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Remote Sensing of Algal Blooms: An Overview with Case Studies
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KLEMAS, V., 2012. Remote sensing of algal blooms: an overview with case studies. Journal of Coastal Research, 28(1A), 34–43. West Palm Beach (Florida), ISSN 0749-0208. High concentrations of nutrients from agricultural and urban runoff, or those produced by coastal upwelling, are causing algal blooms in many estuaries and coastal waters. Algal blooms induce eutrophic conditions, depleting oxygen levels needed by organic life, limiting aquatic plant growth by reducing water transparency, and producing toxins that can harm fish, benthic animals, and humans. The magnitude and frequency of phytoplankton blooms have increased globally in recent decades, as shown in data from ocean-color sensors on-board satellites. Satellite and airborne measurements of spectral reflectance (ocean color) represent an effective way for monitoring phytoplankton by its proxy, chlorophyll-a, the green pigment that is present in all algae. This article reviews the use of remote sensing techniques for detecting phytoplankton and mapping algal blooms. Two case studies are presented, illustrating the advantages and limitations of satellite and airborne remote sensing. www.JCRonline.org ADDITIONAL INDEX WORDS: Harmful algal blooms, remote sensing, eutrophication, phytoplankton blooms.
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... They are the foundation of food chains and webs in aquatic environments. When nutrient loading occurs from agricultural and urban runoff, the abundance of nutrients causes the concentrations of these microorganisms to grow uncontrollably, resulting in HABs [19]. Blooms typically occur in the spring when longer days provide stronger sunlight. ...
... Water warms and becomes less dense, allowing stratification. The upper stratified layer retains the bacteria where the sun is bright, and nutrients are plentiful [19]. ...
... It is estimated that freshwater algal blooms cost the nation nearly $4.8 billion annually [21]. Magnitude and frequency of HABs are increasing globally [19]. Early detection and comprehensive monitoring of HABs is needed to effectively manage and mitigate detrimental impacts [11]. ...
Water is the basis of all life on this planet. Yet, approximately one in seven people in the world do not have access to safe water. Water can become unsafe due to contamination by various organic and inorganic compounds due to various natural and anthropogenic processes. Identifying and monitoring water quality changes in space and time remains a challenge, especially when contamination events occur over large geographic areas. This study investigates recent advances in remote sensing that allow us to detect and monitor the unique spectral characteristics of water quality events over large areas. Based on an extensive literature review, we focus on three critical water quality problems as part of this study: algal blooms, acid mine drainage, and suspended solids. We review the advances made in applications of remote sensing in each of these issues, identify the knowledge gaps and limitations of current studies, analyze the existing approaches in the context of global environmental changes, and discuss potential ways to combine multi-sensor methods and different wavelengths to develop improved approaches. Synthesizing the findings of these studies in the context of the three specific tracks will help stakeholders to utilize, share, and embed satellite-derived earth observations for monitoring and tracking the ever-evolving water quality in the earth’s limited freshwater reserves.
... A higher NIR brings water closer to the impervious surface in the spectral form, making it more difficult to discern from vegetation and impervious surfaces. A possible explanation is that the water in urban areas contains more aquatic plants and algae due to eutrophic sewage released from urban production and households compared to natural sources of water [38,39]. The reflectance value of shadows was close to that of water in all bands, especially in the blue, green, and red bands, which may lead to the poor separation of water bodies based on these three bands only. ...
... A higher NIR brin water closer to the impervious surface in the spectral form, making it more difficul discern from vegetation and impervious surfaces. A possible explanation is that the wa in urban areas contains more aquatic plants and algae due to eutrophic sewage relea from urban production and households compared to natural sources of water [38,39]. T reflectance value of shadows was close to that of water in all bands, especially in the bl green, and red bands, which may lead to the poor separation of water bodies based these three bands only. ...
