Geospatial data is any data that contains location information. Geographic information can come in a variety of forms &ndash geographic coordinates such as latitude and longitude, street addresses, and others – and can be captured by a variety of methods – GPS, IP addresses, LIDAR, historical records, digitization, and others. In short, if data can be placed on a map, it can be characterized as geospatial data.
Geospatial Data Models
There are two basic geospatial data models:
Geospatial data on its own is not very useful — it commonly comes in the form of CSV files, shapefiles, or file geodatabase feature classes. This raw data is only made useful after it is imported into a GIS software, which interprets the data and allows us to analyze and visualize it.
What we can do with geospatial data varies widely depending what the data represents and what we want to investigate using that data. For example, if we have a set of geospatial data that contains transaction locations for a U.S. business, we can visualize that data on a map and import U.S. Census figures to calculate how many purchases are coming from urban vs. rural areas, or we can analyze the data and highlight where customers are grouped vs. where they are spread out, or we can utilize a wide range of other analyses.
The possibilities are always plentiful when working with geospatial data, so it helps to have a well-defined question or goal before you start running analyses and visualizing your data.
All geospatial data has a coordinate system, or projection, that the data is stored in that ties the feature to a location related to the Earth's surface. When working with GIS projects that incorporate more than one layer of geospatial data, each layer must be visualized in the same coordinate system on a map. GIS software is designed to align geospatial data with different coordinate systems on the fly using complex calculations called transformations, however, it is best practice to convert all data in one project into the same coordinate system.
Coordinate systems, also known as map projections, are arbitrary designations for spatial data. Their purpose is to provide a common basis for communication about a particular place or area on the earth's surface. The most critical issue in dealing with coordinate systems is knowing what the projection is and having the correct coordinate system information associated with a dataset.
Geographic vs. Projected Coordinate Systems
Coordinate systems come in two forms:
Choosing a coordinate system is an important part of conducting geospatial analysis and managing your geospatial data with GIS software can help with this effort. Data often starts off in one coordinate system and will need to be projected, or transformed, to a different coordinate system in order to produce an accurate analysis. The primary goal when choosing a coordinate system is to minimize error and distortions for the analysis being performed or the visualization being produced. It also requires asking questions like:
These questions are a few of the more important questions to consider, but there could be more issues to consider depending on your analysis.