Abstract
There is an ongoing effort in using imagery from remote sensing platforms to obtain information about the sea depth; this allows to monitor the dynamics of coastal erosion without the need for costly and repeated local surveys. We worked on a new implementation of the Jupp method to extract depth information from satellite images. Our software is based on previous implementations of the algorithm in the IDL language, but we made our current implementation more modular in order to make possible experimentations with different approaches. We used this implementation on a series of six images (three from the Landsat TM sensor and three from the Landsat OLI sensor) in order to improve the available tools. We established an iterative workflow for working on the Landat-8 images widely exposed in this paper.
Highlights
The availability of high resolution satellite images makes remote sensing an attractive approach to the problem of determining sea depth in coastal areas
For the purposes of our research, we built our own implementation of the Jupp algorithm in the IDL language, which allows us to take advantage of the ENVI platform by Exelis-VIS performing the preparation of input data, visualization and comparison of the results
In this work we started from previous research about the Jupp method and its application to produce a new implementation in the IDL language
Summary
The availability of high resolution satellite images makes remote sensing an attractive approach to the problem of determining sea depth in coastal areas. This is especially promising in the field of coastal erosion monitoring and management that would otherwise require costly and extensive bathymetric surveys. In order to exploit this resource, many recent satellite platforms are equipped with a specific “coastal” sensor, which is sensitive to a slightly higher wavelength than the usual blue band. Such wavelengths have a better water penetration, allowing to extend the bathymetry estimate to grater depths. After a brief historical review, the algorithm, the software and the results on Landsat images are presented in the following paragraphs
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
