|Appears in Collections:||Biological and Environmental Sciences Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Mapping intertidal estuarine sediment grain size distributions through airborne remote sensing|
|Authors:||Rainey, Michael P|
Bryant, Robert G
airborne remote sensing
linear mixture modelling
|Citation:||Rainey MP, Tyler A, Gilvear D, Bryant RG & McDonald P (2003) Mapping intertidal estuarine sediment grain size distributions through airborne remote sensing, Remote Sensing of Environment, 86 (4), pp. 480-490.|
|Abstract:||The intertidal environments of estuaries represent critical exchange environments of sediment and sediment bound contaminants. Ecological and sedimentological related investigations of these environments require monitoring methods that provide rapid spatially representative data on sediment grain size distribution. Remote sensing has the potential to provide synoptic information of intertidal environments. Previous in situ and laboratory-based reflectance investigations have demonstrated that for effective quantification of sediment grain size distributions, remote sensing platforms must include measurements within the short-wave infrared (SWIR). In addition, the timing of image acquisition, in relation to tidal cycles and sediment moisture content, is critical in optimising the spectral differences between the coarser sand and finer ‘mud' fraction of sediments. Daedalus 1268 Airborne Thematic Mapper (ATM) has been identified as an appropriate platform and sensor for providing accurate synoptic maps of estuarine sediment distributions. This paper presents the results from the application of ATM 1.75 m resolution data to the mapping of surface sediment grain-size distributions across intertidal areas of Ribble Estuary, Lancashire, UK. ATM imagery was acquired after the intertidal area was exposed to strong summer drying conditions. Pre-processing and linear unmixing of the imagery collected of the intertidal zone following a period of drying allowed accurate sub-pixel determinations (1.75 m resolution) of sediment clay (r2=0.79) but less accurate for sand (r2=0.60). The results also demonstrate deterioration in the image calibration with increasing sediment moisture content and microphytobenthos cover. However, recombining the subpixel end member abundances through multivariate regression analysis improved the image calibration significantly for both sediment clay and sand content (r2 is greater than 0.8) for imagery collected in both dryer and wetter conditions. These results demonstrate that ATM data, or similar, can be used to gain quantitative information on intertidal sediment distributions and such data has application to a wide variety of estuarine researc|
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|Affiliation:||University of Stirling|
Biological and Environmental Sciences
Biological and Environmental Sciences
University of Stirling
Westlakes Scientific Consulting Ltd
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