Visualization Engine

Impress with Stunning Visuals

Cluster Maps

Managing Large Data Sets

Information-rich maps are a valuable tool for showing important relationships, identifying business trends, and illustrating opportunities. However, plotting thousands or millions of markers on a map can quickly lead to visual overload and impede analysis. When a map has too many points to convey a clear meaning, the information needs to be simplified. Reducing the amount of points on the map can be accomplished by grouping points by certain criteria and displaying with different colors and sizes, icons, placement rules, and more . MapLarge's clustering options offer a variety of choices for interpreting and presenting large data sets.

Organized vs Cluttered

The cluster map below has organized hotels in the Orlando area into numbered groups. It only takes a second to figure out how many hotels are in each location around the city. The point map shows every hotel in the same area. With all the points overlapping it is hard to distinguish exactly how many hotels are in each location without zooming in on the map.

Click on either map for a demo.

Clustering

Hotels locations are easy to find and there is a count in each marker showing how many hotels are around the specified location.

Point Map

With so many dots covering each other, it is difficult to see exactly how many hotels are in a particular location.

Types of Clustering

Cluster Griddy

The map is divided into squares of a certain size and the cluster marker is placed in the center of each applicable grid square. As zoom levels change so do the clusters and their location on the map but they will maintain their grid like appearance.

Cluster Natural

Clusters have a natural appearance on the map. Location is used to control placement within the clustering grid. The original x,y map location of the cluster's founding data point is used for the location.

Cluster Vary Size

Cluster design can be fun and interesting. Different colors, shapes, and icons are useful for emphasizing clusters on the map. Clusters with a higher number count will stand out if given a larger size or a brighter color. This map of Orlando gives the potential visitor an idea of how many hotels are available in the area and where the more expensive hotels are located.

Cluster External Icons

MapLarge provides a suite of design options for map icons but also offers the option to use external icons. Simply include the url to an external icon and it will appear on the map.

Cluster SnapToTable

The SnapToTable option will place the cluster point on or near the closest large city in the grid area. This demo shows clusters of hotels around large cities in the Northeast.

Overview
heat
choropleth
logical network
network
clustering
point in poly
synchronized
annotate editable

Data Visualization Mapping Software

Detecting patterns in Big Data is a challenge when viewing aggregate data. With MapLarge, analysts can view much higher resolutions leading to greater insights in less time. Users can query against any combination of dimensions and visualize their data instantly.

Heat Maps

A visual representation of data using colors. Heat maps can be used with many types of data, from representing the number of foreclosures to the spreads of infectious diseases.

Learn more
Heat Maps

Choropleth Maps

Choropleth maps provide an easy way to visualize how a measurement varies across a geographic area. Polygons are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map.

Learn more
choropleth maps

Logical Network Graphs

Logical network graphs can be used to model  relations and processes in physical, biological, social and information systems. Graphs are created by using a dot or circle for every vertex and by drawing an arc between two vertices if they are connected by an edge.

Learn more
Logical network graphs

Network Graphs

Network graphs are used for spatial analysis, such as routing, fleet routing, travel directions, closest facility, and service area. Use an advanced network data model to allow for realistic network conditions.

learn more
network graphs

Clustering

Simplify data visualization by combining data that are nearby each other on the map and display as a cluster. Useful for identifying the locations of statistically significant hot spots, cold spots, or spatial outliers.

learn more
clustering

Point In Poly Maps

Point-in-polygon maps help determine whether a given point in the plane lies inside, outside, or on the boundary of a polygon. Analyze delivery zones or identify potential customers in target markets.

learn more
point in poly maps

Synchronized Maps

Synchronize multiple maps. Zoom in or out on one map and the other maps will also zoom in or out. Synchronize a map with a chart and as the map is changed with onclick or onhover events, the chart will change in unison.

learn more
synchronized maps

Annotate Editable Maps

Make annotations and draw on the map with various shapes and lines. Annotations are useful to call out specific addresses, points of interest, and other types of destinations. Highlight focus or marketing areas by drawing circles or rectangles.

learn more
annotate editable maps

Heat Maps

Powerful Visualization

Heat maps are graphical displays representing a group of data. Color is used to communicate relationships between data values that would be much harder to understand if presented numerically in a spreadsheet. These maps are well-suited for visualizing large amounts of multi-dimensional data and can be used to identify clusters of rows with similar values, or finding highs and lows. Visualization using a heat map presents a big picture, but also allows individual pieces of data to be placed in the context of all the data. In an instant, you can spot a weather formation and judge the threat of an approaching storm or see the wealth distribution across the United States. Massive data sets can be communicated and clearly understood in a short amount of time.

