3.9 Article

Water residence time affecting phytoplankton blooms: study case in Ibitinga Reservoir (Sao Paulo, Brazil) using Landsat/TM images

期刊

BRAZILIAN JOURNAL OF BIOLOGY
卷 76, 期 3, 页码 664-672

出版社

INT INST ECOLOGY
DOI: 10.1590/1519-6984.23814

关键词

Landsat TM4/TM3 band ratios; chlorophyll-a; phytoplankton bloom; hydraulic residence time

类别

向作者/读者索取更多资源

Satellite images are an effective tool for the detection of phytoplankton blooms, since they cause striking changes in water color. Bloom intensity can be expressed in terms of chlorophyll-a concentration. Previous studies suggest the use of Landsat TM4/TM3 reflectance ratio to retrieve surface chlorophyll-a concentration from aquatic systems. In this study we assumed that a remote sensing trophic state index can be applied to investigate how changes in HRT along the hydrologic year affect the spatial distribution of the phytoplankton blooms at Ibitinga's reservoir surface. For that, we formulated two objectives: (1) apply a semi-empirical model which uses this reflectance ratio to map chlorophyll-a concentration at Ibitinga reservoir along the 2005 hydrologic year and (2) assess how changes in hydraulic residence time (HRT) affect the spatial distribution of phytoplankton blooms at Ibitinga Reservoir. The study site was chosen because previous studies reported seasonal changes in the reservoir limnology which might be related to the reservoir seasonality and hydrodynamics. Six Landsat/TM images were acquired over Ibitinga reservoir during 2005 and water flow measurements provided by the Brazilian Electric System National Operator - ONS were used to compute the reservoir's residence time, which varied from 5.37 to 52.39 days during 2005. The HRT in the date of image acquisition was then compared to the distribution of chlorophyll-a in the reservoir. The results showed that the HRT increasing implies the increasing of the reservoir surface occupied by phytoplankton blooms.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.9
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Environmental Sciences

Land-use intensity of official mineral extraction in the Amazon region: Linking economic and spatial data

Pedro Walfir M. Souza-Filho, Felipe de Lucia Lobo, Rosane Barbosa Lopes Cavalcante, Jose Aroudo Mota, Wilson da Rocha Nascimento, Diogo C. Santos, Evlyn M. L. M. Novo, Claudio Clemente Faria Barbosa, Jose O. Siqueira

Summary: The Amazon region has seen significant deforestation due to mining activities, with gold mining being the major contributor. Mining in protected areas is dominated by artisanal gold mining, while industrial-scale iron ore mining has relatively lower impacts on mining areas.

LAND DEGRADATION & DEVELOPMENT (2021)

Article Environmental Sciences

AlgaeMAp: Algae Bloom Monitoring Application for Inland Waters in Latin America

Felipe de Lucia Lobo, Gustavo Willy Nagel, Daniel Andrade Maciel, Lino Augusto Sander de Carvalho, Vitor Souza Martins, Claudio Clemente Faria Barbosa, Evlyn Marcia Leao de Moraes Novo

Summary: This paper discusses the development of a water quality monitoring system based on remote sensing imagery, specifically focusing on creating a cloud-computing interface on Google Earth Engine. This system allows users to access algae bloom related products with high spatial and temporal resolution. The proposed methodology uses Sentinel-2 images to generate an image collection of the Normalized Difference Chlorophyll-a Index, estimating Chl-a concentration and Trophic State Index.

REMOTE SENSING (2021)

Article Marine & Freshwater Biology

Variability of bio-optical properties in nearshore waters of the estuary and Gulf of St. Lawrence: Absorption and backscattering coefficients

Carlos A. S. Araujo, Simon Belanger

Summary: The inherent optical properties and optically significant constituents in the nearshore zones of the Estuary and Gulf of St. Lawrence were investigated. The study provided a detailed characterization of dissolved organic matter and particulate matter, and revealed the dominant control processes and seasonal variations. The findings contribute to the development of remote sensing algorithms for monitoring biogeochemically relevant constituents in the water.

ESTUARINE COASTAL AND SHELF SCIENCE (2022)

Article Environmental Sciences

Phytoplankton Genera Structure Revealed from the Multispectral Vertical Diffuse Attenuation Coefficient

Cleber Nunes Kraus, Daniel Andrade Maciel, Marie Paule Bonnet, Evlyn Marcia Leao de Moraes Novo

Summary: This research investigated the use of multispectral vertical diffuse attenuation coefficient of downward irradiance (K-d) gradients in accessing phytoplankton genera. The results suggest that phytoplankton genera are organized based on their ability to use light intensity and different spectral ranges of visible light, with changes in light availability seasonally impacting phytoplankton structure. The study provides valuable insights into describing phytoplankton communities in tropical freshwater floodplains using orbital data, and the approach can be used to assess phytoplankton diversity in these environments.

