Skip to main content

The Sinusoidal Projection: A New Importance in Relation to Global Image Data

Buy Article:

$43.00 plus tax (Refund Policy)

The reprojection of image data causes the loss or duplication of original pixel values. This research investigated the feasibility of using the sinusoidal projection for global image database construction. Specifically, reprojection accuracies were tested with geographic latitude and longitude coordinates, and the Hammer-Aitoff, Eckert IV, Mollweide, and sinusoidal projections. Reprojections between these five global projections and the Universal Transverse Mercator (UTM) projection and referencing system were performed using fifty-four sample datasets. A statistical analysis of categorical accuracy, a measure describing the omission of pixel values during reprojection, was conducted. Geographic coordinates and the sinusoidal projection both showed very high accuracy rates (100.0 percent and 99.5 percent respectively) when sample datasets were reprojected from UTM. The geographic coordinates, however, showed very low accuracy (65.3 percent) when sample datasets were reprojected to the UTM projection, while the sinusoidal projection showed the highest accuracy (98.4 percent). The results strongly suggest that the sinusoidal projection is very accurate and efficient for building global image databases.
No References
No Citations
No Supplementary Data
No Data/Media
No Metrics

Keywords: GIS; global image data; scale factor model; sinusoidal projection

Document Type: Research Article

Affiliations: 1: Northern Michigan University, 2: East Carolina University, 3: University of Georgia

Publication date: 2002-05-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more