Variability of blue carbon storage in arid evaporitic environment of two coastal Sabkhas or mudflats.

Coastal Sabkhas are mudflats found in arid coastal regions that are located within the supratidal zone when high rates of evaporation lead to high salinity. While evaporitic minerals often accumulate underneath the surface, the microbial mats are present on the surface of Sabkhas. Coastal Sabkha, an under-studied ecosystem in Qatar, has the potential to store blue carbon. In the present study, we investigated the carbon storage capacity of two Sabkhas from contrasting geological backgrounds. The spatial and temporal variabilities of the carbon stocks were examined. The results showed that both studied Sabkhas exhibit a considerable potential for soil carbon storage with carbon stocks of 109.11 ± 7.07 Mg C ha-1 and 67.77 ± 18.10 Mg C ha-1 in Dohat Faishakh and Khor al Adaid Sabkha respectively. These values fall within the reported range for carbon stocks in coastal Sabkhas in the region (51-194 Mg C ha-1). Interestingly, the carbon stocks in the sediments of the Sabkhas were higher than those in the sediments of Qatari mangroves (50.17 ± 6.27 Mg C ha-1). These finding suggest that coastal Sabkhas can serve as blue carbon ecosystems in arid environments.

Remote sensing of desertification and study of temporal variability of aeolian deposits in parts of the Arabian Desert for sustainable development in an arid environment.

Aeolian deposit in part of the Arabian Desert is mapped using ASTER data to understand desertification, land encroachment, and degradation, and to assess agricultural development in arid regions. In this study, the interpretation of emissive spectra of sand deposits showed the presence of triplet absorptions in emissivity between 8 and 9.50 µm and studied with ASTER spectral bands to map the deposits. The ASTER quartz index (QI) images used to study the Abu Samra region, Qatar from 2000 to 2021 showed significant changes in desertification and land degradation. Analysis of temporal variability of deposits between 2000 and 2021 using ASTER band 12 by Parallelepiped image classification showed a decreasing trend from 9.70% to 2.94% in their distributions due to erosion and transportation. The changes are studied using FCC images (R:1; G:2; B:3) and hill-shaded images of 2000 and 2021. The results are confirmed from FCC (R:14; G:12; B:11) and Google Earth satellite images which showed the occurrence of sabkhas in 1985 and their disappearance from 2015, and the presence of agriculture in 2000 and their absence from 2005. The changes in desertification, land degradation, and agricultural development are verified in the field and evidenced. The grain size analysis of samples by ASTM method showed aeolian deposits have very fine to very coarse (63-2000 µm) sand types with silts of <3%. The samples analyzed by XRD and SEM-EDX methods showed the occurrence of dolomite, calcite, quartz, feldspar, and gypsum minerals with high sphericity and sub-angular to well-rounded characters and suggested transportations of grains from long distances. The geochemical elements analyses of samples reflected the chemistry of carbonates, aluminosilicates, and evaporites minerals which could have been derived from the carbonate, shale and sandstone formations, and sabkhas that occurred in Qatar and the Arabian Peninsula.

History of a disaster: A baseline assessment of the Wakashio oil spill on the coast of Mauritius, Indian Ocean.

Oil spills from tanker ships provide adverse and irreversible impacts of a pollutant over coastal and marine environments. Using Sentinel-1 and 2 satellite images, this baseline paper presents the detection, assessment, and monitoring of the aground and further oil spill from the Wakashio ship of August 06, 2020, on the Mauritius coast. The oil spill started on August 06, after cracks developed on the hull, and continued until the total breakup of the ship on August 15, 2020. Data shows displacements in ship position of about 100 m, and a maximum change of 80° in orientation (from NS to NE). The remote sensing results were validated using met-ocean observations and reanalysis, which showed winds, waves, and tides of high magnitude at the accident site during the incident period. Analysis of the results of this event using REAS and CMEMS data indicate their usefulness to study similar future oil spills events.

Sentinel-2 image transformation methods for mapping oil spill - A case study with Wakashio oil spill in the Indian Ocean, off Mauritius.

Although several indices have been constructed and available at the Index database (IDB) for Sentinel-2 satellite to map and study several earth resources, no indices have been developed to map oil spill. We constructed band ratios (5 + 6)/7, (3 + 4)/2, (11+12)/8 and 3/2, (3 + 4)/2, (6 + 7)/5 using the high-resolution MSI (multi-spectral instrument) visible-near infrared-shortwave infrared spectral bands of Sentinel-2 by summing-up the bands representing the shoulders of absorption features as numerator and the band located nearest to the absorption feature as denominator to discriminate oil spill, and demonstrate the potential of this method to map the Wakashio oil spill which occurred in the Indian Ocean, off Mauritius. The resulted images discriminated the oil spill well. We also decorrelated the spectral bands 4, 3 and 2 by studying the spectral band absorptions and discriminated the spill as very thick, thick and thin. The results of decorrelation stretch method exhibited the distribution of types of oil spill in a different tone, distinctly. Both the image transformation methods (band ratios and decorrelation stretch methods) showed their capability to map oil spills, and these methods are recommended to use for similar spectral bands of other sensors to map oil spills.•This study demonstrated the application of band ratios and decorrelation stretch methods to map oil spill.•The methods discriminated the oil spill off Mauritius, and showed spill thicknesses from the Sentinel-2 data.•The new methods are recommended to use for the spectral bands of other sensors to map oil spill.

