Natural Earth is a public domain map dataset available at 1:10m, 1:50m, and 1:110 million scales (1:10m version is stored in the EEA-SDI). Featuring tightly integrated vector and raster data, with Natural Earth one can make a variety of visually pleasing, well-crafted maps with cartography or GIS software. Natural Earth was built through a collaboration of many volunteers and is supported by NACIS (North American Cartographic Information Society), and is free for use in any type of project. The carefully generalized linework maintains consistent, recognizable geographic shapes at 1:10m, 1:50m, and 1:110m scales. Natural Earth was built from the ground up in order for all data layers align precisely with one another. For example, where rivers and country borders are one and the same, the lines are coincident. Most data contain embedded feature names, which are ranked by relative importance. Other attributes facilitate faster map production, such as width attributes assigned to river segments for creating tapers.

Cultural vector data themes: + Countries + Disputed areas and breakaway regions + First order admin + Populated places + Urban polygons + Parks and protected areas

             + Pacific nation groupings

• Water boundary indicators

Physical vector data themes: + Coastline + Land

             + Ocean

• Minor islands
• Reefs
• Physical region features
• Rivers and lake centerlines
• Lakes + Glaciated areas
• Antarctic ice shelves
• Bathymetry
• Geographic lines
• Graticules

This is a subset of World Biomass Image Layer to focus on Central Asia and Caucasus Region. Use this web map to visualize and understand the Biomass for that region. Use image layer for your analysis. Plants play a central role in the carbon cycle by absorbing carbon dioxide from the atmosphere and incorporating it in the structure of the plant. Globally living plants contain 500 billion metric tons of carbon, more than 60 times the amount of carbon released to the atmosphere by humans each year. Understanding the distribution of the carbon stored in living plants, known as biomass, is key to estimating the effects of land use change on the climate.Dataset SummaryThis layer provides access to a 1-km cell-sized raster with data on the density of carbon stored in living plants in metric tons per hectare for the year 2000. It was published by the Oak Ridge National Laboratory Carbon Dioxide Information Analysis Center in 2008.The authors of these data request that they be cited as:Ruesch, Aaron, and Holly K. Gibbs. 2008. New IPCC Tier-1 Global Biomass Carbon Map For the Year 2000. Available online from the Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee.What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

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Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector, gover

Author: J. Cain, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 4Resource type: lessonSubject topic(s): mapsRegion: united statesStandards: Minnesota Social Studies Standards

Standard 2: People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context. Objectives: Students will be able to:

1. Explore a variety of maps.

2. Become acquainted with the elements of maps referred to as TODALS:

3. Title

4. Orientation

5. Date

6. Author

7. Legend (Key)

8. Scale

9. Locate and interpret TODALS from a variety of maps.

10. Compare and contrast elements of given maps while looking for bias.

11. Reflect on the importance of knowing TODALS when understanding and interpreting maps. Summary: Basic mapping terminology is essential for understanding and interpreting various types of maps. Knowing where to find these essential elements, and interpreting their meaning, are critical to the development of a 4th grader’s knowledge of geography.

The Geometrically Valuable Areas Signaling Map is a map showing a total overview of larger and smaller geologically interesting areas and elements in Zeeland. These areas are interesting because of landscape shape/history, soil type, current formation processes or special geology. The Earthly Valuable Areas Signaling Map forms the basis of provincial selection on the Earthly Valuable Area Map. However, the Signalering Map also contains areas that are not included in the provincial selection of geographically valuable areas but have a clear geographical and landscape significance.

This 1m Digital Terrain Model (DTM) is derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Surface Model (DSM), is a first-stop elevation layer. A processing report and readme file are included with this data release. The DTM is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

This 1m Digital Surface Model (DSM) is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

Map of the toponymy related to the coastal geography of the Valencian Community belonging to the collection of school maps. It is divided into two levels: level 1, with the most important place names and level 2, which also contains place names of a second level of importance. This map comes in two sizes, so that your print fits an A4 or A3 paper size. In case of A4 size, the map scale is 1:1.175.000. For the A3, it's 1:825,000. Mute map versions are also provided for all of the above.

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Digital Map Market Size 2025-2029

The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.

The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.

What will be the Size of the Digital Map Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.

Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.

How is this Digital Map Industry segmented?

