Glossary of Geospatial Terms
Glossary of Geospatial Terms

Do you find it hard to find one, cohesive place to understand the fundamentals of the geospatial domain? Well, you’re not alone. I am here to make it happen for you in very simple English — a glossary of some of the most complicated aspects of the geospatial genre.

Spatial vs Geospatial

Spatial means space, so it is related to space and the position, size, shape, etc. of a particular object (any object, not only on the Earth’s 🌍 surface).

Geospatial means the distribution of something in a geographic sense; it refers to entities that can be located by some coordinate system 🌐.

Geospatial is that type of spatial data which is related to the Earth’s surface and/or near Earth’s surface.

Vector data vs Raster data

Vector data is used to present generalizations of objects or features on the Earth’s surface. There are three main types of vector data: points, lines, and polygons.

Raster data is the data taken from satellite 🛰images or any other aerial device images.

In addition to raster and vector data, there is also LiDAR data (also known as 3D data). 3D data is data that extends the typical latitude and longitude 2-D coordinates and incorporates elevation and or depth into the data.

Vector geometry objects

a) Point:

It is the exact positioning of a real-world geographical area and is represented by a pair of longitude and latitude collectively known as coordinates. Example: [77.59199, 12.99864]

Point geometry object (Grey)

b) Multipoint:

Two or more points in space are called multipoint. Example:

Multipoint geometry object (Grey)

c) Line string:

Connecting points create lines that can be used to represent roads, railway tracks, etc. Example:

Line string geometry object (Pink)

d) Multiline string:

Two or more line string in a space is called Multiline string.

Multiline geometry object image (Black)

e) Polygon:

Connecting lines that create an enclosed area create a polygon. Example:

Polygon image

f) Multi-polygon:

Two or more polygons in space are called Multi Polygon.

Multi-polygon image

Point in Polygon analysis

Let us consider a point, p and a polygon, P. If the point p is inside polygon P then this type of analysis is called Point-in-Polygon analysis. This is how Footfall, Foot Traffic, or Visitors counts are done. Example:

Point in Polygon Image

Geofencing

It is the technique of creating a virtual boundary also called a Geoboundary on the perimeter of any real-world geographical place. For example, consider a racecourse in Bangalore, India that has been geofenced below:

Image representation before geofencing the racecourse

Image representation after geofencing the racecourse

Coordinate Reference System (CRS) or Spatial Reference System 🌐

CRS helps you to precisely relate 2D (coordinates) with real-world places on Earth. CRS is that reference system that helps you flatten the Earth’s surface (3D) to a 2-dimensional surface.

Horizontal accuracy

This type of accuracy represents the radius of the margin of error that the given coordinates’ measurement can be in meters. Let us say that the horizontal accuracy of a device ID is 500 meters. This means that the device is somewhere within a 500-meter radius from the stated location observations (latitude and longitude).

The smaller the horizontal accuracy, the more precise the observation 👍.

GeoJSON and Shapefile

GeoJSON is a wrapper over a JSON file, which includes spatial attributes as an add-on component to it.

You can try creating your own geoJSON file by geofencing any of your favorite locations at geojson.io.

Shapefile is a common format file used to store vector data. One cannot edit the shapefile directly as it is not a text file.

Mapshaper is an online free web tool to convert GeoJSON to shapefile and vice versa.

Global positioning system (GPS)

It is a satellite system that helps you get location and time observation of any place 🏨, mobile device 📱, or any GPS-enabled package. Example:

Data dictionary of GPS data

Topology

Topology expresses the spatial relationships between connecting or adjacent vector features (points, polylines, and polygons).
['Manideep Ganji']
['Location Intelligence', 'Geospatial', 'GIS', 'Technology', 'Data']