Using remote sensing methods to identify valuable underwater habitats
Seagrasses are submerged plants found all over the world from brackish bays to salty continental shelves. Seagrasses create high-productive habitats and are a vital part of the marine ecosystems, providing shelter, nurseries, food, and habitats for other species. Seagrasses can be seen as indicators of environmental changes and ecosystem heath as they are sensitive to water quality.
Accurate and detailed spatial information of seagrasses would be important in assessments of threatened habitats, establishing MPAs and evaluating ecosystem state. However, spatially comprehensive species information is usually lacking and the knowledge of seagrass habitats around the world relies on scarce field observations and models based on inventory records. Because field work is expensive and time consuming, alternative ways of acquiring information of seagrass habitats are needed. Therefore, aerial and satellite images are useful as they are provided in different resolution, times, and prices depending on the purpose of use.
We tested how aerial and high-resolution satellite images could be utilized in finding seagrass habitats in two different environments; in the brackish Finnish coast and in the clear tropical waters of Zanzibar, Tanzania. We did supervised classification to identify seagrasses of pre-processed aerial and satellite images. For the satellite image of the coast of Zanzibar, we also calculated water column correction. Both ways of the method worked, as the seagrass areas were found, although in the Finnish coast poor water visibility hinders light penetration below 4 meter. In developing countries, where marine inventories are usually non-existent, our methodology of utilizing low-cost images for identifying valuable habitats is the only reasonable way of acquiring marine biodiversity data.
Meri Koskelainen, Elina Virtanen, Samuli Korpinen, and Markku Viitasalo, "Using remote sensing methods to identify valuable underwater habitats," Proc. SPIE 10422, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2017, 104220A (Presented at SPIE Remote Sensing: September 11, 2017; Published: 25 January 2018); https://doi.org/10.1117/12.2280753.5616450302001.
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