The digital map industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Navigation
  Geocoders
  Others


Type

  Outdoor
  Indoor


Solution

  Software
  Services


Deployment

  On-premises
  Cloud


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Indonesia
    Japan
    South Korea


  Rest of World (ROW)

By Application Insights

The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.

Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance applications,

Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

Through National Geographic Funding, AmericaView helped facilitate geography education and understanding in the Four Corners region of the United States. The FlyHigh4Geo program was designed to engage students through interactive and inexpensive learning tools that focus on the use of remote sensing and Earth observation to gain an appreciation for local geography and culturally important areas; develop map reading/making skills; and establish a foundation for future geographic learning.

Through National Geographic Funding, AmericaView helped facilitate geography education and understanding in the Four Corners region of the United States. The FlyHigh4Geo program was designed to engage students through interactive and inexpensive learning tools that focus on the use of remote sensing and Earth observation to gain an appreciation for local geography and culturally important areas; develop map reading/making skills; and establish a foundation for future geographic learning.

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The mobile map market share is expected to increase by USD 6.73 billion from 2020 to 2025, and the market’s growth momentum will accelerate at a CAGR of 18.41%. This mobile map market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. The mobile map market report also offers information on several market vendors, including Alibaba Group Holding Ltd., Alphabet Inc., Apple Inc., CE Info. Pvt. Ltd., Environmental Systems Research Institute Inc., HERE Global BV, Microsoft Corp., NavInfo Co. Ltd., TomTom International BV, and Verizon Communications Inc. among others. Furthermore, this report extensively covers mobile map market segmentation by application (outdoor mobile map and indoor mobile map), end-user (automotive navigation, mobile and internet, and public sector and enterprise), and geography (APAC, North America, Europe, South America, and MEA).

What will the Mobile Map Market Size be During the Forecast Period?

Download the Free Report Sample to Unlock the Mobile Map Market Size for the Forecast Period and Other Important Statistics

Mobile Map Market: Key Drivers, Trends, and Challenges

Based on our research output, there has been a positive impact on the market growth during and post COVID-19 era. The increasing adoption of technologically advanced mobile devices is notably driving the mobile map market growth, although factors such as threat from open-source platform may impede market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the mobile map industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key Mobile Map Market Driver

The increasing adoption of technologically advanced mobile devices is one of the primary factors driving the mobile map market growth. The growing penetration of advanced mobile devices has increased the use of location-based services (LBS). To support this, mobile device manufacturers are introducing new devices that can integrate location-based applications such as GPS-enabled applications. In addition, individuals rely on such devices to obtain information such as traffic updates, directions to nearby locations, and real-time information such as weather forecasts. All these GPS-based applications are built on digital maps. Furthermore, the growth in connected devices will drive the demand for mobile maps globally to enable seamless navigation.

Key Mobile Map Market Trend

The development of indigenous mapping systems is one of the major mobile map market trends. This trend is growing significantly in Brazil, Russia, China, and India. Governments are encouraging regional mobile map makers to develop mobile map solutions that are country-specific. This trend is further supported by advanced mapping technology, which can develop accurate 3D digital maps.

Key Mobile Map Market Challenge

The growing popularity of open-source solutions has an adverse effect on the net sales of commercial mobile map solutions. The inflated cost of mobile map solutions has increased the demand for open-source mobile map applications in the market, especially in emerging countries such as China and India. These nations consist of many SMEs that require mobile map solutions but do not have sufficient capital to invest in customized mobile map technology. Therefore, open-source mobile map solutions have become a preferred choice among them. Many automobile companies also prefer open-source mobile map solutions in their vehicles. Large companies, as a part of the cost reduction, now prefer using open-source mobile map solutions compared with commercial mobile map solutions.

This mobile map market analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2021-2025.

Who are the Major Mobile Map Market Vendors?

The report analyzes the market’s competitive landscape and offers information on several market vendors, including:

Alibaba Group Holding Ltd.
Alphabet Inc.
Apple Inc.
CE Info. Pvt. Ltd.
Environmental Systems Research Institute Inc.
HERE Global BV
Microsoft Corp.
NavInfo Co. Ltd.
TomTom International BV
Verizon Communications Inc.

This statistical study of the mobile map market encompasses successful business strategies deployed by the key vendors. The mobile mapping market is fragmented and the vendors are deploying growth strategies such as M&A activities to compete in the market.

