In these examples, demographic estimates are calculated using billions of inputs from numerous data sources to provide daytime demographic estimates with unprecedented accuracy.
In addition to maps, additional visualizations like charts and graphs can interact with each other in a dashboard style interface. In this example, as the user moves the map, the scatter plot redraws to only show the records within the bounds of the map view. This example dynamically queries and renders 2.5 million records as a heat map style scatter plot and also as a map.
Combine any number of maps on a page to analyze multiple variables in the same geography. As you pan, zoom or click on one map, the other maps will take the same action.
This demo enables analysts to find concentrations of disease outbreaks around the world and how they might be spread via air travel. Query for a disease and the map will dynamically update to only display concentrations of that disease. Analysts can also discover the relationship between an airport and all airports connected by direct flights. Once an area has been selected for analysis, analysts can view demographics about the area to find populations which may be affected by the disease.
This example shows the seismic activity in the 7 days leading up to 3-11-2011 earthquake in Japan.
Dementia Mapping
This example highlights the ability to discover patterns in health data. It also shows a unique style of on-hover balloon which conveys multiple attributes through one image.
This tool uses data from the FDIC to measure bank performance. Analysts can look at the geographical distribution of bank branch networks to study patterns. Here, analysts can view banks as individual points or dynamically aggregated into shapes such as zip codes and counties.
Use geographic proximity analysis to determine a score for each bank branch based on the performance of its peers in the 3 or 5 mile areas surrounding the bank. Individual banks can be analyzed or dynamically aggregated into shapes such as zip codes and counties.
Use geographic proximity analysis to determine a score for each bank branch based on the performance of its peers in the 3 or 5 mile areas surrounding the bank. Individual banks can be analyzed or dynamically aggregated into shapes such as zip codes and counties.
This example shows how organizations can leverage their data to convey a public message. AIDSVu is an interactive online map providing a unique view of the HIV/AIDS epidemic in the United States. With a substantial number of variables to map, the MapLarge API makes changes to data seemless since every map query is dynamically generated on the fly.
The FCC provides information about every communications tower in the US. Companies can append or supply their own coverage and asset information. In this example, analysts can dynamically filter the tower locations by height.