How Heat Maps Work

The example below illustrates how the values in the table are displayed as color gradients on the heat map.

Benefits of Using Heat Maps

Heat maps use cell size and color to display complex information in an intelligible way. Multiple rows of data are assigned different sizes and colors based on rules or ranges.

  • Visualize Data
  • Understand the Landscape
  • Identify Growth Potential
  • Mitigate Risks
  • Manage Business
  • Construct Realistic Business Plans
  • Perform Channel Optimization
  • Weather and Climate Forecasts
  • And many more

Choropleth Maps

More Value with Visualization

Choropleth maps display quantitative data as a color, shading, or pattern and can show density, percent, average value or quantity of an event within a geographic area. Sequential colors on these maps represent increasing or decreasing positive or negative data values. Generally, each color represents a range of values with the most intense color being the highest and least intense color being the lowest. Choropleth maps can show the geographic distribution of a single variable, or the relationship between two or more variables. Data sets, such as population, ethnicity, income, language, political preference, annual rainfall, religion, etc, are easily visualized on a choropleth map. Analysis of data and presentation of data are common usages for these types of maps along with quick observation of patterns and variation.

Constructing a Choropleth Map

When creating a choropleth map, data is first put into classes or categories that are represented on the map by grades of color or shading. The greater the density of color or shading, the greater the density or value represented. In this map, counties are colored by age groups with the oldest age group being dark green and the lightest group being white. From the map, we can quickly see there is a large concentration of young people around Utah and northern Arizona. While such generalization may mask detail, it allows for quick observation of patterns and variation, and provides a basis for posing analytical questions.

Popular Use of Choropleth Maps:

Heat maps use cell size and color to display complex information in an intelligible way. Multiple rows of data are assigned different sizes and colors based on rules or ranges.

  • Proposals
  • Research Documentation
  • Marketing Literature
  • Annual Reports
  • Political Campaigns
  • Media
  • Health Trends
  • Crime Statistics
  • Housing Trends

Logical Network Graphs

Enhanced Visualization

Empower analysts to visualize and dynamically query multiple complex datasets at a scale using coordinated analysis between map, graph, list and time sliders. Graph relationships can be used to quickly identify important regions of the network containing relevant information. Determine information flows and analyze different layers in the network. Communities of interest and other emergent clustering patterns are represented in an intuitive visual fashion using familiar mapping paradigms for nonspatial logical graph data.

What are Logical Networks?

Logical networks are an abstract representation of a network. These networks are not dependent on geometry or location of the elements. Social networks, biological networks, and information networks are examples of logical networks. The structure consists of individuals called “nodes”, which are connected by one or more specific types of interdependence, such as friendship, family, common interest, relationships of beliefs, popularity or social status. There can be many kinds of connections between the nodes.

MapLarge's high-level graphing and analytical functions make it easy to explore networks, detect communities, find cohesive groups, visualize the results, and provide recommendations based on results.

Popular Use of Choropleth Maps:

Heat maps use cell size and color to display complex information in an intelligible way. Multiple rows of data are assigned different sizes and colors based on rules or ranges.

  • Exploratory Data Analysis: intuition-oriented analysis by networks manipulations in real time.
  • Link Analysis: revealing the underlying structures of associations between objects, in particular in scale-free networks.
  • Social Network Analysis: easy creation of social data connectors to map community organizations and small-world networks.
  • Biological Network analysis: representing patterns of biological data.

Network Graphs

Generate Network Graphs with MapLarge Mapping Software

Graphs are a powerful visual tool used to display and analyze sophisticated networks. Very complex and valuable questions can be answered in real time with network graphs while colors, design elements and format can all be customized to enhance visualization. Network graphs can be used to create dynamic network data models, to identify patterns and relationships, to locate trends in performance, to optimize routing, and to share information with millions of users simultaneously.

Visualize and Analyze Large Networks

Directly and indirectly networks pervade our daily lives. Most of us are dependent on technological networks, energy networks, and biological networks. We expect our cell phones to work when we need to make a call and we rely on electricity to use our computers, watch tv, and keep our food cold in the refrigerator. Many of us choose to participate in social networks and use information networks for almost instantaneous answers to a multitude of questions. Facebook, Twitter, LinkedIn, and Wikipedia have become household names.