Monitoring oil spill in Norilsk, Russia using satellite data.

This paper studies the oil spill, which occurred in the Norilsk and Taimyr region of Russia due to the collapse of the fuel tank at the power station on May 29, 2020. We monitored the snow, ice, water, vegetation and wetland of the region using data from the Multi-Spectral Instruments (MSI) of Sentinel-2 satellite. We analyzed the spectral band absorptions of Sentinel-2 data acquired before, during and after the incident, developed true and false-color composites (FCC), decorrelated spectral bands and used the indices, i.e. Snow Water Index (SWI), Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI). The results of decorrelated spectral bands 3, 8, and 11 of Sentinel-2 well confirmed the results of SWI, NDWI, NDVI, and FCC images showing the intensive snow and ice melt between May 21 and 31, 2020. We used Sentinel-2 results, field photographs, analysis of the 1980-2020 daily air temperature and precipitation data, permafrost observations and modeling to explore the hypothesis that either the long-term dynamics of the frozen ground, changing climate and environmental factors, or abnormal weather conditions may have caused or contributed to the collapse of the oil tank.

Detection of Wakashio oil spill off Mauritius using Sentinel-1 and 2 data: Capability of sensors, image transformation methods and mapping.

Oil spill incidents contaminate water bodies, and damage the coastal and marine environment including coral reefs and mangroves, and therefore, monitoring the oil spills is highly important. This study discriminates the Wakashio oil spill, which occurred off Mauritius, located in the Indian Ocean on August 06, 2020 using the Sentinel-1 and 2 data acquired before, during and after the spill to understand the spreading of the spill and assess its impact on the coastal environment. The interpretation of VV polarization images of Synthetic-Aperture Radar (SAR) C-band (5.404 GHz) of Sentinel-1 acquired between July 5 and September 3, 2020 showed the occurrence and distribution of oil spill as dark warped patches. The images of band ratios (5 + 6)/7, (3 + 4)/2, (11 + 12)/8 and 3/2, (3 + 4)/2, (6 + 7)/5 of the Sentinel-2 data detected the oil spill. The images of decorrelated spectral bands 4, 3 and 2 distinguished the very thick, thick and thin oil spills in a different tone and showed clearly their distribution over the lagoon and offshore, and the accumulation of spilled oil on the coral reefs and along the coast. The distribution of post-oil spill along the coast was interpreted using the images acquired after 21 August 2020. The accuracy of oil spill mapping was assessed by classifying the SAR-C data and decorrelated images of the MultiSpectral Instrument (MSI) data using the Parallelepiped supervised algorithm and confusion matrix. The results showed that the overall accuracy is on an average 91.72 and 98.77%, and Kappa coefficient 0.84 and 0.96, respectively. The satellite-derived results were validated with field studies. The MSI results showed the occurrence and spread of oil spill having different thicknesses, and supported the results of SAR. This study demonstrated the capability of Sentinel sensors and the potential of image processing methods to detect, monitor and assess oil spill impact on environment.

WorldView-3 mapping of Tarmat deposits of the Ras Rakan Island, Northern Coast of Qatar: Environmental perspective.

This study characterizes the spectral behavior of tarmats and maps the tarmat deposits found along the coast of Ras Rakan Island off Qatar using WorldView-3 (WV-3) sensor data. The laboratory spectra of tar materials showed diagnostic absorptions features at 0.6 and 1.1 µm in the visible and near-infrared (VNIR) and 1.52, 1.73, 2.04, and 2.31 µm in the short wave infrared (SWIR) region. The panchromatic grayscale image and FCC showed the tarmat deposit as a linear warp feature between beach and water. The mapping of deposits using WV-3 data by decorrelation stretch and Linear Spectral Unmixing (LSU) methods discriminated the tarmats from the sandy soil, vegetation and sabkha features in a different tone. The capability of WV-3 sensor and the potential of image processing methods were verified by mapping the tar distribution of the Ras Ushayriq and NE of Al Ruwais.

Mapping and accuracy assessment of siltation of recharge dams using remote sensing technique.

This study demonstrates the use of ASTER data to map the siltation of the Al-Khod Dam constructed at the lower reaches of Samail Catchment area, north Muscat, Sultanate of Oman. In this study, the decorrelated image of spectral bands 6, 3, and 1 clearly discriminated the distribution of siltation. The occurrence of siltation is confirmed by the detection of minerals using the VNIR-SWIR bands by the Spectral Angle Mapper (SAM) method. In addition, the siltation of the dam is studied for the years 1987 to 2018 using Landsat satellite images. Interpretation of images showed a gradual increase of the siltation. Mapping accuracy for the occurrence of siltation is assessed by a confusion matrix which produced an overall accuracy of 97.88% and Kappa coefficient of 0.98 in the Maximum Likelihood method. Results of image analyses are verified in the field and confirmed through laboratory analyses. The study of spectral absorption characters of field samples using a Portable Infrared Mineral Analyzer (PIMA) showed the presence of OH molecule bearing minerals (clays, serpentines, etc.) and carbonate minerals (calcite and dolomite) in the silt deposits. The occurrence of these minerals is confirmed further by X-ray diffraction (XRD) and Scanning Electron Microscope (SEM) analyses.