Sources of Data Creation in GIS

GIS data creation is a multi-stage process that includes:

  • Data capture- Primary and secondary data
  • Geo-referencing
  • Digitizing (vector and raster format)
  • Attribute table import and association
  • Metadata preparation
  • Accuracy testing and repair
  • Data conversion to match with other data sets (vector to raster, raster to vector)
  • Database management.

It requires careful management and nurturing to create a reliable and accurate database.

GIS data creation involves the following processes:


Digitizing is converting geographic data from a hardcopy or a scanned image into vector data by tracing the features.

During the digitizing process, features from a map or image are captured as coordinates in either point, line, or polygon format.

It can be done in two ways:

1. Heads-up digitization

This is the most common way of digitizing. Here, a digital base map is collected and georeferenced using GIS software. Then all features in the map are digitized using the computer mouse while looking at the geometry of objects on a computer screen.

In this process, the operator keeps his head up, hence called heads up digitization. Digitization results in shape files, which are vector features.

  • Also known as, on-screen digitization
  • Raster map as background, vector layer in the foreground
  • Map scanning is necessary
  • Special snap function
  • Zooming= no internal resolution of digitizing

2. Heads-down digitization

Equipment such as a digitizing table, a handheld tracing device (such as digitizing pen or marker), a computer, etc., are used in the process of digitizing.

The base map is attached to a digitizing table. The digitizing table consists of a fine wire mesh, the positions of which are controlled and calculated in the GIS framework attached to it.

After placing the map on the table, it is pinned in a fixed location, and control points are set using known coordinates on the map. Then, the boundary and other required features from the base map are digitized by tracing along them using the digitizing pen.

This entire process is called heads-down digitizing as the operator keeps his head down during the whole process.

  • High precision in coordinate recording
  • Better overview
  • No scanning necessary
  • No snap function
  • Faster(a most common form of coordinate data input)


The electronic detector moves across the map and records light intensity for regularly shaped pixels Scanner output is a raster data set, therefore, needs to be converted into a vector representation. Often requires considerable editing.

Types of Scanners:

1. Drum (Automated vectorization)

Operators set global parameters and the system converted the entire map

2. Interactive line following

Operators points at a specific line and the system follows line using a guiding device such as a laser and converts the line.

Coordinate Geometry (COGO)

Coordinate geometry is a keyboard-based method of spatial data entry. This method is most commonly used to enter cadastral or land record data. This method is highly precise as entering the actual survey measurements of the property lines creates the database.

Distances and bearings are entered into the GIS from the original surveyor plats. The GIS software builds the digital vector file from these values.

Global Positioning Systems (GPS)

GPS is a way to gather accurate linear and point location data. Originally devised in the 1970s by the Department of Defense of the US for military purposes. The current GPS consists of 28 satellites that orbit the earth, transmitting navigational signals.

Through interpolation, these signals received by a data logger can pinpoint the holder’s location. Depending on the unit, the locational accuracy can reach up to a millimeter.
Combined with attribute data entered at the time of collection, GPS is a rapid and accurate method of data collection.

Image processing

Geodatasets can be derived from digital imagery. Most commonly satellite imagery is utilized in a process called supervised classification in which a user selected a sampling of pixels for which the user knows the type (vegetation species, land use, etc).

Using a classification algorithm, remote sensing software such as ERDAS or ENVI classifies a digital image into these named categories based on the sample pixels. Supervised classification results in a raster dataset.

Conversion of existing digital data

This involves the process of converting a variety of digital spatial data. Satellite images, digital aerial photographs, CAD, or other digital data are converted using suitable software. Most software vendors of GIS provide a data exchange format where users can write their own data conversion routes. For example, raster data can be converted to vector data and vice versa.

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