• DocumentCode
    68700
  • Title

    Improved Understanding of Suspended Sediment Transport Process Using Multi-Temporal Landsat Data: A Case Study From the Old Woman Creek Estuary (Ohio)

  • Author

    In-Young Yeo ; Lang, Michael ; Vermote, Eric

  • Author_Institution
    Dept. of Geogr. Sci., Univ. of Maryland, College Park, MD, USA
  • Volume
    7
  • Issue
    2
  • fYear
    2014
  • fDate
    Feb. 2014
  • Firstpage
    636
  • Lastpage
    647
  • Abstract
    We used historical water quality data, continuous in situ water quality monitoring data, and multi-temporal Landsat-7 ETM+ imagery for the period of September 1999-April 2003 to study the distribution of total suspended sediments (TSS) in Old Woman Creek (OWC), a freshwater coastal wetland adjacent to Lake Erie. A multiple linear regression model was developed to describe the relationship between turbidity and atmospherically corrected reflectance from Landsat-7 ETM+ bands 2 and 4 (R2 = 0.65). Turbidity was then converted to total suspended sediments (TSS), based on in situ historical data. Mapped spatial patterns of TSS provided useful information on key physical drivers affecting the transport process of suspended sediment. This study demonstrates the potential and limitations of using medium- spatial scale multispectral data, such as Landsat, to understand important factors that control suspended sediment transport processes within an estuary.
  • Keywords
    remote sensing; sedimentation; sediments; water quality; AD 1999 09 to 2003 04; Lake Erie; Ohio; Old Woman Creek Estuary; freshwater coastal wetland; historical water quality data; multiple linear regression model; multitemporal Landsat data; multitemporal Landsat-7 ETM+ imagery; suspended sediment transport process; total suspended sediments; water quality monitoring data; Earth; Lakes; Monitoring; Remote sensing; Satellites; Sediments; Vegetation mapping; Landsat time-series images; remote sensing; suspended sediment; turbidity; wetland;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1939-1404
  • Type

    jour

  • DOI
    10.1109/JSTARS.2013.2265191
  • Filename
    6574245