Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach
The deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), though algorithms typically have limited transferability in sp...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/13/1629 |
| _version_ | 1818974085076484096 |
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| author | Daniel Jensen Marc Simard Kyle Cavanaugh Yongwei Sheng Cédric G. Fichot Tamlin Pavelsky Robert Twilley |
| author_facet | Daniel Jensen Marc Simard Kyle Cavanaugh Yongwei Sheng Cédric G. Fichot Tamlin Pavelsky Robert Twilley |
| author_sort | Daniel Jensen |
| collection | DOAJ |
| description | The deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), though algorithms typically have limited transferability in space and time due to variability in water constituent compositions, mixtures, and inherent optical properties. This study used in situ spectral reflectances and their first derivatives to compare empirical algorithms for estimating TSS using hyperspectral and multispectral data. These algorithms were applied to imagery collected by NASA’s Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over coastal Louisiana, USA, and validated with a multiyear in situ dataset. The best performing models were then applied to independent spectroscopic data collected in the Peace−Athabasca Delta, Canada, and the San Francisco Bay−Delta Estuary, USA, to assess their robustness and transferability. A derivative-based partial least squares regression (PLSR) model applied to simulated AVIRIS-NG data showed the most accurate TSS retrievals (R<sup>2</sup> = 0.83) in these contrasting deltaic environments. These results highlight the potential for a more broadly applicable generalized algorithm employing imaging spectroscopy for estimating suspended solids. |
| first_indexed | 2024-12-20T15:34:27Z |
| format | Article |
| id | doaj.art-00035843befe4543a821683dd01efa48 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T15:34:27Z |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-00035843befe4543a821683dd01efa482022-12-21T19:35:28ZengMDPI AGRemote Sensing2072-42922019-07-011113162910.3390/rs11131629rs11131629Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral ApproachDaniel Jensen0Marc Simard1Kyle Cavanaugh2Yongwei Sheng3Cédric G. Fichot4Tamlin Pavelsky5Robert Twilley6Department of Geography, University of California at Los Angeles, Los Angeles, CA 90095, USAJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USADepartment of Geography, University of California at Los Angeles, Los Angeles, CA 90095, USADepartment of Geography, University of California at Los Angeles, Los Angeles, CA 90095, USADepartment of Earth and Environment, Boston University, Boston, MA 02215, USADepartment of Geological Sciences, University of North Carolina, Chapel Hill, NC 27599, USASchool of the Coast and Environment, Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA 70803, USAThe deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), though algorithms typically have limited transferability in space and time due to variability in water constituent compositions, mixtures, and inherent optical properties. This study used in situ spectral reflectances and their first derivatives to compare empirical algorithms for estimating TSS using hyperspectral and multispectral data. These algorithms were applied to imagery collected by NASA’s Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over coastal Louisiana, USA, and validated with a multiyear in situ dataset. The best performing models were then applied to independent spectroscopic data collected in the Peace−Athabasca Delta, Canada, and the San Francisco Bay−Delta Estuary, USA, to assess their robustness and transferability. A derivative-based partial least squares regression (PLSR) model applied to simulated AVIRIS-NG data showed the most accurate TSS retrievals (R<sup>2</sup> = 0.83) in these contrasting deltaic environments. These results highlight the potential for a more broadly applicable generalized algorithm employing imaging spectroscopy for estimating suspended solids.https://www.mdpi.com/2072-4292/11/13/1629Remote sensingimaging spectroscopyhyperspectralmultispectralAVIRIS-NGsedimenttotal suspended solids (TSS) |
| spellingShingle | Daniel Jensen Marc Simard Kyle Cavanaugh Yongwei Sheng Cédric G. Fichot Tamlin Pavelsky Robert Twilley Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach Remote Sensing Remote sensing imaging spectroscopy hyperspectral multispectral AVIRIS-NG sediment total suspended solids (TSS) |
| title | Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach |
| title_full | Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach |
| title_fullStr | Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach |
| title_full_unstemmed | Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach |
| title_short | Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach |
| title_sort | improving the transferability of suspended solid estimation in wetland and deltaic waters with an empirical hyperspectral approach |
| topic | Remote sensing imaging spectroscopy hyperspectral multispectral AVIRIS-NG sediment total suspended solids (TSS) |
| url | https://www.mdpi.com/2072-4292/11/13/1629 |
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