GIS stands for Geographic Information Systems. GIS can be thought of as a set of software tools for handling, combining, analyzing, and communicating about our world, particularly in the spatial dimension. Maps are a common product of working with GIS. GIS can be used to created spatial answers (maps) to spatial questions, but GIS can also provide non-spatial answers to questions. Furthermore, the tools necessary for map making and geographic analysis are commonly used with non-spatial data. Mathematical, design, and many other functions, are useful with spatial information, but can be applied to non-spatial data as well.
The software of GIS is often conflated (equated) with GIS. In my teaching, I spend more than half of my practical teaching with sofware from ESRI (environmental systems research institute, but the longer name is almost never used, we just say ehz-ree). The software I am currently teaching with is ArcGIS Pro, this software came after “desktop.” While I try to refer to the current software as “pro” and it’s predecessor as “desktop,” I might be less clear from time to time. There are other software packages out there, some are task focussed, such as GeoDa for spatial statistics and exploratory spatial data analysis. Such software, unless focussed on map layout and design, often have rudimentary mapping capabilities, and maps are created and designed in other software. Other offer similar breadth to Pro, such as QGIS (Q stands for Quantum), and could be worth checking out. In my home department we also teach a series of classes on Remote Sensing, a field focused on satellite observations of Earth. There are several software packages for remote sensing. As computer software and hardware improve the line between GIS and remote sensing is blurred and each is adopting tools and capacities of the other.
One way I like to think about mapping and GIS is to consider how LITTLE information we need for a particular question. A central concern of GIS is the representation of almost anything, spatially. Earth is complex, perhaps unimaginably so. Therefore, it is important to simplify, generalize, and focus how we represent reality and use that representation to answer our questions. We can think of models of reality as being composed of the building blocks, and the geometry of those blocks as the foundation on which GIS is built. There are two ways we represent reality in GIS, one is Raster (like an digital image, made up of rasters, another word for pixels) and one is Vector (points, lines, and polygons). In a coming chapter these two models will be explored in more detail, and their simplicity will be obscured.