Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/113716
Title: Comparing the Capability of Sentinel-2 and Landsat 9 Imagery for Mapping Water and Sandbars in the River Bed of the Lower Tagus River (Portugal)
Authors: Gerardo, Romeu 
Lima, Isabel P. de 
Keywords: remote sensing; multispectral water indices; imagery classification; optimal threshold; river morphology
Issue Date: 2023
Publisher: MDPI
Project: The research presented here was partly funded through the Portuguese Fundação para a Ciência e a Tecnologia (FCT), involving project MEDWATERICE (PRIMA/0006/2018; with the support of PRIMA Programme), supported by national funds (PIDDAC); projects UIDB/04292/2020 and UIDP/04292/2020 granted to MARE–Marine and Environmental Research Center, and project LA/P/0069/2020 granted to the Associate Laboratory ARNET–Aquatic Research Network, supported by national funds. 
Serial title, monograph or event: Remote Sensing
Volume: 15
Issue: 7
Abstract: Mapping river beds to identify water and sandbars is a crucial task for understanding the morphology and hydrodynamics of rivers and their ecological conditions. The main difficulties of this task so far have been the limitations of conventional approaches, which are generally costly (e.g., equipment, time- and human resource-demanding) and have poor flexibility to deal with all river conditions. Currently, alternative approaches rely on remote sensing techniques, which offer innovative tools for mapping water bodies in a quick and cost-effective manner based on relevant spectral indices. This study aimed to compare the capability of using imagery from the Sentinel-2 and newly launched Landsat 9 satellite to achieve this goal. For a segment of the Lower Tagus River (Portugal) with conditions of very low river discharge, comparison of the Normalized Difference Water Index, Modified Normalized DifferenceWater Index, Augmented Normalized DifferenceWater Index, and Automated Water Extraction Index calculated from the imagery of the two satellites shows that the two satellites’ datasets and mapping were consistent and therefore could be used complementarily. However, the results highlighted the need to classify satellite imagery based on index-specific classification decision values, which is an important factor in the quality of the information extracted.
URI: https://hdl.handle.net/10316/113716
ISSN: 2072-4292
DOI: 10.3390/rs15071927
Rights: openAccess
Appears in Collections:I&D MARE - Artigos em Revistas Internacionais
FCTUC Eng.Civil - Artigos em Revistas Internacionais

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