REMOTE SENSING (2021)

Article Environmental Sciences

Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images

Rejane S. Paulino, Vitor S. Martins, Evlyn M. L. M. Novo, Claudio C. F. Barbosa, Lino A. S. de Carvalho, Felipe N. Begliomini

Summary: This research used a physical-based approach with three empirical methods to correct and characterize the adjacency effects in Sentinel-2 images over Brazilian inland waters. The importance of determining the H-Adj parameter for low water reflectance values was highlighted, and the importance of adjacency correction under high aerosol loading and extremely dark, low-reflectance waters was emphasized.

REMOTE SENSING (2022)

Article Environmental Sciences

Environmental niches and seasonal succession of phytoplankton assemblages in a subarctic coastal bay: Applications to remote sensing estimates

Carlos A. S. Araujo, Claude Belzile, Jean-Eric Tremblay, Simon Belanger

Summary: This study investigated the seasonal and spatial variability of surface phytoplankton assemblages and associated environmental niches in a human-impacted subarctic coastal bay in Quebec, Canada. The results showed that the phytoplankton assemblages in the Bay of Sept-iles were more diverse than in the central portion of the St. Lawrence Estuary. The temporal distribution of the phytoplankton assemblages reflected the major seasonal signal of the nearshore subarctic environment.

FRONTIERS IN MARINE SCIENCE (2022)

Article Environmental Sciences

Assessment of Estimated Phycocyanin and Chlorophyll-a Concentration from PRISMA and OLCI in Brazilian Inland Waters: A Comparison between Semi-Analytical and Machine Learning Algorithms

Thainara Munhoz Alexandre de Lima, Claudia Giardino, Mariano Bresciani, Claudio Clemente Faria Barbosa, Alice Fabbretto, Andrea Pellegrino, Felipe Nincao Begliomini

Summary: The aim of this study is to test the accuracy of state-of-the-art water constituent retrieval algorithms for phycocyanin (PC) and chlorophyll-a (chl-a) concentrations in Brazilian reservoirs. The algorithms were tested on PRISMA and Sentinel-3 OLCI data, with a focus on PC mapping using OLCI data for its high revisit time. The results suggest that applying the Semi-Analytical algorithm to PRISMA and OLCI data can accurately detect PC in Brazilian reservoirs.

REMOTE SENSING (2023)

Correction Multidisciplinary Sciences

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality (vol 10, 100, 2023)

Moritz K. Lehmann, Daniela Gurlin, Nima Pahlevan, Krista Alikas, Ted Conroy, Janet Anstee, Sundarabalan V. Balasubramanian, Claudio C. F. Barbosa, Caren Binding, Astrid Bracher, Mariano Bresciani, Ashley Burtner, Zhigang Cao, Arnold G. Dekker, Courtney Di Vittorio, Nathan Drayson, Reagan M. Errera, Virginia Fernandez, Dariusz Ficek, Cedric G. Fichot, Peter Gege, Claudia Giardino, Anatoly A. Gitelson, Steven R. Greb, Hayden Henderson, Hiroto Higa, Abolfazl Irani Rahaghi, Cedric Jamet, Dalin Jiang, Thomas Jordan, Kersti Kangro, Jeremy A. Kravitz, Arne S. Kristoffersen, Raphael Kudela, Lin Li, Martin Ligi, Hubert Loisel, Steven Lohrenz, Ronghua Ma, Daniel A. Maciel, Tim J. Malthus, Bunkei Matsushita, Mark Matthews, Camille Minaudo, Deepak R. Mishra, Sachidananda Mishra, Tim Moore, Wesley J. Moses, Ha Nguyen, Evlyn M. L. M. Novo, Stefani Novoa, Daniel Odermatt, David M. O'Donnell, Leif G. Olmanson, Michael Ondrusek, Natascha Oppelt, Sylvain Ouillon, Waterloo Pereira Filho, Stefan Plattner, Antonio Ruiz Verdu, Salem I. Salem, John F. Schalles, Stefan G. H. Simis, Eko Siswanto, Brandon Smith, Ian Somlai-Schweiger, Mariana A. Soppa, Evangelos Spyrakos, Elinor Tessin, Hendrik J. van der Woerd, Andrea Vander Woude, Ryan A. Vandermeulen, Vincent Vantrepotte, Marcel R. Wernand, Mortimer Werther, Kyana Young, Linwei Yue

SCIENTIFIC DATA (2023)

Article Multidisciplinary Sciences

GLORIA-A globally representative hyperspectral in situ dataset for optical sensing of water quality

