Application of global dust detection index (GDDI) for sand and dust storm monitoring over Kingdom of Saudi Arabia

Essam Mohammed Alghamdi, Mazen Ebraheem Assiri and Mohsin Jamil Butt ()
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Essam Mohammed Alghamdi: King Abdulaziz University
Mazen Ebraheem Assiri: King Abdulaziz University
Mohsin Jamil Butt: King Abdulaziz University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 14, No 34, 13385-13405

Abstract: Abstract Sand and dust storm events are frequent natural hazards in the Kingdom of Saudi Arabia. Sand and dust storm monitoring is therefore essential to mitigate their environmental-related issues. Satellite remote sensing has been successfully used for sand and dust storm monitoring in various parts of the world. In the current endeavor, we are applying the Global Dust Detection Index (GDDI) on Moderate Resolution Imaging Spectroradiometer (MODIS) data onboard Terra satellite to monitor sand and dust storm activities over the Kingdom of Saudi Arabia. In the current study, fourteen sand and dust storm events are analyzed between the years 2000 to 2017. The GDDI based results are validated by using MODIS combined Dark Target (DT) and Deep Blue (DB) Aerosol Optical Depth (AOD) product, Meteosat satellite images, ground-based meteorological stations data, and AOD data from AERONET (Aerosol Robotic Network) stations in the study area. Also, GDDI based results are analyzed by determining algorithm accuracy, Probability Of Correct positive Detection (POCD), and Probability Of False positive Detection (POFD). Results of the study show that GDDI can successfully identify sand and dust storm events with various threshold values over the Kingdom of Saudi Arabia. It is envisaged that the outcome of this study would be very beneficial to understand sand and dust storm characteristics in the study region.

Keywords: GDDI; DT; DB; AERONET; POCD; POFD (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-024-06725-8

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