Ben Romdhane, Haifa
Now showing 1 - 6 of 6
- PublicationChange detection using remote sensing in a reef environment of the UAE during the extreme event of El Niño 2015–2016(2018)
; ;Al-Musallami, Mohamed ;Marpu, Prashanth Reddy ;Ouarda, Taha B. M. J.Ghedira, HosniCoral reefs of the United Arab Emirates (UAE) are living in the world’s hottest sea. Recently, corals harbouring Symbiodinium thermophilum, a thermotolerant microalgae, were found to be prevalent among UAE reefs and were reported to endure extreme sea-surface temperatures. Late 2015–early 2016 was marked with the strongest El Niño on record worldwide, which caused massive coral bleaching (loss of symbiotic microalgae from reef-building corals). In September 2015, the waters flanking UAE coasts were identified to be among the areas facing a thermal stress reaching its highest level liable to cause massive coral bleaching. However, the effect of this thermal stress on UAE corals remained largely unknown. Here, multi-temporal DubaiSat-2 satellite images were used to show that changes in the reef environment of Dalma Island, UAE, between 2014 and 2016, occurred in macroalgaedominant habitats, whereas live corals remained unaltered. Furthermore, extending the study to a larger area helped in discovering a continuum of live and pristine corals, which was not reported or studied before. While sea-surface temperature anomalies of 1°C were reported to significantly damage coral reefs around the world, the live coral habitat was observed to exhibit no-change despite four consecutive months of +2°C to 3°C anomalies reported during the study period. These findings point to the tolerance of UAE live corals faced with extreme climate conditions Scopus© Citations 6 477 102
- PublicationCoral Reefs of Abu Dhabi, United Arab Emirates: Analysis of Management Approaches in Light of International Best Practices and a Changing Climate(2020)
; ;Perry, Richard John Obrien ;Al Blooshi, Ayesha Yousef ;Ghedira, Hosni ;Jabado, Rima W. ;Marpu, Prashanth Reddy ;Ouarda, Taha B. M. J.Grandcourt, Edwin MarkThe coasts and islands that flank Abu Dhabi, the United Arab Emirates (UAE)’s largest emirate, host the country’s most significant coastal and marine habitats including coral reefs. These reefs, although subject to a variety of pressures from urban and industrial encroachment and climate change, exhibit the highest thresholds for coral bleaching and mortality in the world. By reviewing and benchmarking global, regional and local coral reef conservation efforts, this study highlights the ecological importance and economic uniqueness of the UAE corals in light of the changing climate. The analysis provides a set of recommendations for coral reef management that includes an adapted institutional framework bringing together stakeholders, scientists, and managers. These recommendations are provided to guide coral reef conservation efforts regionally and in jurisdictions with comparable environmental challenges. Scopus© Citations 3 793 48
- PublicationDetecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAEIn this paper, the feasibility of satellite remote sensing in detecting and predicting locations of buried objects in the archaeological site of Saruq Al-Hadid, United Arab Emirates (UAE) was investigated. Satellite-borne synthetic aperture radar (SAR) is proposed as the main technology for this initial investigation. In fact, SAR is the only satellite-based technology able to detect buried artefacts from space, and it is expected that fine-resolution images of ALOS/PALSAR-2 (L-band SAR) would be able to detect large features (>1 m) that might be buried in the subsurface (<2 m) under optimum conditions, i.e., dry and bare soil. SAR data were complemented with very high-resolution Worldview-3 multispectral images (0.31 m panchromatic, 1.24 m VNIR) to obtain a visual assessment of the study area and its land cover features. An integrated approach, featuring the application of advanced image processing techniques and geospatial analysis using machine learning, was adopted to characterise the site while automating the process and investigating its applicability. Results from SAR feature extraction and geospatial analyses showed detection of the areas on the site that were already under excavation and predicted new, hitherto unexplored archaeological areas. The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. The validated results can provide guidance for future on-site archaeological work. The pilot process developed in this work can therefore be applied to similar arid environments for the detection of archaeological features and guidance of on-site investigations.
