ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2021
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 15–22, 2021
https://doi.org/10.5194/isprs-annals-V-3-2021-15-2021
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 15–22, 2021
https://doi.org/10.5194/isprs-annals-V-3-2021-15-2021

  17 Jun 2021

17 Jun 2021

USE OF LANDSAT-8 OLI IMAGERY AND LOCAL INDIGENOUS KNOWLEDGE FOR EELGRASS MAPPING IN EEYOU ISTCHEE

K. Clyne1, B. Leblon1, A. LaRocque1, M. Costa2, M. Leblanc3, E. Rabbitskin4, and M. Dunn4 K. Clyne et al.
  • 1University of New Brunswick, Fredericton (NB), Canada
  • 2University of Victoria, Victoria (BC), Canada
  • 3McGill University, Ste-Anne-de-Bellevue (QC), Canada
  • 4Niskamoon Corporation, Nemaska (QC), Canada

Keywords: Eelgrass mapping, James Bay, Landsat-8, Random Forests, local indigenous knowledge, Cree territory

Abstract. The eastern coastline of James Bay (Eeyou Istchee) is known to be home to beds of subarctic eelgrass (Zostera marina L.). These eelgrass beds provide valuable habitat and food source for coastal and marine animals and contribute valuable ecosystem services such as stabilization of the shoreline all along the coast. Despite reports from Cree communities that eelgrass bed health has declined, limited research has been performed to assess and map the spatial distribution of eelgrass within the bay. This study aims to address that issue by evaluating the capability of Landsat-8 Operational Land Imager (OLI) imagery to establish a baseline map of eelgrass distribution in 2019 in the relatively turbid waters of Eeyou Istchee. Three images acquired in September 2019 were merged and classified using Random Forests into the following classes: Eelgrass, Turbid Water, Highly Turbid Water, and Optically Deep Water. The resulting classified image was validated against 108 ground truth data that were obtained from both the eelgrass health and Hydro-Quebec research team. The resulting overall accuracy was 78.7%, indicating the potential of the Random Forests classifier to estimate baseline eelgrass coverage in James Bay using Landsat-8 imagery. This project is part of a Cree driven project, the Coastal Habitat Comprehensive Research Program (CHCRP). The CHCRP aims to combine Cree's traditional knowledge with Western science to better understand environmental changes in the coastal ecosystems and ecosystem services of eastern James Bay. The study is funded by a MITACS grant sponsored by Niskamoon Corporation, an indigenous non-profit organization.