Optical Models for Remote Sensing of Colored Dissolved Organic Matter Absorption and Salinity in New England, Middle Atlantic and Gulf Coast Estuaries USA

Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. This study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash-Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt2) is lower than that of Landsat estimation (10.4 ppt2) and numerical simulations (9.6 ppt2). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

Interference of CDOM in remote sensing of suspended particulate matter (SPM) based on MODIS in the Persian Gulf and Oman Sea

The spatial and temporal variability of suspended particulate matter (SPM) in the Persian Gulf and Oman Sea coastal waters has remained challenging to understand among researchers. Here, for the first time in the region, we parametrized SPM concentration in the study area utilizing derived remote sensing reflectance (R_rs) values from Moderate-resolution Imaging Spectroradiometer (MODIS), using 555 and 667 nm wavelengths. Likewise, the findings showed that the developed optical model based on the optical ratio of R_rs (667)/R_rs (555) was sensitive to the concentration of Chromophoric dissolved organic matter (CDOM) in the seawater, within the visible wavelengths less than 600 nm. Comparing the new estimates of the SPM concentration with in situ measurements by Spearman's Rank correlation for validation revealed that the association between estimated and measured SPM concentration would be considered statistically significant (ρ up to 0.86, p < 0.05). This study increased the average accuracy of the estimates up to 73%.

A global compilation of in situ aquatic high spectral resolution inherent and apparent optical property data for remote sensing applications

Light emerging from natural water bodies and measured by radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities for characterizing aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission; the NASA Surface Biology and Geology designated observable mission; and NASA Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP-AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland waters, estuaries, and oceans. Specific in situ measurements include remote-sensing reflectance, irradiance reflectance, and coefficients describing particulate absorption, particulate attenuation, non-algal particulate absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, and total backscattering. The dataset can be downloaded from https://doi.org/10.1594/PANGAEA.902230 (Casey et al., 2019).

Reconstruction of sea-land interactions between terrestrial vegetation cover and water quality constituents in the Mattapoisett Harbor area during the 1991 Hurricane Bob event

Hurricane Bob passed over the New England region in August 1991, causing significant damage to life, property, and the environment, making it one of the costliest hurricanes in New England history. The environmental impact of a hurricane of this magnitude warrants careful assessment to devise preventive measures and mitigation strategies to bolster water resources management programs against future events. In this paper, we show the reconstructed simultaneous impacts of Hurricane Bob on the vegetative cover of the Mattapoisett river watershed and the water quality of the Mattapoisett Harbor with the aid of remote sensing for earth observations. The water quality impacts, especially in terms of Total Organic Carbon (TOC) and Sea Surface Salinity (SSS), can be identified from variations of SSS and TOC near coastal estuaries due to the influx of freshwater from the coastal Mattapoisett River to the continent-ocean transition between natural tides and bay waves. Using the Landsat satellite images, the Normalized Difference Vegetation Index (NDVI) and water quality constitutes (TOC and SSS) were reconstructed and retrieved for the assessment of the sea-land interactions during the Hurricane Bob event in 1991. Results indicate phenomenal interactive patterns between the harbor and the coastal watershed, as well as the riverine system. TOC and NDVI, especially in the upper watershed region, can be strongly correlated with hurricane impacts according to the singular value decomposition analysis.

Remote Sensing of Floodpath Lakes and Wetlands: A Challenging Frontier in the Monitoring of Changing Environments

Monitoring of changing lake and wetland environments has long been among the primary focus of scientific investigation, technology innovation, management practice, and decision-making analysis. Floodpath lakes and wetlands are the lakes and associated wetlands affected by seasonal variations of water level and water surface area. Floodpath lakes and wetlands are, in particular, sensitive to natural and anthropogenic impacts, such as climate change, human-induced intervention on hydrological regimes, and land use and land cover change. Rapid developments of remote sensing science and technologies, provide immense opportunities and capacities to improve our understanding of the changing lake and wetland environments. This special issue on Remote Sensing of Floodpath Lakes and Wetlands comprise featured articles reporting the latest innovative research and reflects the advancement in remote sensing applications on the theme topic. In this editorial paper, we review research developments using state-of-the-art remote sensing technologies for monitoring dynamics of floodpath lakes and wetlands; discuss challenges of remote sensing in inventory, monitoring, management, and governance of floodpath lakes and wetlands; and summarize the highlights of the articles published in this special issue.