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Geospatial Data Types and their applications

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Geospatial Data Types and their applications

As part of my course curriculum related to MS in Analytics program, I had an opportunity to discuss about Geospatial data. I thought of sharing it with sas community. 


Per Anonymous (2016), Data are generated from observations and spatial data is derived from “observations with locations that are identified with features and positions on earth’s surface”.

There are two main categories of Geospatial data types that are:


Vector Spatial data type: Vector type consists of points, lines, and polygons or areas (when vertices are joined by lines with first and last points being same i.e., closed, they are called polygons). This type includes vertices and paths.


Raster Spatial data type: This type consists of pixels or grid cells similar to photographs. Pixels are typically (not necessarily) regularly spaced and square. In a Raster, each pixel represents a value or class.


An excellent blog post in Sensors and Systems publication from Pitts (2013), unique considerations, with examples of methods, and tools to use geospatial data are summarized in the following table:

Unique Consideration

Method & Tools



Geographic area of coverage with latitudes and longitudes which enables effective integration of datasets that are represented together and queried for later use

Geometry type and complexity influence spatial queries and analyses.

Spatial resolution and scale precision and scale of data displayed.

Hurricane Sandy that impacted east coast from National Weather Service (Figure 1 map in the Pitts (2013) article.


Access method deals with mechanism for accessing data for integration.

Format and size refer to encoding type (File format) and file size in megabytes (MB), gigabytes GB, for example.

Remote sources that could provide dataset for analysis could be File Transfer Protocol (FTP), for example.


Governmental policies, procedures, and regulations influence organizational plan and execution of geospatial data handling; so a method needs to be established for addressing it.


Cellular phone tower location map and their locations influence the health/hazard conditions and their proximity to residential areas for example.


Summary: At least since the beginning of early 2000’s, there has been much more appreciation, curiosity, and interest in the technology of geospatial information due to the advent of MapQuest, Google Maps, smart phones and Global Positioning Systems (GPS) providing directions to drive from point A to point B. Although, the topic seems complicated with latitudinal and longitudinal, vector, and raster graphics, it is ubiquitous in its presence for providing information about disease outbreak for example by Center for Disease Control (CDC). There are plenty of applications including but not limited to military, mobile communications, healthcare, tracking of suspects, and many more. Due to its wide ranging applications, it might be advantageous for us to be well versed and trained in geospatial technology along with sas data and procedural steps that process geospatial data.



Anonymous (2016) GIS spatial data types: Vector vs. Raster


Pitts, Robert (2013) Geospatial data integration challenges and considerations

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