Development of Automatic Detection of Dust Storms for MODIS Satellite Images over Iraq Using ArcGIS Model Builder

Authors

  • Aws A. Al-Khudhairy Climate Center and Scientific Research, Iraqi Meteorological Organization and Seismology https://orcid.org/0009-0007-8038-6802
  • Auday H. Shaban Remote Sensing & GIS Department, College of Science, Baghdad University
  • Yaseen K. Al-Timimi Atmospheric Science Department, College of Science, Mustansiriyah University

DOI:

https://doi.org/10.24996/ijs.2025.66.2.34

Keywords:

ArcGIS, Model Builder, Dust storm, Dust Index, MODIS, Aqua, Terra

Abstract

Geographical Information Systems (GIS) provides a set of instruments and techniques to explain and display different geographical data, and ArcGIS Model Builders consider a very beneficial technique to represent these procedures in a very effective and influential manner. This paper indicates that using the ArcGIS tool Model Builder is the preferred technique to display the flux of procedures, in which the model's design is highly preferable to decrease the time consumed to apply any procedure. One model was used to explain the best methodology to resolve the issue, which deals with dust storm detection over Iraq using MODIS data. This study Facilitate Terra and Aqua MODIS satellite images; the first case was Terra / MODIS during the first half of the day with NDDI and IDDI, while the second case was Aqua/ MODIS during the second half of the day with the three thermal indices MEDI, BTV, TB beside IDDI. This study displays the effectiveness of these indices in two cases to show their validity in detecting dust storms compared to synoptic data over the study area. Besides, it displays ArcGIS Model Builder's importance in applying these Indices more efficiently and smoothly to benefit from it in serving society and the scientific community.

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Section

Remote Sensing

How to Cite

Development of Automatic Detection of Dust Storms for MODIS Satellite Images over Iraq Using ArcGIS Model Builder. (n.d.). Iraqi Journal of Science, 66(2). https://doi.org/10.24996/ijs.2025.66.2.34