With all these networks generating useful and marketable information, analysts need a way to harness and evaluate this data to make effective decisions. Graphs are a powerful visual tool used to display and analyze sophisticated networks. Very complex and valuable questions can be answered in real time with network graphs while colors, design elements and format can all be customized to enhance visualization. Network graphs can be used to create dynamic network data models, to identify patterns and relationships, to locate trends in performance, to optimize routing, and to share information with millions of users simultaneously.

Physical Network Graphs

MapLarge provides network-based spatial analysis, such as routing, fleet routing, travel directions, closest facility, and service area. Develop networks from your GIS data by using an advanced network data model allowing for realistic network conditions.

Physical Network Graph Examples

  • Find shortest routes.
  • Produce the most efficient routes for a fleet of vehicles that must visit many locations.
  • Use time windows to limit when vehicles can arrive at locations.
  • Locate closest facilities.
  • Determine optimal locations for facilities by performing a location-allocation analysis.
  • Define service areas based on travel time or distance.
  • Create a network using your existing GIS data.
  • Generate a matrix of network travel costs from each origin to all destinations.

Cluster Maps

Managing Large Data Sets

Information-rich maps are a valuable tool for showing important relationships, identifying business trends, and illustrating opportunities. However, plotting thousands or millions of markers on a map can quickly lead to visual overload and impede analysis. When a map has too many points to convey a clear meaning, the information needs to be simplified. Reducing the amount of points on the map can be accomplished by grouping points by certain criteria and displaying with different colors and sizes, icons, placement rules, and more . MapLarge's clustering options offer a variety of choices for interpreting and presenting large data sets.

Organized vs Cluttered

The cluster map below has organized hotels in the Orlando area into numbered groups. It only takes a second to figure out how many hotels are in each location around the city. The point map shows every hotel in the same area. With all the points overlapping it is hard to distinguish exactly how many hotels are in each location without zooming in on the map.

Click on either map for a demo.

Clustering

Hotels locations are easy to find and there is a count in each marker showing how many hotels are around the specified location.

Point Map

With so many dots covering each other, it is difficult to see exactly how many hotels are in a particular location.

Types of Clustering

Cluster Griddy

The map is divided into squares of a certain size and the cluster marker is placed in the center of each applicable grid square. As zoom levels change so do the clusters and their location on the map but they will maintain their grid like appearance.

Cluster Natural

Clusters have a natural appearance on the map. Location is used to control placement within the clustering grid. The original x,y map location of the cluster's founding data point is used for the location.

Cluster Vary Size

Cluster design can be fun and interesting. Different colors, shapes, and icons are useful for emphasizing clusters on the map. Clusters with a higher number count will stand out if given a larger size or a brighter color. This map of Orlando gives the potential visitor an idea of how many hotels are available in the area and where the more expensive hotels are located.

Cluster External Icons

MapLarge provides a suite of design options for map icons but also offers the option to use external icons. Simply include the url to an external icon and it will appear on the map.

Cluster SnapToTable

The SnapToTable option will place the cluster point on or near the closest large city in the grid area. This demo shows clusters of hotels around large cities in the Northeast.

Synchronized Maps

Visual Comparisons

Valuable insights can be discovered by visualizing maps side-by-side and synchronizing them. Detecting changes, making comparisons, or studying relationships becomes easier when the maps are in the same viewing area. Synchronizing the maps helps keep the focus area in perspective and supports detailed analysis. The maps to the right are placed side by side to explore how the rate of AIDS compares to the % of the population living in poverty in various parts of the country. As you zoom in or out on one map, the other map also zooms in or out so the maps stay focused on the same area.

How Synchronized Maps Work

Synchronizing maps causes them to move together at exactly the same rate and time. This allows for an accurate geospatial relationship whether the map is zoomed in/out or moved to a different location. It is possible to synchronize as many maps as necessary to provide adequate visual information. In the example below, four maps are synchronized to show candidate support during an election year. The map in the top left is Obama, the top right is McCain, the bottom left is Clinton, and the bottom right is Romney. As you zoom in, the four maps zoom in to the same location. Click on the maps to try the demo.

Benefits of Using Synchronized Maps

  • Generate New Insights
  • Identify New Opportunities
  • Analyzing Location and Demographic Data
  • Business Planning
  • Manage Materials, Supplies, Human resources, and Logistics
  • Accurate Visual Comparisons
  • Multiple Weather and Climate Forecasts

Annotate and Edit

interaction Visualization

Maps are a powerful tool for conveying information about geographic features, locations, and relationships, but sometimes this is not enough to communicate an important message. Adding markers, paths, shapes, and annotations to a map improves the visualization of spatial information and can highlight a specific area or provide more insight into data sets.