Urban water bodies are critical for sustainable urban ecological and social development. However, the complex compositions of urban land cover and small water bodies pose considerable challenges to urban water surface delineation. Here, we propose a novel urban water extraction algorithm (UWEA) that is efficient in distinguishing water and other low-reflective objects by combining the modified normalized difference water index (mNDWI) and HSV transformation. The spectral properties of urban land covers were analyzed and the separability of objects in different color spaces was compared before applying the HSV transformation. The accuracy and robustness of the UWEA were validated in six highly urbanized subregions of Beijing, Tokyo, and New York, and compared with the mNDWI and HIS methods. The results show that the UWEA had the fewest total errors (sum of omission and commission errors) for all the validation sites, which was approximately 3% fewer errors than those of the mNDWI and 17% fewer errors than those of the HIS method. The UWEA performed best because it was good at identifying small water bodies and suppressing reflective surfaces. The UWEA is effective in urban water monitoring and its thresholds are also robust in various situations. The resulting highly accurate water map could support water-related analyses. This method is also useful for scientists, managers, and planners in water resource management, urban hydrological applications, and sustainable urban development.
... Remotely sensed satellite imagery has great potential for monitoring environmental changes at fine spatiotemporal scales, yet has rarely been applied to hypoxia mapping (Chen et al., 2014;Matli et al., 2020). A few studies have indicated that remotely-sensed Chlorophyll a (Chlor-a) from satellite imagery, such as MODIS (Moderate Resolution Imaging Spectroradiometer) and SeaWiFS (Sea-viewing Wide Field-of-view Sensor), can serve as a surrogate for mapping algae bloom and ocean hypoxia by combining in-situ sampling data (Klemas, 2011;Chen et al., 2014;Le et al., 2016). A recent study attempted to use a linear regression approach to characterize the relationship between surface dissolved oxygen (DO) and satellite-derived variables, such as Chlor-a concentration and water temperature (Kim et al., 2020). ...
The growing number, size, and frequency of coastal hypoxia increasingly threaten marine ecosystem health and essential ecosystem services for human well-being. It is therefore urgent to use continuous and consistent observation and develop advanced tools to characterize and track the spatial and temporal change of coastal hypoxia. Satellite imagery with fine spatiotemporal resolution and global coverage has shown great potential for monitoring environmental changes, yet has rarely been applied to hypoxia mapping. To advance the understanding, we synthesized satellite-derived ocean color variables and dissolved oxygen measurements collected during 2014, and used random forest regression, lagged linear regression, and functional data analysis to estimate the spatiotemporal change of the hypoxia zone in the Gulf of Mexico. The three models achieved similar predictive accuracy (±1.2–1.4 mg/L dissolved oxygen), but the random forest regression performed the best in estimating the bottom dissolved oxygen from satellite-derived variables. Our models also revealed time lags of roughly 0–5 and 16–19 days between the surface water process (e.g., algae bloom and ocean warming) and bottom water hypoxia, which was rarely considered in previous hypoxia studies using satellite data. Finally, our models showed that the area of Gulf hypoxia increased gradually from May and reached a peak during mid-July and mid-August in 2014, and the hypoxia zone occurred in the estuary of the Mississippi River and Suwannee River during roughly 25% of summer days. In addition to predicting the size of hypoxic zones, our study provides additional information on where, when, and how long hypoxic zones persist with greater spatial details and enables modeling hypoxic zones at near-real-time (e.g., days) temporal scales. More importantly, we demonstrate the great potential of applying satellite remote sensing for spatially explicit hypoxia mapping, which could promote more cost-effective coastal hypoxia monitoring and assessment practices.
... Off the coast of the U.S., the size of the Gulf of Mexico hypoxic zone, the world's second largest oxygen-depleted "dead zone" (Dybas, 2005), can be tracked and modeled using satellite data (Haag et al., 2009), and contributions from changes in bioenergy-related land use can be estimated using satellite-based inputs (Donner and Kucharik, 2008;Hendricks et al., 2014). Similarly, satellite data have been used to track the size and occurrence of harmful algal blooms (Klemas, 2012;Shen et al., 2012) and estimate the contribution of bioenergy to water quality impairments (Hamada et al., 2015;Lin et al., 2015;Chen et al., 2017). Satellite data have also been critical in real-time monitoring of oil spills (see Figure 6). ...
