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Article

Utilizing the Google Earth Engine for Agricultural Drought Conditions and Hazard Assessment Using Drought Indices in the Najd Region, Sultanate of Oman

by
Mohammed S. Al Nadabi
1,
Paola D’Antonio
2,
Costanza Fiorentino
2,*,
Antonio Scopa
2,
Eltaher M. Shams
3 and
Mohamed E. Fadl
4
1
Department of Geographic Information Systems and Remote Sensing, Directorate General of Planning, Ministry of Agriculture, Fisheries and Water Resources, Muscat 100, Oman
2
School of Agricultural, Forest, Food, and Environmental Sciences (SAFE), University of Basilicata, Via dell’Ateneo Lucano 10, 85100 Potenza, Italy
3
Geography and GIS Department, Faculty of Arts, Assiut University, Assiut 71526, Egypt
4
Division of Scientific Training and Continuous Studies, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11769, Egypt
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(16), 2960; https://doi.org/10.3390/rs16162960
Submission received: 25 June 2024 / Revised: 5 August 2024 / Accepted: 8 August 2024 / Published: 12 August 2024

Abstract

Accurately evaluating drought and its effects on the natural environment is difficult in regions with limited climate monitoring stations, particularly in the hyper-arid region of the Sultanate of Oman. Rising global temperatures and increasing incidences of insufficient precipitation have turned drought into a major natural disaster worldwide. In Oman, drought constitutes a major threat to food security. In this study, drought indices (DIs), such as temperature condition index (TCI), vegetation condition index (VCI), and vegetation health index (VHI), which integrate data on drought streamflow, were applied using moderate resolution imaging spectroradiometer (MODIS) data and the Google Earth Engine (GEE) platform to monitor agricultural drought and assess the drought risks using the drought hazard index (DHI) during the period of 2001–2023. This approach allowed us to explore the spatial and temporal complexities of drought patterns in the Najd region. As a result, the detailed analysis of the TCI values exhibited temporal variations over the study period, with notable minimum values observed in specific years (2001, 2005, 2009, 2010, 2014, 2015, 2016, 2017, 2019, 2020, and 2021), and there was a discernible trend of increasing temperatures from 2014 to 2023 compared to earlier years. According to the VCI index, several years, including 2001, 2003, 2006, 2008, 2009, 2013, 2015, 2016, 2017, 2018, 2020, 2021, 2022, and 2023, were characterized by mild drought conditions. Except for 2005 and 2007, all studied years were classified as moderate drought years based on the VHI index. The Pearson correlation coefficient analysis (PCA) was utilized to observe the correlation between DIs, and a high positive correlation between VHI and VCI (0.829, p < 0.01) was found. Based on DHI index spatial analysis, the northern regions of the study area faced the most severe drought hazards, with severity gradually diminishing towards the south and east, and approximately 44% of the total area fell under moderate drought risk, while the remaining 56% was classified as facing very severe drought risk. This study emphasizes the importance of continued monitoring, proactive measures, and effective adaptation strategies to address the heightened risk of drought and its impacts on local ecosystems and communities.
Keywords: GEE; drought assessment; drought indices; drought hazard; MODIS GEE; drought assessment; drought indices; drought hazard; MODIS
Graphical Abstract

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MDPI and ACS Style

Al Nadabi, M.S.; D’Antonio, P.; Fiorentino, C.; Scopa, A.; Shams, E.M.; Fadl, M.E. Utilizing the Google Earth Engine for Agricultural Drought Conditions and Hazard Assessment Using Drought Indices in the Najd Region, Sultanate of Oman. Remote Sens. 2024, 16, 2960. https://doi.org/10.3390/rs16162960

AMA Style

Al Nadabi MS, D’Antonio P, Fiorentino C, Scopa A, Shams EM, Fadl ME. Utilizing the Google Earth Engine for Agricultural Drought Conditions and Hazard Assessment Using Drought Indices in the Najd Region, Sultanate of Oman. Remote Sensing. 2024; 16(16):2960. https://doi.org/10.3390/rs16162960

Chicago/Turabian Style

Al Nadabi, Mohammed S., Paola D’Antonio, Costanza Fiorentino, Antonio Scopa, Eltaher M. Shams, and Mohamed E. Fadl. 2024. "Utilizing the Google Earth Engine for Agricultural Drought Conditions and Hazard Assessment Using Drought Indices in the Najd Region, Sultanate of Oman" Remote Sensing 16, no. 16: 2960. https://doi.org/10.3390/rs16162960

APA Style

Al Nadabi, M. S., D’Antonio, P., Fiorentino, C., Scopa, A., Shams, E. M., & Fadl, M. E. (2024). Utilizing the Google Earth Engine for Agricultural Drought Conditions and Hazard Assessment Using Drought Indices in the Najd Region, Sultanate of Oman. Remote Sensing, 16(16), 2960. https://doi.org/10.3390/rs16162960

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