Accentuate Specific Coordinates

Annotations offer an easy way to accentuate specific coordinates on the map and provide additional information about them. Identify particular addresses, businesses, airports, and other types of destinations. Overlays are available to present more complex information such as routes or traffic information, or the boundaries of areas such as parks, lakes, cities, states, or countries. Both annotations and overlays remain fixed to the map so that they move appropriately when the user zooms, pans, or scrolls. Descriptive text can be placed near individual map features. The name of each major city in the US or large universities can be added to the map. Attractive fonts and colored text can be used to draw attention to an area of the map, such as the general location of Yellowstone National Park or The Grand Canyon. Improve presentation of the map with a map title to provide context along with other information such as map author, data source, and date.

Benefits of Annotatable/Editable Maps

  • Visualize Data
  • Understand the Landscape
  • Identify Growth Potential
  • Mitigate Risks
  • Manage Business
  • Construct Realistic Business Plans
  • Perform Channel Optimization
  • Weather and Climate Forecasts
  • And many more
Overview
heat
choropleth
logical network
network
clustering
point in poly
synchronized
annotate editable

Data Visualization Mapping Software

Heat Maps

A visual representation of data using colors. Heat maps can be used with many types of data, from representing the number of foreclosures to the spreads of infectious diseases.

Learn more
Heat Maps

Choropleth Maps

Choropleth maps provide an easy way to visualize how a measurement varies across a geographic area. Polygons are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map.

Learn more
choropleth maps

Logical Network Graphs

Logical network graphs can be used to model  relations and processes in physical, biological, social and information systems. Graphs are created by using a dot or circle for every vertex and by drawing an arc between two vertices if they are connected by an edge.

Learn more
Logical network graphs

Network Graphs

Network graphs are used for spatial analysis, such as routing, fleet routing, travel directions, closest facility, and service area. Use an advanced network data model to allow for realistic network conditions.

learn more
network graphs

Clustering

Simplify data visualization by combining data that are nearby each other on the map and display as a cluster. Useful for identifying the locations of statistically significant hot spots, cold spots, or spatial outliers.

learn more
clustering

Point In Poly Maps

Point-in-polygon maps help determine whether a given point in the plane lies inside, outside, or on the boundary of a polygon. Analyze delivery zones or identify potential customers in target markets.

learn more
point in poly maps

Synchronized Maps

Synchronize multiple maps. Zoom in or out on one map and the other maps will also zoom in or out. Synchronize a map with a chart and as the map is changed with onclick or onhover events, the chart will change in unison.

learn more
synchronized maps

Annotate Editable Maps

Make annotations and draw on the map with various shapes and lines. Annotations are useful to call out specific addresses, points of interest, and other types of destinations. Highlight focus or marketing areas by drawing circles or rectangles.

learn more
annotate editable maps

Heat Maps

Powerful Visualization

Heat maps are graphical displays representing a group of data. Color is used to communicate relationships between data values that would be much harder to understand if presented numerically in a spreadsheet. These maps are well-suited for visualizing large amounts of multi-dimensional data and can be used to identify clusters of rows with similar values, or finding highs and lows. Visualization using a heat map presents a big picture, but also allows individual pieces of data to be placed in the context of all the data. In an instant, you can spot a weather formation and judge the threat of an approaching storm or see the wealth distribution across the United States. Massive data sets can be communicated and clearly understood in a short amount of time.

How Heat Maps Work

The example below illustrates how the values in the table are displayed as color gradients on the heat map.

Benefits of Using Heat Maps

Heat maps use cell size and color to display complex information in an intelligible way. Multiple rows of data are assigned different sizes and colors based on rules or ranges.

  • Visualize Data
  • Understand the Landscape
  • Identify Growth Potential
  • Mitigate Risks
  • Manage Business
  • Construct Realistic Business Plans
  • Perform Channel Optimization
  • Weather and Climate Forecasts
  • And many more

Choropleth Maps

More Value with Visualization

Choropleth maps display quantitative data as a color, shading, or pattern and can show density, percent, average value or quantity of an event within a geographic area. Sequential colors on these maps represent increasing or decreasing positive or negative data values. Generally, each color represents a range of values with the most intense color being the highest and least intense color being the lowest. Choropleth maps can show the geographic distribution of a single variable, or the relationship between two or more variables. Data sets, such as population, ethnicity, income, language, political preference, annual rainfall, religion, etc, are easily visualized on a choropleth map. Analysis of data and presentation of data are common usages for these types of maps along with quick observation of patterns and variation.