Transitioning to a sustainable energy system poses a massive challenge to communities, nations, and the global economy in the next decade and beyond. A growing portfolio of satellite data products is available to support this transition. Satellite data complement other information sources to provide a more complete picture of the global energy system, often with continuous spatial coverage over targeted areas or even the entire Earth. We find that satellite data are already being applied to a wide range of energy issues with varying information needs, from planning and operation of renewable energy projects, to tracking changing patterns in energy access and use, to monitoring environmental impacts and verifying the effectiveness of emissions reduction efforts. While satellite data could play a larger role throughout the policy and planning lifecycle, there are technical, social, and structural barriers to their increased use. We conclude with a discussion of opportunities for satellite data applications to energy and recommendations for research to maximize the value of satellite data for sustainable energy transitions.
... In recent years, phytoplankton distribution monitoring by various techniques (satellite image processing [1][2][3][4][5][6][7][8][9][10], radar probing [11], laser remote sensing [12][13][14][15][16][17] and contact measurements with sample analysis [18][19][20][21]) has revealed an increased contamination of freshwater [22,23] and seawater areas [24] by blue-green algae. Phytoplankton blooms deplete dissolved oxygen, thus suppressing biodiversity in shallow waters and also poisoning them with biotoxins. ...
Harmful algal blooms in freshwater reservoirs became a steady phenomenon in recent decades, so instruments for monitoring water quality in real time are of high importance. Modern satellite remote sensing is a powerful technique for mapping large areas but cannot provide depth-resolved data on algal concentrations. As an alternative to satellite techniques, laser remote sensing is a perspective technique for depth-resolved studies of fresh or seawater. Recent progress in lasers and electronics makes it possible to construct compact and lightweight LiDARs (Light Detection and Ranging) that can be installed on small boats or drones. LiDAR sensing is an established technique; however, it is more common in studies of seas rather than freshwater reservoirs. In this study, we present an experimental verification of a compact LiDAR as an instrument for the shipborne depth profiling of chlorophyll concentration across freshwater Lake Kinneret (Israel). Chlorophyll depth profiles of 3 m with a 1.5 m resolution were measured in situ, under sunlight conditions. A good correlation (R2 = 0.89) has been established between LiDAR signals and commercial algae profiler (FluoroProbe, bbe Moldaenke) data. A non-monotonic algae depth distribution was observed along the boat route during daytime (Tiberias town -->Jordan River mouth -->Tiberias town). To estimate the LiDAR capability of in situ simultaneous measurements of temperature and chlorophyll concentrations, the impact of high algal concentrations on water temperature laser remote sensing has been studied in detail.
... Algal blooms, which are abnormal marine phenomena, have become a global problem in recent decades (Anderson et al., 2012;Klemas, 2011;Grattan et al., 2016;Sakamoto et al., 2021). Some of the related phytoplankton species can cause toxicity to sea products and human health (Wells et al., 2015;Sanseverino et al., 2016). ...
Long-term satellite missions could help to provide insights into spatial and temporal variations in algal blooms. However, the traditional reflectance-based method has limitations in regards to determining the available threshold for algal bloom detection among the time-varying observation conditions. In terms of extracting useful information from long-term data series precisely and efficiently, the deep learning method has shown its superiority over traditional algorithms in batch data processing. In this study, a U-net model for algal bloom extraction along the coast of the East China Sea was developed using GOCI images. The U-net model was trained with two different datasets that were constructed with six-band channels (all visible bands from GOCI imagery) and RGB-band channels (bands of 443, 555, and 680 nm from GOCI imagery). The quantitative assessment from the U-net models suggests that the U-net model trained with the six-band channel datasets outperformed the RGB-band channel datasets, with increases of 23.6%, 18.1%, and 12.5% in terms of accuracy, precision, and F-score, respectively. The validation map derived from the U-net model trained with six-band channel datasets also showed considerable matching with the ground-truth maps. By using the U-net model, the occurrence of algal blooms was automatically extracted from GOCI images. A 10-year time series of GOCI data collected between 2011 and 2020 was derived using an output-trained U-net model to explore spatial variation along the coast of the ECS. It was found that the most affected areas of the algal blooms varied by year, but were mainly located in the Zhoushan and Zhejiang coasts. Additionally, by performing principal component analysis on the daily meteorological data during April and August 2011–2020, factors related to algal bloom occurrence were discussed.
