Browsing by Author "Knudby, Anders"

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    Simple and effective monitoring of historic changes in nearshore environments using the free archive of Landsat imagery
    (Elsevier, 2009) Knudby, Anders; Newmanb, Candace; Shaghude, Yohanna W.; Muhando, Christopher A.
    The recently released archive of Landsat imagery can be used to detect historic changes in nearshore environments. We used a series of free Landsat images spanning the years from 1984 to 2009 to detect changes in the spatial extent of dominant substrate types, coral, algae, and seagrass, around Bawe and Chumbe islands in Zanzibar, and we compared the use of true-colour composites and supervised classifications. Results indicate temporal changes in the spatial extent of seagrass meadows are easily mapped with Landsat imagery, whereas temporal changes in algae cover and particularly coral cover pose greater challenges because of the similarities in spectral reflectance properties between the relevant substrate types. Supervised classification requires substantially more processing than the simple display of true-colour composites, but does not improve interpretation in our study. We suggest that historic Landsat imagery, obtained at no cost and processedminimally with free software, is the best available data source for studies of historic changes in the nearshore environments of East Africa. 2009 Elsevier B.V. All rights reserved
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    Simple and effective monitoring of historic changes in nearshore environments using the free archive of Landsat imagery
    (Elsevier, 2010) Knudby, Anders; Newman, Candace; Shaghude, Yohanna W.; Muhando, Christopher A.
    The recently released archive of Landsat imagery can be used to detect historic changes in nearshore environments. We used a series of free Landsat images spanning the years from 1984 to 2009 to detect changes in the spatial extent of dominant substrate types, coral, algae, and seagrass, around Bawe and Chumbe islands in Zanzibar, and we compared the use of true-colour composites and supervised classifications. Results indicate temporal changes in the spatial extent of seagrass meadows are easily mapped with Landsat imagery, whereas temporal changes in algae cover and particularly coral cover pose greater challenges because of the similarities in spectral reflectance properties between the relevant substrate types. Supervised classification requires substantially more processing than the simple display of true-colour composites, but does not improve interpretation in our study. We suggest that historic Landsat imagery, obtained at no cost and processedminimally with free software, is the best available data source for studies of historic changes in the nearshore environments of East Africa.