Quantification of floating macroalgae blooms using the Scaled Algae Index
MetadataShow full item record
Copyright ©2012. American Geophysical Union.
Quantifying the spatial coverage of floating macroalgae from satellite imagery, using methods such as the normalized difference vegetation index (NDVI) and the floating algae index (FAI), requires the use of a scene-wide threshold to isolate and then compute the number of floating macroalgae pixels. The problem faced is the sensitivity of the NDVI and, to a lesser extent, the FAI to radiance contributions from atmospheric aerosols and turbid water. Both these factors can vary significantly across a satellites' field-of-view generating irregular apparent reflectance of ocean and floating macroalgae pixels across an NDVI/FAI scene, leading to inaccuracies in spatial coverage estimates. We present a simple image processing algorithm, termed the scaled algae index (SAI) that removes any variability present in ocean and floating macroalgae pixels in NDVI or FAI imagery. The SAI does this by subtracting a given pixel's index by that of a local ocean pixel, effectively scaling ocean pixels to values near zero, and macroalgae pixels to positive values. The SAI algorithm has been tested on NDVI and FAI scenes of the 2008/2009 floating macroalgae blooms that occurred in the Yellow Sea, China. These SAI images show a major reduction in variability with scene-wide histograms being unimodal. Histogram analysis also indicates that sufficient contrast exists between ocean and floating macroalgae pixels to enable segmentation by a scene-wide threshold. A semiautomated threshold determination procedure is also presented, which together with the SAI algorithm can be used to compute accurate estimates of the spatial coverage of floating macroalgae.
Showing items related by title, author, creator and subject.
Effect of cover management factor in quantification of soil loss: case study of Sungai Akah subwatershed, Baram River basin Sarawak, MalaysiaHamza, Vijith; Seling, L.; Dodge-Wan, Dominique (2017)© 2017 Informa UK Limited, trading as Taylor & Francis Group The present study evaluates the effectiveness and suitability of cover management factors (C factor) generated through different techniques like land use/land ...
Fractals and fuzzy sets for modelling the heterogenity and spatial complexity of urban landscapes using multiscale remote sensing dataIslam, Zahurul (2004)This research presents models for the analysis of textural and contextual information content of multiscale remote sensing to select an appropriate scale for the correct interpretation and mapping of heterogeneous urban ...
Tin, H.; O'Leary, Mick; Fotedar, Ravi; Garcia, R. (2016)© 2015 MTS.Marine submerged aquatic vegetation (SAV) plays a vital role as habitats, nursery and feeding grounds for a wide range of marine aquatic and terrestrial life. Recently, remote sensing techniques have been ...