Extraction of Vacant Lands for Baghdad City Using Two Classification Methods of Very High Resolution Satellite Images

  • Jalal Ibrahim Faraj Department of Physics, College of Science, University of Baghdad, Baghdad, Iraq
  • Faleh Hassan Mahmood Remote Sensing Unit, College of Science, University of Baghdad, Baghdad, Iraq
Keywords: Vacant lands, Classification, Satellite images, Remote sensing, supervised Classification

Abstract

The use of remote sensing technologies was gained more attention due to an increasing need to collect data for the environmental changes. Satellite image classification is a relatively recent type of remote sensing uses satellite imagery to indicate many key environment characteristics. This study aims at classifying and extracting vacant lands from high resolution satellite images of Baghdad city by supervised Classification tool in ENVI 5.3 program. The classification accuracy was 15%, which can be regarded as fairly acceptable given the difficulty of differentiating vacant land surfaces from other surfaces such as roof tops of buildings.

Published
2018-12-26
How to Cite
FarajJ. I., & MahmoodF. H. (2018). Extraction of Vacant Lands for Baghdad City Using Two Classification Methods of Very High Resolution Satellite Images. Iraqi Journal of Science, 59(4C), 2336-2342. Retrieved from http://scbaghdad.edu.iq/eijs/index.php/eijs/article/view/567
Section
Remote Sensing