Optical Satellite Remote Sensing of the Coastal Zone Environment — An Overview

Optical remote-sensing data are a powerful source of information for monitoring the coastal environment. Due to the high complexity of coastal environments, where different natural and anthropogenic phenomenon interact, the selection of the most appropriate sensor(s) is related to the applications required, and the different types of resolutions available (spatial, spectral, radiometric, and temporal) need to be considered. The development of specific techniques and tools based on the processing of optical satellite images makes possible the production of information useful for coastal environment management, without any destructive impacts. This chapter will highlight different subjects related to coastal environments: shoreline change detection, ocean color, water quality, river plumes, coral reef, alga bloom, bathymetry, wetland mapping, and coastal hazards/vulnerability. The main objective of this chapter is not an exhaustive description of the image processing methods/algorithms employed in coastal environmental studies, but focus in the range of applications available. Several limitations were identified. The major challenge still is to have remote-sensing techniques adopted as a routine tool in assessment of change in the coastal zone. Continuing research is required into the techniques employed for assessing change in the coastal environment

Multi-temporal assessment of chlorophyll-a concentration in estuarine waters: a case study of sundays and swartkops estuaries, Eastern Cape Province

Estuaries are productive and delicate marine systems, which are of commercial, recreational and aesthetic value as they reflect the land use of a catchment by creating “nutrient traps”, these nutrients are absorbed by water and later released into the coastal oceans. Disturbances in an estuary influence a wide variety of habitats and organisms in a marine ecosystem, for example, high chlorophyll-a affects marine species that utilize calm waters, food and turbid water found in estuaries. The degradation of South African estuaries is an on-going accelerating process; therefore, there is a need for preservation measures for estuarine ecosystems by means of monitoring nutrient flow. This research was aimed at assessing the use of OLCI ocean color products in monitoring chl-a concentration and impacts of the estuaries in Algoa Bay. OLCI on the Sentinel platforms, coupled with OCNN and OC4ME algorithms were employed to assess the distribution of chlorophyll-a in Swartkops and Sunday’s estuaries. OC4Me and OCNN are the default models designed for OLCI data. However, the OLCI resolution was not able to measure the chl-a concentration within these estuaries. Therefore, satellite product assessment was primarily focused on the Algoa bay scale due to the resolution of the available data. SNAP and Matlab were applied for the production of the final products. Accuracy assessment was used to check the agreement between the in situ datasets of chl-a and the final processed satellite products. Results of this investigation point that OCNN did not perform well in the study as compared to OC4Me and it did not produce accurate results in areas with very high biomass concentration. The research concludes by recommending the use of higher resolution data such as Sentinel 2 MSI (10m, 20m, and 60m resolution) for resolving chlorophyll-a within these estuaries

A Semi-analytical Model for Remote Sensing Retrieval of Suspended Sediment Concentration in the Gulf of Bohai, China

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Investigation of Colored Dissolved Organic Matter and Dissolved Organic Carbon Using Combination of Ocean Color Data and Numerical Model in the Northern Gulf of Mexico

The first part of this thesis includes evaluating and developing empirical band ratio algorithms for the estimation of colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC) for SeaWiFS, MODIS and MERIS ocean color sensors for the northern Gulf of Mexico. For CDOM, matchup comparison between SeaWiFS-derived CDOM absorption coefficients and in situ absorption measurements at 412 nm (aCDOM(412)) were examined using the D’Sa et al. (2006) and the Mannino et al. (2008) algorithms. These reflectance band ratio algorithms were also assessed to retrieve aCDOM(412) from MODIS and MERIS data using the Rrs(488)/Rrs(555) and Rrs(510)/Rrs(560) band ratios, respectively. Since DOC cannot be measured directly by remote sensors, CDOM as the colored component of DOC is utilized as a proxy to estimate DOC remotely. A seasonal relationship between CDOM and DOC was established for the summer and spring-winter with high correlation for both periods. Seasonal band ratio empirical algorithms to estimate DOC were thus developed. In the second part of this study, a numerical model to study CDOM dynamics in the northern Gulf of Mexico was examined. To derive surface CDOM concentration maps from simulated salinity output from the Navy Coastal Ocean Model (NCOM), a highly correlated linear inverse relationship between CDOM and salinity is required which was examined for both inner-shelf and outer-shelf areas for the spring-winter and the summer periods. Applying these relationships on NCOM simulated salinity resulted in hourly maps of CDOM exhibiting high consistency with CDOM patterns derived from SeaWiFS sensor. Overlaying the NCOM-derived CDOM maps on the simulated currents showed the profound effect of currents on CDOM advection. Cold fronts strongly impact CDOM advection in both the inner and outer shelves by flushing CDOM-laden waters out of the coastal bays

Optical detection of a <i>Noctiluca scintillans</i> bloom

Noctiluca scintillans blooms are often observed as reddish patches in Belgian waters in June-July in calm weather. The possibility of mapping these blooms is investigated here. In June 2005 a dataset of in situ measured reflectance spectra, airborne hyperspectral images, experimental reflectance and absorption spectra of Noctiluca scintillans was collected. The strong optical signature of dense Noctiluca scintillans blooms suggests that mapping these blooms should be feasible. A detection algorithm is proposed based on a combination of a high reflectance threshold with a condition of sharp increase in reflectance in the range 520-580 nm. This algorithm will detect only intense blooms but should distinguish between Noctiluca scintillans and both intense phytoplankton blooms and very turbid water. Noctiluca scintillans detection by optical sensors mounted on ships and airplanes has been confirmed for the June 2005 bloom in Belgian waters. Detection from satellites should also be feasible but only if suitable wavelengths are available and only if the spatial resolution is sufficiently high. The optical properties of this species are thought to be related to gut content. The applicability of this algorithm to other regions and situations therefore remains to be tested