To make the most of the opportunities and recover from post COVID-19 impact, market vendors should focus more on the growth prospects in the fast-growing segments

This 1m Digital Surface Model (DSM) shaded relief is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM shaded relief has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. This shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM dataset is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

The Marion County Board of County Commissioners (MCBCC) Interactive Map is a user-friendly, web-based mapping tool designed to help Marion County citizens easily access important geographic information about their community. This comprehensive platform offers numerous features, including property searches, zoning and land use data, public facility locations, transportation routes, and emergency services information. Maintained by the MCBCC, this map serves as a valuable resource for residents, businesses, and visitors, promoting greater understanding of local geography and enhanced community engagement.

Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials, and transportation, it has played an important role in the city’s settlement and development. The river valley has changed dramatically in the years since European settlement, particularly during the late nineteenth and early twentieth century, when the Lower Don River was straightened and channelized and the huge marsh at its mouth drained and filled. Today, the Lower Valley forms the foundation for one of the most densely populated areas in Canada, outlining as it does the eastern portion of Toronto’s downtown core and radiating residential areas. This project documents historical changes in the landscape of the Don River Valley. Drawing from the wide range of geographical information available for the Don River watershed (and the Lower Don in particular), including historical maps, geological maps, fire insurance plans, planning documents, and city directories, the project uses Geographic Information Systems software to place, compile, synthesize and interpret this information and make it more accessible as geospatial data and maps. The project is a work in progress. To date, we have scanned several dozen historical maps of Toronto and the Don River watershed, and compiled the following geospatial datasets: 1) changes to the river channel and shoreline of Toronto harbour, 1858-1918; 2) industrial development in the Lower Don River Watershed, 1857-1951 (as points, and in some cases polygons); 3) historical mill sites in the Don River Watershed, 1825; 18524) land ownership in the watershed, 1860 and 1878; and 4) points of interest in the watershed. In the future, we hope to expand the project to include data from other Toronto area watersheds and other parts of the city. The project was conducted through a collaboration between Jennifer Bonnell, a doctoral student in the History of Education program at the University of Toronto's Ontario Institute for Studies in Education (OISE/UT) - now at York University in the History Department and Marcel Fortin, the Geographic Information Systems (GIS) and Map Librarian at the University of Toronto's Map and Data Library. Financial and in-kind support was provided by the Network in Canadian History and Environment (NiCHE) and the University of Toronto Libraries. Valuable research support for the Points of Interest pages came from Lost Rivers, a community-based urban ecology organization focused on building public awareness of the City's river systems. Jordan Hale, a University of Toronto Geography student conducted much of the digitization and database work.This project could not have been completed without their skilled assistance and dedication.

Media Map is a configurable app template for displaying an interactive map with basic tools and a set of options for limiting map navigation. Designed to fit into small spaces on a web page or as a standalone app.Configurable OptionsUse Media Map to present content from a map and configure it using the following options:Support your map with descriptive text by including an info panel with a title and description, and/or a splash screen to help orient your audience and prime them to receive your message.Enable tools on the map including a legend, basemap toggle, overview map, etc.Keep your audience focused on what is important by configuring options for map navigation by choosing to include zoom buttons, bookmarks, search, defining min/max zoom levels, or preventing scrolling of the map.Enable the time slider to animate data change over time.Use custom CSS to customize the look and feel of the app.Use CasesCreate a simple app to allow users to navigate to predefined locations.Optimize your map for consumption on a mobile device by preventing map scrolling.Let your user choose between two basemaps to experience different perspectives on your phenomena.Sprinkle geography all over the web by adding a spatial component to your web page.Create a detailed local map with an overview to provide global context. Supported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.

Data RequirementsThis application has no data requirements. Get Started This application can be created in the following ways:

Click the Create a Web App button on this page Share a map and choose to Create a Web App On the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

The Law of 14 November 1996 implementing the City Recovery Pact (PRV) distinguished three levels of intervention: sensitive urban areas, urban revitalisation zones (ZRUs), urban free zones (ZFU). These three levels of intervention ZUS, ZRU and ZFU, characterised by devices of increasing importance, were intended to respond to different degrees of difficulties encountered in those neighbourhoods. Since then, the Planning Law for City and Urban Cohesion of 21 February 2014 has laid down (Article 5) the modalities for the reform of the priority geography of city policy. Two decrees issued in 2014 (No 2014-767 of 3 July 2014 and No 2014-1575 of 22 December 2014) set out these arrangements for the metropolis and for the ultramarine territories respectively. Thus, the national list of priority neighbourhoods of the city policy (Decrees n°2014-1750 and n° 2014-1751 of 30 December 2014) was produced and the national mapping of their perimeters was published. These perimeters replace sensitive urban areas (SEZs) and urban social cohesion contract (CUCS) neighbourhoods as of 1 January 2015.

