The use of remote sensing technology in defining the water depth in the lakes and water bodies: Western Iraq as a case study | [Journal of Global Innovations in Agricultural Sciences • 2023]

Author(s):

1. Taghreed Abdul-Hameed Naji: College of Education for Pure Sciences Ibn Al-Haitham, University of Baghdad,,

2. Shahad Abdul-Qader Abdul-Hameed: Ministry of Water Resources, Baghdad, Iraq

3. Dahlia Abdul-Qader Abdul- Hameed: Ministry of Water Resources, Baghdad, Iraq

4. Tabarak Mohammed Awad: Al-Karkh University of Science,Baghdad,Iraq

5. Sura Sabah Rasool Fakhruldeen: Ministry of Water Resources,Baghdad,Iraq

Abstract:

The study's primary purpose is to explore an appropriate way of monitoring and assessing water depths using the satellite remote sensing technique of the Al Habbaniyah Lake in Iraq. This research studied the experience-conditions (thresholds) of different bands for multi-temporal satellite image data with different satellite image sensors (Landsat 5-TM, and EO1-ALI) for the same region, to recognize regions of water depths. The threshold values are taken that to separate the Al Habbaniyah Lake to the required depths (shallow, deep, and very deep), as a supervised method. A three-dimension feature space plot had used to represent these regions. The relationship of the mean values of the three separated water regions with all TM and ALI bands is studied. Other lakes in Iraq were used to actualize the validity and accuracy of this technique to find the water depth regions; Al Qadisiyha and Al Mosul lakes are in the West and North of Iraq of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-5 Thematic Mapper (TM) satellite images respectively. This technique succeeded in determining Al Habbaniyah lake depths but failed to recognize the regions of water depths for some of the lakes which have the big depths by correct form such as; Al Qadisiyha and Al Mosul lakes.

Page(s): 191-197

DOI: 10.22194/JGIAS/11.1083

Published: Journal: Journal of Global Innovations in Agricultural Sciences, Volume: 11, Issue: 2, Year: 2023

Keywords:

Remote Sensing , Water detection , experienceconditions , eo1ali

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