Volume XLII-4/W16
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 587–593, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-587-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 587–593, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-587-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Oct 2019

01 Oct 2019

SATELLITE-BASED MAPPING OF ABOVE-GROUND BLUE CARBON STORAGE IN SEAGRASS HABITAT WITHIN THE SHALLOW COASTAL WATER

D. A. Sani1,2,3 and M. Hashim1,2 D. A. Sani and M. Hashim
  • 1Geoscience & Digital Earth Centre (INSTEG), Research Institute for Sustainable Environment (RISE), Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  • 2Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  • 3Department of Geography, Yusuf Maitama Sule University, Kano, Nigeria

Keywords: Blue Carbon, Seagrass, STAGC, Landsat 7 ETM+, BRI, DII

Abstract. These Mapping and estimation of seagrass total above-ground carbon (STAGC) using satellite-based techniques are required to fast-track the achievement of the 2020 agenda on Sustainable Development Goals (SDG) 14th. This attainment is possible as seagrass habitats provide a critical coastal ecosystem for storing blue carbon stock, sediment accumulation, fisheries production and stabilisation of coastal environment. However, seagrasses are generally declining across the globe due to anthropogenic disturbance, resulting in a prolonged growth rate of seagrasses that varies according to the species compositions. Therefore, this study aims at mapping and estimation of seagrass total above-ground carbon (STAGC) using Landsat ETM+ in the coastline of Penang. These satellite images were calibrated with Bottom Reflected Index (BRI) and Depth Invariant Index (DII) to compare the estimate of the STAGC for more accuracy. The leaving radiances of the seagrass were correlated with the corresponding in-situ measurements to predict seagrass carbon. This established relationship with BRI image shown a healthy correlation with STAGB (R2 = 0.992, p ≤ 0.001). Whereas the STAGB versus DII relationship has less accuracy (R2 = 0.955, p ≤ 0.01), adjusted R2 = 0.980 and 0.978 were recorded for both BRI and DII STAGC estimate using the logistic model. Therefore, careful management of blue carbon stock is essential, as this study shall contribute to achieving targets 14.2 and 14.5 of SDG 14th by the United Nations.