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD)

Spatial and temporal dynamics of suspended sediment concentrations in coastal waters of the South China Sea, off Sarawak, Borneo: ocean colour remote sensing observations and analysis

High-quality ocean colour observations are increasingly accessible to support various monitoring and research activities for water quality measurements. In this paper, we present a newly developed regional total suspended solids (TSSs) empirical model using MODIS Aqua's Rrs(530) and Rrs(666) reflectance bands to investigate the spatial and temporal variation in TSS dynamics along the southwest coast of Sarawak, Borneo, with the application of the Open Data Cube (ODC) platform. The performance of this TSS retrieval model was evaluated using error metrics (bias = 1.0, MAE = 1.47, and RMSE = 0.22, in milligrams per litre) with a log10 transformation prior to calculation as well as using a k-fold cross-validation technique. The temporally averaged map of the TSS distribution, using daily MODIS Aqua satellite datasets from 2003 until 2019, revealed that large TSS plumes were detected – particularly in the Lupar and Rajang coastal areas – on a yearly basis. The average TSS concentration in these coastal waters was in the range of 15–20 mg L−1. Moreover, the spatial map of the TSS coefficient of variation (CV) indicated strong TSS variability (approximately 90 %) in the Samunsam–Sematan coastal areas, which could potentially impact nearby coral reef habitats in this region. Study of the temporal TSS variation provides further evidence that monsoonal patterns drive the TSS release in these tropical water systems, with distinct and widespread TSS plume variations observed between the northeast and southwest monsoon periods. A map of relative TSS distribution anomalies revealed strong spatial TSS variations in the Samunsam–Sematan coastal areas, while 2010 recorded a major increase (approximately 100 %) and widespread TSS distribution with respect to the long-term mean. Furthermore, study of the contribution of river discharge to the TSS distribution showed a weak correlation across time at both the Lupar and Rajang river mouth points. The variability in the TSS distribution across coastal river points was studied by investigating the variation in the TSS pixels at three transect points, stretching from the river mouth into territorial and open-water zones, for eight main rivers. The results showed a progressively decreasing pattern of nearly 50 % in relation to the distance from shore, with exceptions in the northeast regions of the study area. Essentially, our findings demonstrate that the TSS levels on the southwest coast of Sarawak are within local water quality standards, promoting various marine and socio-economic activities. This study presents the first observation of TSS distributions in Sarawak coastal systems with the application of remote sensing technologies and aims at enhancing coastal sediment management strategies for the sustainable use of coastal waters and their resources.</p

A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans

The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors' data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters

Influence of suspended sediment front on nutrients and phytoplankton dynamics off the Changjiang Estuary: A FVCOM-ERSEM coupled model experiment

Under embargo until: 2021-12-27High-turbidity water is a common feature in the estuary and inner shelf. Sediment suspension functions as a modulator that directly influences the interactions among nutrients, phytoplankton and other related ecosystem variables. A physical-biological coupling model system was applied to examine the impact of sediment front on interactions among on suspended sediment, vertical mixing, nutrients and phytoplankton over the inner shelf off the high-turbidity, phosphate-limited Changjiang Estuary. The physical model was the Finite-Volume Community Ocean Model (FVCOM) and the biological model was the European Regional Seas Ecosystem Model (ERSEM). Results revealed that in the nearshore region the growth of phytoplankton over the spring-summer seasons was limited by suspended sediments and intensified vertical mixing during the autumn-winter seasons extended the sediment-induced suppression extended offshore to restrict the phytoplankton growth over the shelf. Nutrients were diluted by spreading of freshwater discharge and significantly decreased off the suspended sediment front due to the depletion by the offshore phytoplankton growth. The simulation results showed that although the diatom phytoplankton dominated the Chlorophyll a (Chl-a) concentration, the non-diatom group had a more contribution to the biomass. The relatively high phytoplankton biomass was found over the offshore deep underwater valley area as results of remote advection by the Taiwan Warm Current and weak turbulent mixing.acceptedVersio

A Reconstruction Method for Hyperspectral Remote Sensing Reflectance in the Visible Domain and Applications

A reconstruction method was developed for hyperspectral remote sensing reflectance (Rrs)data in the visible domain (400–700 nm) based on in situ observations. A total of 2,647 Rrs spectra were collected over a wide variety of water environments including open ocean, coastal and inland waters. Ten schemes with different band numbers (6 to 15) were tested based on a nonlinear model. It was found that the accuracy of the reconstruction increased with the increase of input band numbers. Eight of these schemes met the accuracy criterion with the mean absolute error (MAE) and mean relative error (MRE)values between reconstructed and in situ Rrs less than 0.00025 sr-1 and 5%, respectively. We chose the eight-band scheme for further evaluation because of its decent performance. The results revealed that the parameterization derived by the eight-band scheme was efficient for restoring Rrs spectra from different water bodies. In contrast to the previous studies that used a linear model with 15 spectral bands, the nonlinear model with the eight-band scheme yielded a comparable reconstruction performance. The MAE andMRE values were generally less than 0.00016 sr-1 and 3% respectively; much lower than the uncertainties in satellite-derived Rrs products. Furthermore, a preliminary experiment of this method on the data from the Hyperspectral Imager for the Coastal Ocean (HICO) showed high potential in the future applications for reconstructing Rrs spectra from space-borne optical sensors. Overall, the eight-band scheme with our non-linear model was proven to be optimal for hyperspectral Rrs reconstruction in the visible domain