687
Views
31
CrossRef citations to date
0
Altmetric
Review Article

State-of-the-art of geometric correction of remote sensing data: a data fusion perspective

Pages 3-35 | Received 23 Jul 2010, Accepted 05 Nov 2010, Published online: 18 Feb 2011
 

Abstract

The three-dimensional (3D) geometric processing and ortho-rectification of remote sensing (RS) data becomes a key issue as being the first step in multi-source multi-format data fusion in geographic information systems. The fusion of image data (visible and microwave, panchromatic and multi bands, polarimetric bands, passive and active, etc.), their metadata (GPS, star trackers, inertial system, lens and focal plane, etc.), the associated 3D cartographic data (ground control points, contour lines, digital terrain model (DEM), planimetric features, etc.) is thus a requisite to perform first 3D precise geometric correction and then the ortho-rectification process with DEM. This article presents an update of the state-of-the-art of geometric correction with the source of geometric distortions, the different mathematical models, the methods, algorithms and processing steps to track finally the error propagation during the fusion of the different RS and cartographic data from the image acquisition to the ortho-rectification processes.

View correction statement:
Corrigendum to the paper ‘State-of-the-art of geometric correction of remote sensing data: a data fusion perspective’

Acknowledgement

Earth Sciences Sector (ESS) contribution number: 20100290.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 256.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.