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Normalized difference vegetation index (NDVI) is one of the parameters of vegetation that can be studied by remote sensing of land surface with Sentinel-2 (S-2) satellite image. The NDVI is a nondimensional index that depicts the difference in plant cover reflectivity between visible and near-infrared light and can be used to measure the density of green on a piece of land. On the other hand, the dual-pol radar vegetation index (DpRVI) is one of the indices studied using multispectral synthetic aperture radar (SAR) images. Researchers have identified that SAR images are highly sensitive to identify the buildup of biomass from leaf vegetative growth to the flowering stage. Vegetation biophysical characteristics such as the leaf area index (LAI), vegetation water content, and biomass are frequently used as essential system parameters in remote sensing data assimilation for agricultural production models. In the current study, we have used LAI as a system parameter. The findings of the study revealed that the optical data (NDVI) showed a high correlation (up to 0.712) with LAI and a low root-mean-square error (0.0296) compared to microwave data with 0.4523 root-mean-square error. The NDVI, LAI, and DpRVI mean values all decreased between 2019 and 2020. While the DpRVI continued to decline between 2020 and 2021, the NDVI and LAI saw an increase over the same period, which was likely caused by an increase in the study area’s average annual rainfall and the cautious stance of the Red Global (RSG) project on sustainability.

Rabigh is a thriving coastal city located at the eastern bank of the Red Sea, Saudi Arabia. The city has suffered from shoreline destruction because of the invasive tidal action powered principally by the wind speed and direction over shallow waters. This study was carried out to calibrate the water column depth in the vicinity of Rabigh. Optical and microwave remote sensing data from the European Space Agency were collected over 2 years (2017–2018) along with the analog daily monitoring of tidal data collected from the marine station of Rabigh. Depth invariant index (DII) was implemented utilizing the optical data, while the Wind Field Estimation algorithm was implemented utilizing the microwave data. The findings of the current research emphasis on the oscillation behavior of the depth invariant mean values and the mean astronomical tides resulted in R2 of 0.75 and 0.79, respectively. Robust linear regression was established between the astronomical tide and the mean values of the normalized DII (R2 = 0.81). The findings also indicated that January had the strongest wind speed solidly correlated with the depth invariant values (R2 = 0.92). Therefore, decision-makers can depend on remote sensing data as an efficient tool to monitor natural phenomena and also to regulate human activities in fragile ecosystems.

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The spatial distribution of benthic foraminifera from surficial stations in the southern Corniche of Jeddah were investigated to infer their nearshore distribution and responses to important environmental factors (e.g., grain size, temperature, salinity, pH, and dissolved oxygen). Genera that found to dominate the studied stations are: Clavulina, Coscinospira, Cycloforina, Elphidium, Peneroplis, Quinqueloculina, Sorites, Spiroloculina, Varidentella, and Triloculina. The Canonical Correspondence Analysis (CCA) multivariate technique suggests a clear segregation in the stations. Stations from the northern part (SC4, 5,6,10) were found to be positively correlated with dissolved oxygen and temperature, while most of the stations (SC11-20) were found positively correlated with CaCO3 and salinity and to a lesser extent TOC (wt.%). Ammonia convexa, Quinqueloculina costata, Q. leavigata, Q. neostriatula, Triculoculina schreiberiana and Elpheduim advenum have shown to favor thriving in stations characterized by higher carbonate contents, salinity and TOC (wt.%). Neorotalia calcar and Q. seminula have been dominated in stations characterized by positive correlation with dissolved oxygen and temperature. Stations characterized by coarse grain size (gravely substrate) and populations of marine green algae show less diversity and dominance of S. orbiculus one of the largest foraminifera that prefer symbiosis. [ABSTRACT FROM AUTHOR]