... Algae are unicellular prokaryotes, their growth is driven by light, nutrient (nitrate and phosphates) and temperature. These organisms are primary producers; produce food via photosynthesis and key foundation of marine and freshwater food chains and webs (Klemas, 2012). Freshwater ecosystems provide unique habitats, supports high level of biodiversity. ...
Phytoplankton blooms are closely coupled to physical processes. Increased access to wind, sea surface temperature, and ocean color datasets aids in retrospective analyses of bloom events and provides vital linkages of physical and biological processes. From such analyses, conceptual models of bloom initiation, transport, maintenance, and dissipation may help identify the timing of bloom initiation and define environmental conditions conducive to growth. The advent of on-line, real-time environmental data, new ocean color sensors, and hyperspectral scanners may allow enough predictive capability so that harmful or toxic bloom conditions can be detected, research efforts focused, and reliable information made available, before effects of these blooms are manifest in near shore areas.
Between January 18-20, 1995, a dinoflagellate algal bloom occurred in the Swan River, Western Australia. An airborne Digital Multi-Spectral Video (DMSV) system was used to acquire data on the bloom several times a day for three days. Simultaneous in-water data were gathered to determine the temporal and spatial dynamics of the algal concentrations. The study demonstrated the highly dynamic nature of algal blooms in space, depth, and time (within and between days), but the DMSV, limited by the existing band combinations, failed to show a strong qualitative relationship between physical and biological measurements. The results indicate that, to describe the bloom best, the timing of airborne data acquisition must be timed to coincide with movements of phytoplankton within the water column (such as daily afternoon migration of cells to the surface waters) and times of the day that will minimize sun-glint. Furthermore, ground truthing to calibrate or validate images must be carried out within a short period of airborne data acquisition because of the dynamic nature of the distributions of the phytoplankton cells. When blooms are rapidly changing, in-water sampling over large spatial scales, within short time spans, may be logistically impossible. In these situations, remote sensing provides an effective tool to capture the dynamic nature of the blooms in a qualitative sense.
Coastal zone, as defi ned by the Coastal Institute of the University of Rhode Island, includes areas of continental shelves, islands, or partially enclosed seas, estuaries, bays, lagoons, beaches, and terrestrial and aquatic ecosystems within watersheds that drain into coastal waters. The coastal zone is the most dynamic interface between land and sea and represents the most challenging frontier between human civilization and environmental conservation. Worldwide, over 38% of human population lives in the coastal zones (Crossett et al., 2004). In the United States, about 53% of the human population lives in the coastal counties (Small and Cohen, 2004). An increasing proportion of the global population lives within the coastal zones of all major continents that require increasing attention to agricultural, industrial, and other human-related effects on coastal habitats and water quality and their impacts on ecological dynamics, ecosystem health, and biological diversity.
Beginning systematically with the fundamentals, the fully-updated third edition of this popular graduate textbook provides an understanding of all the essential elements of marine optics. It explains the key role of light as a major factor in determining the operation and biological composition of aquatic ecosystems, and its scope ranges from the physics of light transmission within water, through the biochemistry and physiology of aquatic photosynthesis, to the ecological relationships that depend on the underwater light climate. This book also provides a valuable introduction to the remote sensing of the ocean from space, which is now recognized to be of great environmental significance due to its direct relevance to global warming. An important resource for graduate courses on marine optics, aquatic photosynthesis, or ocean remote sensing; and for aquatic scientists, both oceanographers and limnologists.
