New Adaptive Satellite Image Classification Technique for Al habbinya Region West of Iraq

Main Article Content

Taghreed A. Naji Amaal J. Hatem Amaal J. Hatem

Abstract

   Developing a new adaptive satellite images classification technique, based on a new way of merging between regression line of best fit and new empirical conditions methods. They are supervised methods to recognize different land cover types on Al habbinya region. These methods should be stand on physical ground that represents the reflection of land surface features.      The first method has separated the arid lands and plants. Empirical thresholds of different TM combination bands; TM3, TM4, and TM5 were studied in the second method, to detect and separate water regions (shallow, bottomless, and very bottomless). The Optimum Index Factor (OIF) is computed for these combination bands, which realized the higher OIF value with low correlated from other TM combination bands. This study was performed using ArcGIS9.3, ENVI 4.5 softwares and MATLAB7.9b language.

Article Details

How to Cite
NAJI, Taghreed A.; HATEM, Amaal J.; HATEM, Amaal J.. New Adaptive Satellite Image Classification Technique for Al habbinya Region West of Iraq. Ibn AL- Haitham Journal For Pure and Applied Science, [S.l.], v. 26, n. 2, p. 143-149, apr. 2017. ISSN 2521-3407. Available at: <http://jih.uobaghdad.edu.iq/index.php/j/article/view/494>. Date accessed: 13 oct. 2019.
Section
physics