Evaluate the impact of empirical geometric correction models of satellite images on the land cover classification accuracy

Authors

  • Fatima Nowira Tishreen University
  • Omar Al Khalil Tishreen University
  • Iyad Fahsa Tishreen University

Abstract

Land cover classification is one of the important topics in the field of remote sensing. Satellite images are exposed to geometric distortions that affect the geometric quality of the spatial data extracted from them. Thus, they must be corrected by applying geometric correction.

This research aims to evaluate the effects of the type of geometric correction models and resampling algorithms on the quality of the Maximum Likelihood-based land cover classification. 12 ground control points distributed uniformly were used for geometric correction.

The research results showed that the nearest neighbor algorithm with the second-order polynomial model are the most suitable for the issue of land cover classification. In fact, overall accuracy of the classification reached 88.75% with a kappa coefficient of 0.85. On the other hand. The results showed that although the accuracy of the geometric correction using a rubber-sheeting model (±7.065m) was the best, the classification results were not. In this case, total accuracy value ranged between 59.493% and 60.7% and a kappa coefficient rages from 0.46 to 0.47, meaning that a more accurate geometric correction does not correspond to a more accurate classification result.

Downloads

Published

2023-10-22

How to Cite

1.
نويره ف, عمر الخليل, إياد فحصة. Evaluate the impact of empirical geometric correction models of satellite images on the land cover classification accuracy. Tuj-eng [Internet]. 2023Oct.22 [cited 2024May2];45(4):547-60. Available from: https://journal.tishreen.edu.sy/index.php/engscnc/article/view/15437

Issue

Vol. 45 No. 4 (2023): Tishreen University Journal of Research and Scientific Studies - Engineering Sciences Series

Section

Master student researches

License

Copyright (c) 2023 https://creativecommons.org/licenses/by-nc-sa/4.0/

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The authors retain the copyright and grant the right to publish in the magazine for the first time with the transfer of the commercial right to Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series

 Under a CC BY- NC-SA 04 license that allows others to share the work with of the work's authorship and initial publication in this journal. Authors can use a copy of their articles in their scientific activity, and on their scientific websites, provided that the place of publication is indicted in  Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series   .  The Readers have the right to send, print and subscribe to the initial version of the article, and the title of  Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series     Publisher

journal uses a CC BY-NC-SA license which mean

You are free to:

  • Adapt — remix, transform, and build upon the material
  •  
  • The licensor cannot revoke these freedoms as long as you follow the license terms.

 

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • NonCommercial — You may not use the material for commercial purposes.
  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.