Moritz K. Lehmann, Daniela Gurlin, Nima Pahlevan, Krista Alikas, Janet Anstee, Sundarabalan V. Balasubramanian, Claudio C. F. Barbosa, Caren Binding, Astrid Bracher, Mariano Bresciani, Ashley Burtner, Zhigang Cao, Arnold G. Dekker, Courtney Di Vittorio, Nathan Drayson, Reagan M. Errera, Virginia Fernandez, Dariusz Ficek, Cedric G. Fichot, Peter Gege, Claudia Giardino, Anatoly A. Gitelson, Steven R. Greb, Hayden Henderson, Hiroto Higa, Abolfazl Irani Rahaghi, Cedric Jamet, Dalin Jiang, Thomas Jordan, Kersti Kangro, Jeremy A. Kravitz, Arne S. Kristoffersen, Raphael Kudela, Lin Li, Martin Ligi, Hubert Loisel, Steven Lohrenz, Ronghua Ma, Daniel A. Maciel, Tim J. Malthus, Bunkei Matsushita, Mark Matthews, Camille Minaudo, Deepak R. Mishra, Sachidananda Mishra, Tim Moore, Wesley J. Moses, Ha Nguyen, Evlyn M. L. M. Novo, Stefani Novoa, Daniel Odermatt, David M. O'Donnell, Leif G. Olmanson, Michael Ondrusek, Natascha Oppelt, Sylvain Ouillon, Waterloo Pereira Filho, Stefan Plattner, Antonio Ruiz Verdu, Salem I. Salem, John F. Schalles, Stefan G. H. Simis, Eko Siswanto, Brandon Smith, Ian Somlai-Schweiger, Mariana A. Soppa, Evangelos Spyrakos, Elinor Tessin, Hendrik J. van der Woerd, Andrea Vander Woude, Ryan A. Vandermeulen, Vincent Vantrepotte, Marcel R. Wernand, Mortimer Werther, Kyana Young, Linwei Yue

Summary: The development of algorithms for remote sensing of water quality requires a large amount of in situ data to consider the bio-geo-optical diversity of inland and coastal waters. The GLORIA dataset includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range, contributed by researchers affiliated with 59 institutions worldwide. This dataset provides a comprehensive reference for practitioners planning similar measurements and enables scientific and technological advancement towards operational regional and global water quality monitoring.

SCIENTIFIC DATA (2023)

Letter Limnology

Validity of the Landsat surface reflectance archive for aquatic science: Implications for cloud-based analysis

Daniel Andrade Maciel, Nima Pahlevan, Claudio Clemente Faria Barbosa, Evlyn Marcia Leao de Moraes de Novo, Rejane Souza Paulino, Vitor Souza Martins, Eric Vermote, Christopher J. Crawford

Summary: The US Geological Survey Landsat surface reflectance (SR) archive, originally developed for terrestrial science, is increasingly being used in large-scale water-quality studies. However, these products have not been rigorously validated using in situ measured reflectance. This study quantifies and demonstrates the quality of the SR products using a global dataset (N = 1100). It found that the Landsat 8/9 SR in the green and red bands meet the accuracy requirements, but there are uncertainties and biases in the blue, coastal-aerosol, and visible bands that need to be addressed for advanced applications.

LIMNOLOGY AND OCEANOGRAPHY LETTERS (2023)

Article Environmental Sciences

Holistic environmental monitoring in ports as an opportunity to advance sustainable development, marine science, and social inclusiveness

Filippo Ferrario, Carlos A. S. Araujo, Simon Belanger, Daniel Bourgault, Julie Carriere, Charlotte Carrier-Belleau, Elliot Dreujou, Ladd Erik Johnson, S. Kim Juniper, Raphael Mabit, Christopher W. McKindsey, Lindsey Ogston, Manon M. M. Picard, Richard Saint-Louis, Emilie Saulnier-Talbot, Jean-Luc Shaw, Nadine Templeman, Thomas W. Therriault, Jean-Eric Tremblay, Philippe Archambault

Summary: Ports play a central role in society, but they also pose potential environmental risks and stressors. Port managers face challenges in mitigating these risks and impacts on ecosystems and human health. The development of comprehensive environmental monitoring approaches integrated into wider ecosystems can help achieve sustainable development.

ELEMENTA-SCIENCE OF THE ANTHROPOCENE (2022)

Article Remote Sensing

Empirical Remote Sensing Algorithms to Retrieve SPM and CDOM in Québec Coastal Waters

Raphael Mabit, Carlos A. S. Araujo, Rakesh Kumar Singh, Simon Belanger

Summary: This paper investigated the methods of estimating dissolved organic matter and suspended particulate matter in coastal waters using satellite remote sensing data, and developed regional algorithms for OLI and MSI sensors. The results showed that different algorithms were required for different water bodies, and the ACOLITE algorithm performed the best in CDOM estimation.

FRONTIERS IN REMOTE SENSING (2022)

Article Environmental Sciences

A machine learning approach for monitoring Brazilian optical water types using Sentinel-2 MSI

Edson Filisbino Freire da Silva, Evlyn Marcia Leao de Moraes Novo, Felipe de Lucia Lobo, Claudio Clemente Faria Barbosa, Carolline Tressmann Cairo, Mauricio Almeida Noernberg, Luiz Henrique da Silva Rotta

Summary: This study utilizes a machine learning method to monitor Brazilian OWTs using Sentinel-2 MSI, achieving a classification accuracy of 0.94 based on field radiometric data simulation. The novelty detection in satellite images distinguishes between known and new OWTs, providing an expected accuracy of 0.78 considering errors retrieved from field measurements.

REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT (2021)

暂无数据