121 research outputs found

    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

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    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

    SISTEM PERINGATAN DINI UNTUK MARAK ALGA MENGGUNAKAN CITRA SATELIT DI TELUK JAKARTA

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    Jakarta Bay is experiencing eutrophication, primarily due to nutrient inflows from agriculture, industry, and urban sources. This abundance of nutrients has led to significant algae blooms. A study using Terra and Aqua MODIS satellite data from 2004 to 2007 monitored these blooms by measuring chlorophyll-a levels. During this period, large-scale fish kills were observed directly related to the algal blooms, as evidenced by high chlorophyll-a concentrations and blooms covering more than a quarter of the bay. Interestingly, not all intense blooms resulted in massive fish kills. The study suggests that this mortality is primarily due to oxygen depletion after peak bloom periods, compounded by poor water circulation in the bay. Using satellite imagery to monitor algal blooms is a practical tool for implementing an early warning system (EWS) in Jakarta Bay. Satellite imagery has proven effective in monitoring these blooms and could help develop an early warning system in Jakarta Bay despite limitations such as cloud cover.Teluk Jakarta telah mengalami eutrofikasi, terutama disebabkan oleh masuknya nutrien dari sumber pertanian, industri, dan perkotaan. Kelimpahan nutrien ini telah menyebabkan terjadinya marak alga yang signifikan. Studi dengan menggunakan data satelit Terra dan Aqua MODIS dari tahun 2004 hingga 2007 telah memantau marak alga ini dengan mengukur tingkat klorofil-a. Selama periode ini, terjadi kematian massal ikan yang secara langsung terkait dengan peristiwa marak alga, seperti yang dibuktikan dengan tingginya konsentrasi klorofil-a dan marak alge yang menutupi lebih dari seperempat teluk. Menariknya, tidak semua marak alge yang intens mengakibatkan kematian ikan massal. Studi tersebut menunjukkan bahwa kematian ini terutama disebabkan oleh kekurangan oksigen setelah periode marak alge mencapai puncak, yang diperburuk oleh sirkulasi air yang lemah di teluk ini. Penggunaan citra satelit untuk memantau marak alga adalah alat yang praktis untuk menerapkan sistem peringatan dini (EWS) di Teluk Jakarta. Citra satelit telah terbukti efektif dalam memantau marak alga ini dan dapat membantu mengembangkan sistem peringatan dini di Teluk Jakarta meskipun terdapat keterbatasan seperti adanya penutupan awan

    Proceedings of the Workshop on Economic Impacts of Harmful Algal Blooms on Fisheries and Aquaculture

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    Earth Resources: A continuing bibliography with indexes, issue 16, January 1978

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    This bibliography lists 543 reports, articles, and other documents introduced onto the NASA scientific and technical information system between October 1 and December 31, 1977. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

    The use of operational harmful algal bloom monitoring systems in South Africa to assess long term changes to bloom occurrence & impacts for aquaculture

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    The south coast of South Africa is a very dynamic, productive, high energy environment and is considered to be a generally challenging setting for in-water aquaculture. One of the largest environmental threats to aquaculture are harmful algal blooms (HABs), a natural ecological phenomenon often accompanied by severe impacts on coastal resources and local economies. There is a wide variety of potentially harmful blooming species in the region, with impacts resulting from both toxicity and the negative effects associated with high biomass. While HABs are fairly well documented around the southern Benguela area, the primary concern is the lack of long-term data showing if blooms are becoming more frequent, persistent or are having greater impact over the last decades, consistent with environmental change experienced in the region. For this study, high-resolution satellite remote sensing observations from 16 years of MODIS-Aqua (1 km) and one month of Sentinel-3 OLCI (300 m), using regionally optimised blended algorithms, were used to investigate the spatial distribution and temporal variability of chlorophyll-a (Chl-a) along the south coast of South Africa. A Chl-a threshold of 27 mg mโˆ’3 was used as an analytic to identify the occurrence of high biomass blooms in the remote sensing data. Phytoplankton count data from aquaculture farms are used to provide information corresponding to changes in phytoplankton community structure, and to investigate the distribution and seasonal trends of HABs along the south coast. To further explore the spatial and temporal distribution, phytoplankton species considered harmful for this study were identified and classified to their seasonal occurrence: some species were consistently present throughout the years, however each region showed contrasting seasonality. A second interest of this study is linked to assessing the capacity of the aquaculture industry to make profitable use of existing observational and early warning tools. The impact of HABs on the environment or in aquaculture facilities can be potentially mitigated by increasing the industry awareness and early warnings of HAB development. In this regard, the Fisheries and Aquaculture Decision Support Tool (DeST) was used in order to develop short term alerts on HAB development. The EO analyses conducted here specifically use the same methods used by this DeST to demonstrate the use of this tool for historical analysis in addition to real time alerting. In order to evaluate the effectiveness of the tool and how the aquaculture farmers use the ABSTRACT information provided on the DeST, an online user feedback was generated, and distributed to all stakeholders via emai

