Spatial Data

Learning Objective 2: Be able to identify different kinds of spatial data.

A Geographic Information System (GIS) works with data that is tied to a location on Earth. This type of data is often referred to as “spatial data”, “geospatial data”, or even “GIS data”, and is spatially referenced using location information — most commonly geographic coordinates. A GIS uses this location information to project a geospatial file into a virtual geographic space where it can then be visualized and manipulated. If your data’s locative information is in the form of text — for example, country/city names or street addresses — this can be made legible to a GIS with a few extra steps (see geocoding). You may have to create new columns and populate them with coordinate information.

Raster vs. Vector Data

There are 2 main types of geospatial data: vector and raster.

Raster data is data which is made up of pixels arranged in a grid, whereas vector data is made up of vertices and the paths between them that create geometries representing real-world features. If you’re working with continuous geospatial phenomena such as satellite imagery, topography, or climatic data (like rainfall or temperature), you’re likely using raster data. If you’re working with points, lines, or polygons, that’s likely vector data.

Vector Data

Each vector dataset will contain either points, lines, or polygons. However, a dataset can include multiple features (either points, lines, or polygons). For example, below are a handful of vector datasets, including Vancouver neighborhoods (polygons), city blocks (polygons), restaurants (points) and streets (lines). A GIS allows you to add multiple datasets, layer them on top of each other, and run calculations between them. For instance, in a GIS, you could load in the below datasets and then use spatial analysis tools to learn how many restaurants are within your neighborhood, or within 10 blocks of you.

In another example, below is a map consisting of three layers of vector data: cities (points), major roads (lines), and land/water (polygons). Cities, roads, land, and water are all different datasets consisting of vector data.

Each feature (each polygon, point, or line within a given dataset of points, lines, or polygons) contains various information such as a unique identifier, the area in square kilometers or length, the name, the population, etc. These attributes can be explored from within a GIS by opening what’s called the Attribute Table.

Raster Data

Rasters, on the other hand, can generally only store one value per pixel. This value could be a color representing different kinds of topography (think of the whites, greens, and browns representing different elevations in the image below) or the quantity of something like rainfall or temperature. Multiple rasters can be overlaid to generate a multi-part raster, but generally, each pixel of a single raster can store one value meaning your raster is showing one variable. You can also do math between raster layers, or run boolean operations to isolate all pixels that do or do not meet certain criteria. An example of this is Suitability Analysis.

In a GIS, you can convert raster data to vector data and vector data to raster data, and extract raster values to a vector dataset.

File Extensions

Spatial data have different file extensions that you may be used to. Raster data will often be TIF (aka TIFF) file and have the extention .tif or .tiff.

Vector data come in more diverse file formats. The Shapefile is an industry standard format with the extension .shp (and a host of “sidecar files” — be sure to keep them all together). Shapefiles store data in binary. Therefore, shapefiles are not legible to human eyes and can only be opened and visualized by a GIS. GeoJSON, on the other hand, stores vector data in .geojson files that can be opened in a code editor or online in geojson.io. From there, geoJSON can easily be parsed with human eyes.

See here for an exhaustive list of formats spatial data can take. Although the nuance of file formats might seem too detail oriented for an introduction to reference mapping, being aware of different spatial data types and formats will help you know what to download and troubleshoot why something may not be opening/working. If you have no prior experience with spatial data, this may be quite overwhelming right now. However, with a little bit of practical experience under your belt file formatting will quickly become common sense to you.