What are the Types of Geographic Information System Maps?

There are many different styles of GIS mapping, starting from heat maps to category maps to bubble maps, depending on the problem that has to be solved.

Fremont, CA: Without Geographic Information System (GIS) map data, monitoring change, making educated decisions, and detecting geospatial trends is simply not possible today. When it comes to portraying geophysical data about the planet on the screen in a dynamic and interactive form, a GIS map is a must-have tool. A GIS map frequently converts real-world geographical data into colored patterns or shapes because human eyes are programmed to respond to varied colors and shapes. This accelerates the processing of data, resulting in more timely and well-informed judgments.

Types of GIS maps:

Heat maps

The term "GIS heat map" is frequently misused to refer to quantity maps; however, it actually refers to a different mapping convention. A basic idea of "warmer" and "cooler" regions can help when the data you need to show on the map is extremely dense and mixed up, especially if you know that the hottest locations represent the densest concentration of the supplied quantity. Red is generally considered to represent heat, whereas blue is said to represent coolness.

Category maps

There's nothing like a category GIS map when you need to know exactly which parts of the map correspond to which data segment. This is till date, the most popular type of GIS mapping because it is the simplest to generate. A separate color is assigned to a certain category or attribute. As a consequence, you'll have a handy map of variously colored patches, each representing a different category.

Quantity maps

On a GIS quantity map, Color-coding is used, but different shades of the same color are used to show the variation in amounts of items depicted on the map. It's an ideal GIS mapping solution for seeing a large amount of detailed data spread out over a large area.

Cluster maps

Colors, forms, and labels are successfully mixed well together in this kind to cluster densely packed points of data together. In a nutshell, there are various points to show on the GIS map individually, thus they are merged into a single cluster point for ease.