    Optical discrimination among dinoflagellate species causing Harmful Algal Blooms (HABs) in Korean coastal waters

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    ์ด ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ ์—ฐ์•ˆ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์œ ํ•ด ์ ์กฐ(Harmful Algal blooms)๋ฅผ ๊ด‘ํ•™์ ์œผ๋กœ ๊ตฌ๋ณ„ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ๊ฐœ๋ฐœํ•˜๊ธฐ ์œ„ํ•ด ์ง„ํ–‰๋˜์—ˆ์œผ๋ฉฐ, ํŠนํžˆ ์ฃผ์š” ์œ ํ•ด ์ ์กฐ ์›์ธ ์ข…์œผ๋กœ ์•Œ๋ ค์ง„ ์™€ํŽธ๋ชจ์กฐ๋ฅ˜ Cochlodinium polykrikoides์— ์ดˆ์ ์„ ๋งž์ถ”์–ด ์ƒ๋ฌผ ๊ด‘ํ•™์  ํŠน์„ฑ์„ ํ™œ์šฉํ•œ ์ ์กฐ ํƒ์ง€ ๊ฐ€๋Šฅ์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ์‹คํ—˜์‹ค์—์„œ ๋ฐฐ์–‘ ์ค‘์ธ C. polykrikoides๋ฅผ ๋น„๋กฏํ•œ ๋‹ค๋ฅธ ์™€ํŽธ๋ชจ์กฐ๋ฅ˜ ์œ ํ•ด ์ ์กฐ ์ข…๋“ค์˜ ํก๊ด‘ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ์ธก์ •ํ•˜์—ฌ ์ ์กฐ ์ข…์ด ๊ฐ€์ง€๋Š” ๊ณ ์œ ํ•œ ํก๊ด‘ ํŠน์„ฑ์„ ํŒŒ์•…ํ•˜์˜€๋‹ค. ๋˜ํ•œ ์œ ํ•ด ์ ์กฐ ์ข…์˜ ๊ณ ์œ  ๊ด‘ ํŠน์„ฑ ์˜ํ•œ ๋ฐ˜์‚ฌ๋„ ์ŠคํŽ™ํŠธ๋Ÿผ์˜ ๋ถ„๊ด‘ ๋ฐ˜์‘์„ ๋ฐ”ํƒ•์œผ๋กœ ๊ด‘ํ•™์  ๊ตฌ๋ณ„ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์— ํ™œ์šฉ๋œ ๋ฐ˜์‚ฌ๋„ ์ŠคํŽ™ํŠธ๋Ÿผ(N = 2,275)์€ ์‹คํ—˜์œผ๋กœ ์ธก์ •ํ•œ ์ ์กฐ ์ข… ํก๊ด‘ ์ž๋ฃŒ์™€ International Ocean-Color Coordinating Group์—์„œ ์ œ๊ณตํ•˜๋Š” ์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๊ด‘ํ•™ ๋ชจ๋ธ์ธ Hydrolight๋ฅผ ํ†ตํ•ด ๋ชจ์˜๋˜์—ˆ๋‹ค. ํ•ด์ˆ˜์˜ ๋ฐ˜์‚ฌ๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ํ•ด์ˆ˜ ๊ตฌ์„ฑ์š”์†Œ์˜ ๋†๋„๋ฅผ ๋‹ค์–‘ํ•˜๊ฒŒ ์„ค์ •ํ•˜์—ฌ ํญ๋„“์€ ๊ด‘ํ•™์  ์กฐ๊ฑด์„ ํฌ๊ด„ํ•˜๋Š” 2,275๊ฐœ์˜ ๋ฐ˜์‚ฌ๋„ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ์ƒ์„ฑํ•˜์˜€๋‹ค. ๋ชจ์˜ ๋œ ๋ฐ˜์‚ฌ๋„ ์ŠคํŽ™ํŠธ๋Ÿผ ์ž๋ฃŒ๋ฅผ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ, C. polykrikoides๋ฅผ ํฌํ•จํ•œ 4 ์ข…์˜ ์œ ํ•ด ์ ์กฐ ์ข…์˜ ๋ฐ˜์‚ฌ๋„ ์ŠคํŽ™ํŠธ๋Ÿผ ๊ฐ„์—๋Š” ๋†’์€ ์œ ์‚ฌ๋„๋ฅผ ๋ณด์ธ ๋ฐ˜๋ฉด, ์ ์กฐ๊ฐ€ ์•„๋‹Œ ๊ฒฝ์šฐ์˜ ๋ฐ˜์‚ฌ๋„์™€ ์ ์กฐ์ธ ๊ฒฝ์šฐ์˜ ๋ฐ˜์‚ฌ๋„๋Š” ๋šœ๋ ทํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ํŠนํžˆ, C. polykrikoides ์ ์กฐ์ธ ๊ฒฝ์šฐ์— ์ฒญ-๋…น ํŒŒ์žฅ์—์„œ ๋ณด์ด๋Š” ๊ณ ์œ ํ•œ ํก๊ด‘ ํŠน์„ฑ์ด ๋ฐ˜์‚ฌ๋„์— ์˜ํ–ฅ์„ ์คŒ์œผ๋กœ์จ ์ ์กฐ๊ฐ€ ์•„๋‹Œ ๊ฒฝ์šฐ์˜ ๋ฐ˜์‚ฌ๋„์™€ ๊ตฌ๋ณ„๋˜๋Š” ํŠน์ง•์„ ๋ณด์˜€๊ณ  ์ด ์ฐจ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ C. polykrikoides ๊ตฌ๋ณ„ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค. R1: Rrs(555)/Rrs(531)์™€ R2: Rrs(488)/Rrs(443), ๋‘ ๋ฐ˜์‚ฌ๋„ ๋ฐด๋“œ ๋น„๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ ์กฐ๊ฐ€ ์•„๋‹Œ ๊ฒฝ์šฐ๋กœ๋ถ€ํ„ฐ ํšจ๊ณผ์ ์œผ๋กœ C. polykrikoides blooms๋ฅผ ๊ตฌ๋ณ„ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ชจ์˜ ๋œ ๋ฐ˜์‚ฌ๋„ ์ž๋ฃŒ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ œ์•ˆ ๋œ ๋‘ ๋ฐ˜์‚ฌ๋„ ๋ฐด๋“œ ๋น„๋ฅผ ์‹ค์ œ ํ•œ๊ตญ ์—ฐ์•ˆ์—์„œ ์ธก์ •ํ•œ ๋ฐ˜์‚ฌ๋„์— ์ ์šฉํ•œ ๊ฒฐ๊ณผ, C. polykrikoides ์ ์กฐ์™€ ์ ์กฐ๊ฐ€ ์•„๋‹Œ ํ•ด์—ญ์ด ๋ช…ํ™•ํžˆ ๊ตฌ๋ณ„๋˜์—ˆ๋‹ค. ํ•œ๊ตญ ์—ฐ์•ˆ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์œ ํ•ด ์ ์กฐ ์ข…์˜ ๊ด‘ ํŠน์„ฑ ๋ฐ ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ œ์•ˆ ๋œ ๋ฐ˜์‚ฌ๋„ ๋ฐด๋“œ ๋น„ ๊ตฌ๋ณ„ ๋ฐฉ๋ฒ• ๋“ฑ์˜ ๋ถ„์„ ๊ฒฐ๊ณผ๋“ค์€ ์ถ”ํ›„ in-water ์ ์กฐ ํƒ์ง€ ์•Œ๊ณ ๋ฆฌ๋“ฌ ๋ฐ ์œ„์„ฑ ์ ์กฐ ํƒ์ง€ ์•Œ๊ณ ๋ฆฌ๋“ฌ ๊ฐœ๋ฐœ์„ ์œ„ํ•œ ์ด๋ก ์ , ์ •๋Ÿ‰์  ๊ธฐ์ค€์„ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.List of Tables iv List of Figures v List of Abbreviations viii Abstract x 1. Introduction 1.1 Background 1 1.2 Problem statement 4 1.3 Research aim and approach 8 2. Data and Methods 2.1 Radiometric observations and discrete water samples 9 2.2 Optical parameter measurements 11 2.2.1 Phytoplankton absorption and Chlorophyll a 11 2.2.2 Absorption of colored dissolved organic matter (CDOM) 14 2.3 Hyperspectral Rrs simulation using Hydrolight 15 2.4 Derivative analysis and similarity index 19 3. Results 3.1 Light absorption of HAB species 20 3.2 Comparison of aph in in situ and culture samples 25 3.3 Comparison of hyperspectral remote sensing reflectance (Rrs) 27 3.3.1 in situ Rrs spectra 27 3.3.2 Rrs of HAB species and Unspecified Phytoplankton Assemblages 29 3.3.3 Similarity index between C. polykrikoides and other species 31 3.4 Optical discrimination of C. polykrikoides from other species 33 4. Discussion 36 4.1 Similarity of Rrs(ฮป) characteristics among dinoflagellate HAB species 37 4.2 Distribution of C. polykrikoides blooms and UPA in Rrs ratio space 39 4.3 Uncertainties in the simulation 42 5. Conclusion 44 Acknowledgements 46 References 48 Appendix A Model input data 55Maste

