Using Sentinel-2 Images to Estimate Topography, Tidal-Stage Lags and Exposure Periods over Large Intertidal Areas

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 2; p. 320
• Main Authors: Granadeiro, José P., Belo, João, Henriques, Mohamed, Catalão, João, Catry, Teresa
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-01-2021
• Subjects: Algorithms; Archipelagoes; bathymetry; Biodiversity; Coastal ecology; Coasts; Correlation analysis; DEM; Digital Elevation Models; Ecosystem services; Ecosystems; Estimates; Estimation; Exposure; exposure period maps; intertidal mapping; Intertidal zone; Parameter estimation; Pixels; Regions; Remote sensing; Sediments; Sentinel-2; Software; tide-stage lags estimation; Topography; Wildlife conservation; Guinea Bissau
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs13020320

Intertidal areas provide key ecosystem services but are declining worldwide. Digital elevation models (DEMs) are important tools to monitor the evolution of such areas. In this study, we aim at (i) estimating the intertidal topography based on an established pixel-wise algorithm, from Sentinel-2 MultiSpectral Instrument scenes, (ii) implementing a set of procedures to improve the quality of such estimation, and (iii) estimating the exposure period of the intertidal area of the Bijagós Archipelago, Guinea-Bissau. We first propose a four-parameter logistic regression to estimate intertidal topography. Afterwards, we develop a novel method to estimate tide-stage lags in the area covered by a Sentinel-2 scene to correct for geographical bias in topographic estimation resulting from differences in water height within each image. Our method searches for the minimum differences in height estimates obtained from rising and ebbing tides separately, enabling the estimation of cotidal lines. Tidal-stage differences estimated closely matched those published by official authorities. We re-estimated pixel heights from which we produced a model of intertidal exposure period. We obtained a high correlation between predicted and in-situ measurements of exposure period. We highlight the importance of remote sensing to deliver large-scale intertidal DEM and tide-stage data, with relevance for coastal safety, ecology and biodiversity conservation.