise 4a: Build a geodatabase Exercise 4b: Create features Exercise 4c: Modify featuresChapter 5 Facilitating workflows Exercise 5a: Manage a repeatable workflow using tasks Exercise 5b: Create a geoprocessing model Exercise 5c: Run a Python command and script toolChapter 6 Collaborative mapping Exercise 6a: Prepare a database for data collection Exercise 6b: Prepare a map for data collection Exercise 6c: Collect data using ArcGIS CollectorChapter 7 Geoenabling your projectExercise 7a: Prepare project data Exercise 7b: Geocode location data Exercise 7c: Use geoprocessing tools to analyze vector dataChapter 8 Analyzing spatial and temporal patternsExercise 8a: Create a kernel density map Exercise 8b: Perform a hot spot analysis Exercise 8c: Explore the results in 3D Exercise 8d: Animate the dataChapter 9 Determining suitability Exercise 9a: Prepare project data Exercise 9b: Derive new surfaces Exercise 9c: Create a weighted suitability modelChapter 10 Presenting your project Exercise 10a: Apply detailed symbology Exercise 10b: Label features Exercise 10c: Create a page layout Exercise 10d: Share your projectAppendix Image and data source credits Data license agreement GlossaryGetting to Know ArcGIS Pro 2.6 | Official Trailer | 2020-08-10 | 00:57

The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed. The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed. The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed. The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed.

Layer of the BTUNa (reference year 2021) containing the surface elements of the roads, tracks, paths and paths for the municipality of Pamplona at 1:500 scale. The BTUNa is an adaptation to the production of the Urban Topographic Base (BTU) of the National Geographic Institute (IGN). It is a data model agreed by the Autonomous Communities (ACs) and approved by the Superior Geographical Council (CSG) of which there is a v1 version dated 2008, although in Navarra an extended version (BTUNa) has been prepared.

The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed. The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed. The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed. The digital topographic maps are generated from digital landscape and terrain models as well as the official real estate register information system ALKIS and visualised according to the national ATKIS signature catalogue. They are available in a maximum of 23 content levels (according to the technical regulations of the AdV) in three forms (single layers, gray combination and color combination). The data are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. The raster data are divided into different levels according to cartographic content elements. They are delivered as single-coloured single layers (layers) and as colored combination outputs in a uniform resolution. In addition, the data in the standard sheet section (with map frame and legend) are offered as PDF and as a plotted card. They are available as web services, raster data and analog card prints (plots). When using the data, the license conditions must be observed.

This map is designed to be used as a general reference map for informational and educational purposes as well as a basemap by GIS professionals and other users for creating web maps and web mapping applications.The map was developed by National Geographic and Esri and reflects the distinctive National Geographic cartographic style in a multi-scale reference map of the world. The map was authored using data from a variety of leading data providers, including DeLorme, HERE, UNEP-WCMC, NASA, ESA, USGS, and others.This reference map includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings and landmarks, overlaid on shaded relief and land cover imagery for added context. The map includes global coverage down to ~1:144k scale and more detailed coverage for North America down to ~1:9k scale.Map Note: Although small-scale boundaries, place names and map notes were provided and edited by National Geographic, boundaries and names shown do not necessarily reflect the map policy of the National Geographic Society, particularly at larger scales where content has not been thoroughly reviewed or edited by National Geographic.Data Notes: The credits below include a list of data providers used to develop the map. Below are a few additional notes:Reference Data: National Geographic, Esri, DeLorme, HERE, INCREMENT P, NRCAN, METILand Cover Imagery: NASA Blue Marble, ESA GlobCover 2009 (Copyright notice: © ESA 2010 and UCLouvain)Protected Areas: IUCN and UNEP-WCMC (2011), The World Database on Protected Areas (WDPA) Annual Release. Cambridge, UK: UNEP-WCMC. Available at: www.protectedplanet.net.Ocean Data: GEBCO, NOAAExplore the Map: You can Explore the National Geographic Map using this live map presentation authored by Allen Carroll. Allen was formerly the Chief Cartographer at National Geographic and is currently part of the ArcGIS Online team at Esri.Web Map: Here's a ready-to-use web map that uses the National Geographic World Map as its basemap. Tip: Remember that you can open a web map, zoom in to a location of interest, then click the Share button to get a URL link or code you can embed in your own web page that launches the map at that location. This makes it really easy to share the web map with others showing the location of your choice. This doesn't even require that you sign-in to ArcGIS Online, so anyone can do it.Note: Boundaries and names shown do not necessarily reflect the map policy of the National Geographic Society.

Layer of the BTUNa (reference year 2021) containing the surface elements of the services, facilities and endowments for the municipality of Pamplona at 1:500 scale. The BTUNa is an adaptation to the production of the Urban Topographic Base (BTU) of the National Geographic Institute (IGN). It is a data model agreed by the Autonomous Communities (ACs) and approved by the Superior Geographical Council (CSG) of which there is a v1 version dated 2008, although in Navarra an extended version (BTUNa) has been prepared.