    Harmful algal blooms in the PICES region of the North Pacific

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    Foreword Background and objectives [pdf, 0.84 MB] Country reviews and status reports Section I. Western North Pacific Japan Yasuwo Fukuyo, Ichiro Imai, Masaaki Kodama and Kyoichi Tamai Red tides and harmful algal blooms in Japan [pdf, 0.7 MB] People's Republic of China Tian Yan, Ming-Jiang Zhou and Jing-Zhong Zou A national report of HABs in China [pdf, 0.24 MB] Republic of Korea Sam Geun Lee, Hak Gyoon Kim, Eon Seob Cho and Chang Kyu Lee Harmful algal blooms (red tides): Management and mitigation in Korea [pdf, 0.27 MB] Russia Tatiana Y. Orlova, Galina V. Konovalova, Inna V. Stonik, Tatiana V. Morozova and Olga G. Shevchenko Harmful algal blooms on the eastern coast of Russia [pdf, 1.4 MB] Section II. Eastern North Pacific Canada F.J.R. "Max" Taylor and Paul J. Harrison Harmful marine algal blooms in western Canada [pdf, 0.87 MB] United States of America Vera L. Trainer Harmful algal blooms on the U.S. west coast [pdf, 0.5 MB] Mexico Jose L. Ochoa, S. Lluch-Cota, B.O. Arredondo-Vega, E. Nuรฑes-Vรกzquez, A. Heredia-Tapia, J. Pรฉrez-Linares and R. Alonso-Rodriguez Marine Biotoxins and harmful algal blooms in Mexico's Pacific littora [pdf, 0.2 MB] Summary and conclusions [pdf, 0.6 MB] Appendices A. Members of the Working Group [pdf, 0.1 MB] B. Original terms of reference (Vladivostok, 1999) [pdf, 0.08 MB] C. Annual reports of WG 15 [pdf, 0.15 MB] D. Workshop report on taxonomy and identification of HAB species and data management [pdf, 0.15 MB] (Document pdf contains 156 pages

    Remotely Sensed Assessment of the Preferred Habitat of Alexandrium catenella in the Gulf of Maine and the Bay of Fundy

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    Harmful Algal Blooms (HABs) of the toxic dinoflagellate Alexandrium catenella are an annually recurring problem in the Gulf of Maine (GoM), resulting in risks to human health and substantial economic losses due to shellfish harvesting closures. The monitoring approaches in the region are restricted to real-time identification of the HABs events, when they are clearly underway and already causing deleterious effects to the environment. To fully function as an early warning system rather than an immediate response, monitoring strategies need to be focused on environmental conditions preceding A. catenella HABs. However, the current understanding of the preferred habitat for A. catenella in the GoM is still scarce due to the complex interactions between this organism and the environment. My dissertation research contributes to the solution of these problems by determining the preferred thermal habitat for A. catenella, contrasting environmental conditions for two extremes in A. catenella concentration, and exploring the benefits of using high resolution spectral data to characterize the GoM surface waters. This dissertation is focused on the application of current and future remote sensing technology to the measurement and management of GoM HABs. Chapter 1 briefly introduces the problematic of HABs, monitoring efforts and the study species. Chapter 2 characterizes the interannual variability in the thermal habitat and bloom phenology of A. catenella in the Bay of Fundy, identifying the environmental conditions associated with this variability and its responses to climate change. Chapter 3 contrasts the optical and thermal conditions associated with two extremes in A. catenella concentration over multiple years and areas in the GoM and establishes a set of typical water types for each concentration category. Chapter 4 characterizes the spatial and temporal variability of hyperspectral reflectance of surface waters in the GoM and determines the advantage of hyperspectral resolution over multispectral to identify important spatial patterns and regions. Chapter 5 will conclude with a discussion on the implications of these results to monitoring efforts in the GoM, implications of climate change, and discusses future directives to further explore habitat suitability approaches in monitoring efforts

    Earth resources. A continuing bibliography with indexes, issue 23

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    This bibliography lists 226 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1, 1979 and September 30, 1979. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis
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