Constructing a Choropleth Map

When creating a choropleth map, data is first put into classes or categories that are represented on the map by grades of color or shading. The greater the density of color or shading, the greater the density or value represented. In this map, counties are colored by age groups with the oldest age group being dark green and the lightest group being white. From the map, we can quickly see there is a large concentration of young people around Utah and northern Arizona. While such generalization may mask detail, it allows for quick observation of patterns and variation, and provides a basis for posing analytical questions.

Popular Use of Choropleth Maps:

Heat maps use cell size and color to display complex information in an intelligible way. Multiple rows of data are assigned different sizes and colors based on rules or ranges.

  • Proposals
  • Research Documentation
  • Marketing Literature
  • Annual Reports
  • Political Campaigns
  • Media
  • Health Trends
  • Crime Statistics
  • Housing Trends

Logical Network Graphs

Enhanced Visualization

Empower analysts to visualize and dynamically query multiple complex datasets at a scale using coordinated analysis between map, graph, list and time sliders. Graph relationships can be used to quickly identify important regions of the network containing relevant information. Determine information flows and analyze different layers in the network. Communities of interest and other emergent clustering patterns are represented in an intuitive visual fashion using familiar mapping paradigms for nonspatial logical graph data.

What are Logical Networks?

Logical networks are an abstract representation of a network. These networks are not dependent on geometry or location of the elements. Social networks, biological networks, and information networks are examples of logical networks. The structure consists of individuals called “nodes”, which are connected by one or more specific types of interdependence, such as friendship, family, common interest, relationships of beliefs, popularity or social status. There can be many kinds of connections between the nodes.

MapLarge's high-level graphing and analytical functions make it easy to explore networks, detect communities, find cohesive groups, visualize the results, and provide recommendations based on results.

Popular Use of Choropleth Maps:

Heat maps use cell size and color to display complex information in an intelligible way. Multiple rows of data are assigned different sizes and colors based on rules or ranges.

  • Exploratory Data Analysis: intuition-oriented analysis by networks manipulations in real time.
  • Link Analysis: revealing the underlying structures of associations between objects, in particular in scale-free networks.
  • Social Network Analysis: easy creation of social data connectors to map community organizations and small-world networks.
  • Biological Network analysis: representing patterns of biological data.

Network Graphs

Generate Network Graphs with MapLarge Mapping Software

Graphs are a powerful visual tool used to display and analyze sophisticated networks. Very complex and valuable questions can be answered in real time with network graphs while colors, design elements and format can all be customized to enhance visualization. Network graphs can be used to create dynamic network data models, to identify patterns and relationships, to locate trends in performance, to optimize routing, and to share information with millions of users simultaneously.

Visualize and Analyze Large Networks

Directly and indirectly networks pervade our daily lives. Most of us are dependent on technological networks, energy networks, and biological networks. We expect our cell phones to work when we need to make a call and we rely on electricity to use our computers, watch tv, and keep our food cold in the refrigerator. Many of us choose to participate in social networks and use information networks for almost instantaneous answers to a multitude of questions. Facebook, Twitter, LinkedIn, and Wikipedia have become household names.

With all these networks generating useful and marketable information, analysts need a way to harness and evaluate this data to make effective decisions. Graphs are a powerful visual tool used to display and analyze sophisticated networks. Very complex and valuable questions can be answered in real time with network graphs while colors, design elements and format can all be customized to enhance visualization. Network graphs can be used to create dynamic network data models, to identify patterns and relationships, to locate trends in performance, to optimize routing, and to share information with millions of users simultaneously.

Physical Network Graphs

MapLarge provides network-based spatial analysis, such as routing, fleet routing, travel directions, closest facility, and service area. Develop networks from your GIS data by using an advanced network data model allowing for realistic network conditions.

Physical Network Graph Examples

  • Find shortest routes.
  • Produce the most efficient routes for a fleet of vehicles that must visit many locations.
  • Use time windows to limit when vehicles can arrive at locations.
  • Locate closest facilities.
  • Determine optimal locations for facilities by performing a location-allocation analysis.
  • Define service areas based on travel time or distance.
  • Create a network using your existing GIS data.
  • Generate a matrix of network travel costs from each origin to all destinations.

