Deriving Water Quality Parameters Using Sentinel-2 Imagery: A Case Study in the Sado Estuary, Portugal

被引:54
|
作者
Sent, Giulia [1 ]
Biguino, Beatriz [1 ,2 ]
Favareto, Luciane [1 ]
Cruz, Joana [1 ]
Sa, Carolina [1 ,5 ]
Dogliotti, Ana Ines [3 ]
Palma, Carla [2 ]
Brotas, Vanda [1 ,4 ]
Brito, Ana C. [1 ,4 ]
机构
[1] Univ Lisbon, MARE Marine & Environm Sci Ctr, Fac Ciencias, P-1749016 Lisbon, Portugal
[2] Inst Hidrog, Rua Trinas 49, P-1249093 Lisbon, Portugal
[3] Univ Buenos Aires, Inst Astron & Fis Espacio IAFE, CONICET, Pabellon IAFE,Ciudad Univ,C1428EGA, Buenos Aires, DF, Argentina
[4] Univ Lisbon, Dept Biol Vegetal, Fac Ciencias, P-1749016 Lisbon, Portugal
[5] Portugal Space, Estr Laranjeiras, P-1500423 Lisbon, Portugal
基金
欧盟地平线“2020”;
关键词
monitoring; remote sensing; WFD; transitional waters; water policy; suspended particulate matter; chlorophyll-a; CDOM; turbidity; ATMOSPHERIC CORRECTION ALGORITHMS; DISSOLVED ORGANIC-MATTER; COASTAL WATERS; CHLOROPHYLL-A; INLAND; MODEL; PHYTOPLANKTON; PERFORMANCE; RETRIEVAL; CDOM;
D O I
10.3390/rs13051043
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Monitoring water quality parameters and their ecological effects in transitional waters is usually performed through in situ sampling programs. These are expensive and time-consuming, and often do not represent the total area of interest. Remote sensing techniques offer enormous advantages by providing cost-effective systematic observations of a large water system. This study evaluates the potential of water quality monitoring using Sentinel-2 observations for the period 2018-2020 for the Sado estuary (Portugal), through an algorithm intercomparison exercise and time-series analysis of different water quality parameters (i.e., colored dissolved organic matter (CDOM), chlorophyll-a (Chl-a), suspended particulate matter (SPM), and turbidity). Results suggest that Sentinel-2 is useful for monitoring these parameters in a highly dynamic system, however, with challenges in retrieving accurate data for some of the variables, such as Chl-a. Spatio-temporal variability results were consistent with historical data, presenting the highest values of CDOM, Chl-a, SPM and turbidity during Spring and Summer. This work is the first study providing annual and seasonal coverage with high spatial resolution (10 m) for the Sado estuary, being a key contribution for the definition of effective monitoring programs. Moreover, the potential of remote sensing methodologies for continuous water quality monitoring in transitional systems under the scope of the European Water Framework Directive is briefly discussed.
引用
收藏
页码:1 / 30
页数:27
相关论文
共 50 条
  • [1] First Experiences in Mapping Lake Water Quality Parameters with Sentinel-2 MSI Imagery
    Toming, Kaire
    Kutser, Tiit
    Laas, Alo
    Sepp, Margot
    Paavel, Birgot
    Noges, Tiina
    REMOTE SENSING, 2016, 8 (08):
  • [2] Tidal variability of water quality parameters in a mesotidal estuary (Sado Estuary, Portugal)
    Nascimento, Angela
    Biguino, Beatriz
    Borges, Carlos
    Cereja, Rui
    Cruz, Joana P. C.
    Sousa, Fatima
    Dias, Joaquim
    Brotas, Vanda
    Palma, Carla
    Brito, Ana C.
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [3] Remote sensing of tropical riverine water quality using sentinel-2 MSI and field observations
    Virdis, Salvatore G. P.
    Xue, Wenchao
    Winijkul, Ekbordin
    Nitivattananon, Vilas
    Punpukdee, Pongsakon
    ECOLOGICAL INDICATORS, 2022, 144
  • [4] Validation of Sentinel-2 (MSI) and Sentinel-3 (OLCI) Water Quality Products in Turbid Estuaries Using Fixed Monitoring Stations
    Salama, Mhd. Suhyb
    Spaias, Lazaros
    Poser, Kathrin
    Peters, Steef
    Laanen, Marnix
    FRONTIERS IN REMOTE SENSING, 2022, 2
  • [5] Multitemporal water quality study in Sitjar (Castello, Spain) reservoir using Sentinel-2 images
    Radin, C.
    Soria-Perpinya, X.
    Delegido, J.
    REVISTA DE TELEDETECCION, 2020, (56): : 117 - 130
  • [6] Monitoring Water Quality Parameters Using Sentinel-2 Data: A Case Study in the Weihe River Basin (China)
    Liu, Tieming
    Guo, Zhao
    Li, Xiaoping
    Xiao, Teng
    Liu, Jiaxin
    Zhang, Yuanzhi
    SUSTAINABILITY, 2024, 16 (16)
  • [7] Space-time monitoring of water quality in an eutrophic reservoir using SENTINEL-2 data-A case study of San Roque, Argentina
    German, Alba
    Shimoni, Michal
    Beltramone, Giuliana
    Rodriguez, Maria Ines
    Muchiut, Jonathan
    Bonansea, Matias
    Scavuzzo, C. Marcelo
    Ferral, Anabella
    REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2021, 24
  • [8] Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms
    Tian, Shang
    Guo, Hongwei
    Xu, Wang
    Zhu, Xiaotong
    Wang, Bo
    Zeng, Qinghuai
    Mai, Youquan
    Huang, Jinhui Jeanne
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (07) : 18617 - 18630
  • [9] Monitoring Coastal Water Body Health with Sentinel-2 MSI Imagery
    Lock, Marcelle
    Saintilan, Neil
    van Duren, Iris
    Skidmore, Andrew
    REMOTE SENSING, 2023, 15 (07)
  • [10] Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery
    Perez-Gonzalez, Rebeca
    Soria-Perpinya, Xavier
    Soria, Juan Miguel
    Delegido, Jesus
    Urrego, Patricia
    Sendra, Maria D.
    Ruiz-Verdu, Antonio
    Vicente, Eduardo
    Moreno, Jose
    WATER, 2021, 13 (20)