Optical Satellite Remote Sensing of the Coastal Zone Environment — An Overview

Abstract

Optical remote-sensing data are a powerful source of information for monitoring the coastal environment. Due to the high complexity of coastal environments, where different natural and anthropogenic phenomenon interact, the selection of the most appropriate sensor s is related to the applications required, and the different types of resolutions available spatial, spectral, radiometric, and temporal need to be considered. The development of specific techniques and tools based on the processing of optical satellite images makes possible the production of information useful for coastal environment management, without any destructive impacts. This chapter will highlight different subjects related to coastal environments shoreline change detection, ocean color, water quality, river plumes, coral reef, alga bloom, bathymetry, wetland mapping, and coastal hazards/vulnerability. The main objective of this chapter is not an exhaustive description of the image processing methods/algorithms employed in coastal environmental studies, but focus in the range of applications available. Several limitations were identified. The major challenge still is to have remote-sensing techniques adopted as a routine tool in assessment of change in the coastal zone. Continuing research is required into the techniques employed for assessing change in the coastal environment.

Using Optical Satellite and Aerial Imagery for Automatic Coastline Mapping

“…Potential data sources for coastline investigation include historical photographs, coastal maps and charts, aerial photography, beach surveys, in situ geographic positioning system shorelines, and a range of digital elevation or image data derived from remote sensing platforms (Boak & Turner, 2005;Holman & Haller, 2013;Harley et al, 2019). High and very high resolution satellite images and the related feature extraction techniques have proven to be particularly suitable for these applications (Teodoro, 2016). Further benefits are identified in rapid and more frequent data acquisition, faster and more automated processing and a greater sampling intensity, such as in the case of Sentinel-2 images.…”

An Approach Based on Landsat Images for Shoreline Monitoring to Support Integrated Coastal Management—A Case Study, Ezbet Elborg, Nile Delta, Egypt

“…Then, classification is performed using both segmented images as well as NDVI (Normalized Difference Vegetation Index) map to discriminate accurately between the water and no water for extraction of coastlines. Numerous studies for extracting shoreline via remote satellite images have been discussed by References [20][21][22][23][24][25]. Also, mapping shorelines was carried out using supervised approaches such as the machine learning techniques.…”

The Estimation and Evaluation of Shoreline Locations, Shoreline-Change Rates, and Coastal Volume Changes Derived from Landsat Images

“…Many previous studies have investigated the potential of optical satellite images for coastal monitoring (Blodget, Taylor, and Roark, 1991;Chen and Chang, 2009;Dinesh Kumar et al, 2007;Ekercin, 2007;Elena, 2008;Foody, Muslim, and Atkinson 2003;Gutierres et al, 2016;Kingston, 2003;Kuleli et al, 2011;Liu and Jezek, 2004;Mason, Davenport, and Flather, 1997;Plant et al, 2007;Teodoro, 2016;Teodoro et al, 2018;Wang, Zhang, and Ma, 2010;White and El-Asmar, 1999). However, few of these studies have fully explored the accuracy of the derived shorelines through comparison with simultaneous and independent in situ observations because of limitations in the availability of satellite images and in situ data.…”