The vast Canadian geography north of approximately 50° latitude is depicted on the map Northern Canada / Nord du Canada. This bilingual map is the latest in the Atlas of Canada's series of reference maps. The four million scale provides a detailed regional base of the north. An inset of the Labrador coast shows the cultural connection of Nunatsiavut to the Inuit of Nunavut. The map shows the populated places in the three territories, the northern areas of the provinces, and adjacent areas of Russia, Alaska, and Greenland. Major roads and railways are mapped along with a selection of airports and seaplane bases. Major ports are identified by showing cargo and/or ferry movements throughout the north. The map also has an economic focus with the addition of energy,mineral and metal resource extraction sites (mines, natural gas and crude oil fields) and major pipelines. Important to any understanding of the north is the physical geography. The map shows the relief, bathymetry, major glaciers, ice fields, a selection of mountain peaks, tree line, the limits of permanent polar sea ice, and just over 2900 named hydrographic and physical features. Also shown are national parks and other federal protected areas. The surveyed locations of the Magnetic North Pole are mapped from 1831 to 2011. Every effort has been made to ensure that the data is current to the period 2007 to 2011.

This data publication contains multiple maps of Puerto Rico scanned at 600 dots per inch: full map scans, scans clipped to mapped areas only, and georeferenced scans of 1:10,000-scale land-use maps from 1950-1951 that were produced by the Rural Land Classification Program of Puerto Rico, a project led by Dr. Clarence F. Jones of Northwestern University. These historical maps classified land use and land cover into 20 different classes, including 13 different types of crops, two classes of forests, four classes of grasslands and other areas, which is a general class for non-rural areas. This package includes maps from 76 out of the 78 municipalities of Puerto Rico, covering 422 quadrangles of a 443-quadrangle grid for mainland Puerto Rico. It excludes the island municipalities of Vieques and Culebra, Mona Island and minor outlying islands.The Rural Land Classification Program of Puerto Rico produced 430 1:10,000-scale maps. That program also produced one island-wide land-use map with more generalized delineations of land use. Previously, Kennaway and Helmer (2007) scanned and georeferenced the island-wide map, and they converted it to vector and raster formats with embedded georeferencing and classification. This data publication contains the higher-resolution maps, which will provide more precise historical context for forests. It will better inform management efforts for the sustainable use of forest lands and to build resilience and resistance to various future disturbances for these and other tropical forest landscapes.

The maps were scanned and georeferenced to help with the planning and application process for the USDA Forest Service (USDA) Forest Legacy Program, a competition-based program administered by the USDA Forest Service in partnership with State agencies to encourage the protection of privately owned forest lands through conservation easements or land purchases. Geospatial products and maps will also be used by personnel at the Department of Natural and Environmental Resources and partners in Non-Governmental Organizations working with the Forest Stewardship Program. This latter program provides technical assistance and forest management plans to private landowners for the conservation and effective management of private forests across the US. The information will provide local historical context on forest change patterns that will enhance the recommendations of forest management practices for private forest landowners. These data will also be useful for urban forest professionals to understand the land legacies as a basis for planning green infrastructure interventions.

Data depict the rural areas of Puerto Rico around 1951 and how they were classified by geographers then. Having it georeferenced allows managers, teachers, students, the public and scientists to compare how these classifications have changed throughout the years. It will allow more precise identification and mapping of the past land use of present forests, forest stand age, and the past juxtaposition of different land uses relative to each other. These factors can affect forest species composition, biodiversity and ecosystem services. Forest stand age, past land-use type and past disturbance type, forest example, help gauge current forest structure, carbon storage, or rates of carbon accumulation. Another example of how the maps are important is for understanding how watersheds have changed through time, which helps assess how forest ecosystem services related to hydrology evolve. These maps will also help gauge how the forests of Puerto Rico are responding to recent disturbances, and how past disturbances over a range of scales relate to these responses.For more information on the Rural Land Classification Program of Puerto Rico, generated maps, and the island-wide land-use map, please see Jones (1952), Jones and Berrios (1956), as well as Kennaway and Helmer (2007).