- PublicationOptical and radiative properties of aerosols over Abu Dhabi in the United Arab Emirates(2016)
; ;Beegum, S Naseema ;Ali, Mohammed Tauha ;Armstrong, PeterGhedira, HosniThe present study is on the aerosol optical and radiative properties in the short-wave radiation and its climate implications at the arid city of Abu Dhabi (24.42 ∘N, 54.61 ∘E, 4.5 m MSL), in the United Arab Emirates. The direct aerosol radiative forcings (ARF) in the short-wave region at the top (TOA) and bottom of the atmosphere (BOA) are estimated using a hybrid approach, making use of discrete ordinate radiative transfer method in conjunction with the short-wave flux and spectral aerosol optical depth (AOD) measurements, over a period of 3 years (June 2012–July 2015), at Abu Dhabi located at the south-west coast of the Arabian Gulf. The inferred microphysical properties of aerosols at the measurement site indicate strong seasonal variations from the dominance of coarse mode mineral dust aerosols during spring (March–May) and summer (June–September), to the abundance of fine/accumulation mode aerosols mainly from combustion of fossil-fuel and bio-fuel during autumn (October–November) and winter (December–February) seasons. The monthly mean diurnally averaged ARF at the BOA (TOA) varies from −13.2 Wm−2 (∼−0.96 Wm−2) in November to −39.4 Wm−2 (−11.4 Wm−2) in August with higher magnitudes of the forcing values during spring/summer seasons and lower values during autumn/winter seasons. The atmospheric aerosol forcing varies from + 12.2 Wm−2 (November) to 28.2 Wm−2 (June) with higher values throughout the spring and summer seasons, suggesting the importance of mineral dust aerosols towards the solar dimming. Seasonally, highest values of the forcing efficiency at the surface are observed in spring (−85.0 ± 4.1 W m−2 τ −1) followed closely by winter (−79.2 ± 7.1 W m−2 τ −1) and the lowest values during autumn season (−54 ± 4.3 W m−2 τ −1). The study concludes with the variations of the atmospheric heating rates induced by the forcing. Highest heating rate is observed in June (0.39 K day −1) and the lowest in November (0.17 K day −1) and the temporal variability of this parameter is linearly associated with the aerosol absorption index. Scopus© Citations 2 13
- PublicationStudying coral reef patterns in UAE waters using panel data analysis and multinomial logit and probit modelsLike coral reefs around the world, the reefs of the United Arab Emirates (UAE) are facing global climate change and associated threats. The coasts and islands that flank Abu Dhabi host an important number of corals that should be the focus of conservation actions. Well-designed conservation and management plans require efficient monitoring systems that include understanding coral reef patterns. To understand some of these patterns; coral cover data, satellite-derived and in-situ water quality parameters from nine key reef environments in the UAE from 2011 to 2014 to model coral patterns were used. The objectives were to model coral patterns and realistically predict coral damage intensity with changing environmental variables. Coral damage cover models were defined and estimated for the coral damage cover. Effects of environmental factors were estimated, and predictions of coral damage intensity were presented with changing factors. Main findings, based on the studied data, showed that nutrient enrichment, a proxy for anthropogenic pressure, and salinity are the most influential factors to induce coral damage in UAE waters. Furthermore, results demonstrated that the probability of severe damage increases with decreasing water oxygenation and with increasing temperature, light, salinity, acidity and nutrient levels. The defined and estimated predictions accounted for corals’ behavioural aspects, across individual reefs and over time. This approach is more appropriate than estimation predictions that just account for historic trends. Nevertheless, there are, probably, many components within the model framework that can be expanded and/or improved as more information become available. An extended dataset will enable a means to independently validate the defined models and test other modelling approaches. Continually increasing the insitu and remote sensing data sizes, spatially and temporally, defines a long-term priority.
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