Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery
Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was pe...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-08-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/16/3057 |
| _version_ | 1797522240943685632 |
|---|---|
| author | Aline de M. Valerio Milton Kampel Vincent Vantrepotte Nicholas D. Ward Jeffrey E. Richey |
| author_facet | Aline de M. Valerio Milton Kampel Vincent Vantrepotte Nicholas D. Ward Jeffrey E. Richey |
| author_sort | Aline de M. Valerio |
| collection | DOAJ |
| description | Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The <i>k</i>-means classification was applied to the in situ normalized reflectance spectra (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>r</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula>), allowing the identification of four OWTs. An optical index method was also applied to the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>r</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula> defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (<i>a</i><sub>CDOM</sub>) and particulate matter (<i>a</i><sub>p</sub>), chlorophyll-<i>a</i> and suspended particulate matter (SPM) concentrations, and <i>a</i><sub>CDOM</sub>/<i>a</i><sub>p</sub> ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of <i>a</i><sub>p</sub> to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region. |
| first_indexed | 2024-03-10T08:26:36Z |
| format | Article |
| id | doaj.art-a41cbdff95104b2b9eceb6b5f59bb127 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T08:26:36Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-a41cbdff95104b2b9eceb6b5f59bb1272023-11-22T09:31:09ZengMDPI AGRemote Sensing2072-42922021-08-011316305710.3390/rs13163057Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument ImageryAline de M. Valerio0Milton Kampel1Vincent Vantrepotte2Nicholas D. Ward3Jeffrey E. Richey4Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São José dos Campos 12227-010, SP, BrazilEarth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São José dos Campos 12227-010, SP, BrazilCentre National de la Recherche Scientifique (CNRS), Université Littoral Côte d’Opale, UMR 8187, Laboratoire d’Océanologie et de Géosciences (LOG), 59000 Lille, FranceMarine and Coastal Research Laboratory, Pacific Northwest National Laboratory (PNNL), Sequim, WA 99354, USASchool of Oceanography, University of Washington (UW), Seattle, WA 98195, USAOptical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The <i>k</i>-means classification was applied to the in situ normalized reflectance spectra (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>r</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula>), allowing the identification of four OWTs. An optical index method was also applied to the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>r</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></mrow></semantics></math></inline-formula> defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (<i>a</i><sub>CDOM</sub>) and particulate matter (<i>a</i><sub>p</sub>), chlorophyll-<i>a</i> and suspended particulate matter (SPM) concentrations, and <i>a</i><sub>CDOM</sub>/<i>a</i><sub>p</sub> ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of <i>a</i><sub>p</sub> to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region.https://www.mdpi.com/2072-4292/13/16/3057water colorremote sensing reflectancebio-optical productsoptically significant constituentsAmazon River |
| spellingShingle | Aline de M. Valerio Milton Kampel Vincent Vantrepotte Nicholas D. Ward Jeffrey E. Richey Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery Remote Sensing water color remote sensing reflectance bio-optical products optically significant constituents Amazon River |
| title | Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery |
| title_full | Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery |
| title_fullStr | Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery |
| title_full_unstemmed | Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery |
| title_short | Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery |
| title_sort | optical classification of lower amazon waters based on in situ data and sentinel 3 ocean and land color instrument imagery |
| topic | water color remote sensing reflectance bio-optical products optically significant constituents Amazon River |
| url | https://www.mdpi.com/2072-4292/13/16/3057 |
| work_keys_str_mv | AT alinedemvalerio opticalclassificationofloweramazonwatersbasedoninsitudataandsentinel3oceanandlandcolorinstrumentimagery AT miltonkampel opticalclassificationofloweramazonwatersbasedoninsitudataandsentinel3oceanandlandcolorinstrumentimagery AT vincentvantrepotte opticalclassificationofloweramazonwatersbasedoninsitudataandsentinel3oceanandlandcolorinstrumentimagery AT nicholasdward opticalclassificationofloweramazonwatersbasedoninsitudataandsentinel3oceanandlandcolorinstrumentimagery AT jeffreyerichey opticalclassificationofloweramazonwatersbasedoninsitudataandsentinel3oceanandlandcolorinstrumentimagery |