Cluster Maps

Managing Large Data Sets

Information-rich maps are a valuable tool for showing important relationships, identifying business trends, and illustrating opportunities. However, plotting thousands or millions of markers on a map can quickly lead to visual overload and impede analysis. When a map has too many points to convey a clear meaning, the information needs to be simplified. Reducing the amount of points on the map can be accomplished by grouping points by certain criteria and displaying with different colors and sizes, icons, placement rules, and more . MapLarge's clustering options offer a variety of choices for interpreting and presenting large data sets.

Organized vs Cluttered

The cluster map below has organized hotels in the Orlando area into numbered groups. It only takes a second to figure out how many hotels are in each location around the city. The point map shows every hotel in the same area. With all the points overlapping it is hard to distinguish exactly how many hotels are in each location without zooming in on the map.

Click on either map for a demo.

Clustering

Hotels locations are easy to find and there is a count in each marker showing how many hotels are around the specified location.

Point Map

With so many dots covering each other, it is difficult to see exactly how many hotels are in a particular location.

Types of Clustering

Cluster Griddy

The map is divided into squares of a certain size and the cluster marker is placed in the center of each applicable grid square. As zoom levels change so do the clusters and their location on the map but they will maintain their grid like appearance.

Cluster Natural

Clusters have a natural appearance on the map. Location is used to control placement within the clustering grid. The original x,y map location of the cluster's founding data point is used for the location.

Cluster Vary Size

Cluster design can be fun and interesting. Different colors, shapes, and icons are useful for emphasizing clusters on the map. Clusters with a higher number count will stand out if given a larger size or a brighter color. This map of Orlando gives the potential visitor an idea of how many hotels are available in the area and where the more expensive hotels are located.

Cluster External Icons

MapLarge provides a suite of design options for map icons but also offers the option to use external icons. Simply include the url to an external icon and it will appear on the map.

Cluster SnapToTable

The SnapToTable option will place the cluster point on or near the closest large city in the grid area. This demo shows clusters of hotels around large cities in the Northeast.

Synchronized Maps

Visual Comparisons

Valuable insights can be discovered by visualizing maps side-by-side and synchronizing them. Detecting changes, making comparisons, or studying relationships becomes easier when the maps are in the same viewing area. Synchronizing the maps helps keep the focus area in perspective and supports detailed analysis. The maps to the right are placed side by side to explore how the rate of AIDS compares to the % of the population living in poverty in various parts of the country. As you zoom in or out on one map, the other map also zooms in or out so the maps stay focused on the same area.

How Synchronized Maps Work

Synchronizing maps causes them to move together at exactly the same rate and time. This allows for an accurate geospatial relationship whether the map is zoomed in/out or moved to a different location. It is possible to synchronize as many maps as necessary to provide adequate visual information. In the example below, four maps are synchronized to show candidate support during an election year. The map in the top left is Obama, the top right is McCain, the bottom left is Clinton, and the bottom right is Romney. As you zoom in, the four maps zoom in to the same location. Click on the maps to try the demo.

Benefits of Using Synchronized Maps

  • Generate New Insights
  • Identify New Opportunities
  • Analyzing Location and Demographic Data
  • Business Planning
  • Manage Materials, Supplies, Human resources, and Logistics
  • Accurate Visual Comparisons
  • Multiple Weather and Climate Forecasts

Annotate and Edit

interaction Visualization

Maps are a powerful tool for conveying information about geographic features, locations, and relationships, but sometimes this is not enough to communicate an important message. Adding markers, paths, shapes, and annotations to a map improves the visualization of spatial information and can highlight a specific area or provide more insight into data sets.

Accentuate Specific Coordinates

Annotations offer an easy way to accentuate specific coordinates on the map and provide additional information about them. Identify particular addresses, businesses, airports, and other types of destinations. Overlays are available to present more complex information such as routes or traffic information, or the boundaries of areas such as parks, lakes, cities, states, or countries. Both annotations and overlays remain fixed to the map so that they move appropriately when the user zooms, pans, or scrolls. Descriptive text can be placed near individual map features. The name of each major city in the US or large universities can be added to the map. Attractive fonts and colored text can be used to draw attention to an area of the map, such as the general location of Yellowstone National Park or The Grand Canyon. Improve presentation of the map with a map title to provide context along with other information such as map author, data source, and date.

Benefits of Annotatable/Editable Maps

  • Visualize Data
  • Understand the Landscape
  • Identify Growth Potential
  • Mitigate Risks
  • Manage Business
  • Construct Realistic Business Plans
  • Perform Channel Optimization
  • Weather and Climate Forecasts
  • And many more

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