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Photo-library method for mapping seagrass biomass
Authors:Tiit Kutser  Ele Vahtme  Chris M Roelfsema  Liisa Metsamaa
Institution:aEstonian Marine Institute, University of Tartu, Mäealuse 10a, 12618 Tallinn, Estonia;bCentre for Remote Sensing and Spatial Information Science, School of Geography, Planning and Architecture, University of Queensland, Brisbane, Qld 4072, Australia
Abstract:The creation of seagrass biomass maps by diving/snorkelling is time-consuming and expensive. This paper presents a method for estimating seagrass dry weight using a photo-library of classes of differing seagrass biomass. Field data were collected at seagrass beds in Ngederrak Reef, Palau, in 2006. Photos of 25 × 25 cm quadrats were taken prior to the collection the above-ground biomass for determination of biomass dry weight. Fifteen classes of seagrass biomass and substrate type were identified. The dry weight for each class of seagrass was measured in laboratory. A photo-library was created for biomass classification where each in situ quadrat photo is accompanied with seagrass dry weight of the sample and a photo of the sorted sample taken in laboratory. The photo-library of quadrats was then used to estimate seagrass biomass on photos gathered along 100 m long transects at 2 m intervals. This procedure was conducted by three different observers. The seagrass dry weight estimates were consistent between interpreters even if one of the interpreters had no experience in seagrass research. This approach allows quick collection of seagrass dry weight data over large areas. The method can be used for creating seagrass biomass maps by snorkelling/diving and/or for calibrating and validating biomass maps created by remote sensing.
Keywords:seagrass  biomass  remote sensing
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