![input gps tracks cartodb input gps tracks cartodb](https://help.gaiagps.com/hc/article_attachments/115015440727/quip_doc_9__1_.png)
Maps are the guiding force for us to explore the world, get to our destination every day, and have helped us explore and evolve our understanding of the world. I can’t imagine where we would be without maps today (both literally and figuratively!). The Folium library in Python helps us analyze the location and geospatial data with ease and lets us create interactive maps.Geospatial analysis is taking on an ever more important role in the industry.A ‘one-to-one’ dot density map, Snow plotted each recorded case of cholera and in an early example of spatial analysis, was able to determine that a high density of cases were clustered around a specific water pump, the source of the cholera outbreak.
![input gps tracks cartodb input gps tracks cartodb](https://www.bhphotovideo.com/images/images2500x2500/Bushnell_360305_BACK_TRACK_D_TOUR_GPS_RED_6_LANGUAGE_845235.jpg)
Both of these types of dot density map visualize the scatter of your data, which can provide insights into where instances of an occurrence are clustered.įun fact: One of the best known early applications of Location Intelligence was John Snow’s map of cholera patients in London in 1854. Some dot density maps are ‘one-to-one’ in which each dot represents a single occurrence or data point, or ‘one to many’ in which each dot represents a set of aggregated data, for example one dot may represent 100 individuals with a certain attribute. Dot density mapsĪ dot density map uses a dot to represent a feature or attribute in your data. Our Head of Cartography, Mamata Akella, has also provided some best practices for designing a powerful proportional symbol map.
![input gps tracks cartodb input gps tracks cartodb](https://www.bhphotovideo.com/images/images2500x2500/garmin_010_02029_00_edge_explore_gps_1428479.jpg)
Proportional symbol maps are extremely useful for clearly telling the story of your data, as in the above map, showing urban populations by country around the world.Īdditionally, with 4.5% of all people having some level of color-blindness, a proportional symbol map adds a level of accessibility to your visualization over some of the more color focused options. In the heat map below, drought conditions across the United States are visualized based on intensity, giving us a greater understanding of past and potential impact areas. Visualizing the intensity of occurrence using a heat map is a technique commonly used when tracking weather and natural phenomena, in which established borders and boundaries are less useful for understanding impact areas. This technique requires point geometries, as you are looking to map the frequency of an occurrence at a specific point. A heatmap uses color to represent intensity, though unlike a choropleth map, a heatmap does not use geographical or geo-political boundaries to group data. Heat mapsĪ heat map represents the intensity of an incident’s occurrence within a dataset. Established during the 2000 Presidential Election, when the protracted debate over results lead to choropleth maps being a staple of political news coverage, institutions gradually settled on the red as republican/blue as democrat color scheme to provide viewers with a common understanding regardless of their preferred news source. Let’s take a look at five thematic map visualization techniques that are particularly useful to decision makers, analysts, storytellers, and others who are looking to draw insights from their data, tell a powerful story, or gain a greater understanding of the world around us.įun Fact: the common use of red and blue to represent Republicans and Democrats respectively, is a modern phenomena. The methodology and the type of map that you want to create may be different, for example, if you are exploring global shipping data or voter propensity, or environmental disaster impact. There are a number of visualization techniques and thematic map types that have different applications depending on the type of data that you are exploring and the type of spatial analysis that you are looking to do. Thematic maps pull in attributes or statistics about a location and represent that data in a way that enables a greater understanding of the relationships between locations and the discovery of spatial patterns in the data that we are exploring. Unlike reference maps, which tell us where something is, thematic maps tell us how something is. As our understanding of Location Intelligence and its applications across the public and private sector grows, thematic maps are becoming a more critical part of any professional’s toolkit.