Satellite-Derived Bathymetry for Improving Canadian Hydrographic Service Charts

• Published in: ISPRS International Journal of Geo-Information
• Main Authors: René Chénier, Marc-André Faucher, Ryan Ahola
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2018
• Subjects: Canadian Hydrographic Service; empirical approach; high resolution; multispectral; nautical charts; remote sensing; Satellite Derived Bathymetry; Geography (General); G1-922; Arctic
• Online Access: https://doi.org/10.3390/ijgi7080306; https://doaj.org/article/61e81107275e4f97bfcceee4c5d6f684

Approximately 1000 Canadian Hydrographic Service (CHS) charts cover Canada’s oceans and navigable waters. Many charts use information collected with techniques that predate the more advanced technologies available to Hydrographic Offices (HOs) today. Furthermore, gaps in survey data, particularly in the Canadian Arctic where only 6% of waters are surveyed to modern standards, are also problematic. Through a Canadian Space Agency (CSA) Government Related Initiatives Program (GRIP) project, CHS is exploring remote sensing techniques to assist with the improvement of Canadian navigational charts. Projects exploring optical/Synthetic Aperture Radar (SAR) shoreline extraction and change detection, as well as optical Satellite-Derived Bathymetry (SDB), are currently underway. This paper focuses on SDB extracted from high-resolution optical imagery, highlighting current results as well as the challenges and opportunities CHS will encounter when implementing SDB within its operational chart production process. SDB is of particular interest to CHS due to its ability to supplement depths derived from traditional hydrographic surveys. This is of great importance in shallow and/or remote Canadian waters where achieving wide-area depth coverage through traditional surveys is costly, time-consuming and a safety risk to survey operators. With an accuracy of around 1 m, SDB could be used by CHS to fill gaps in survey data and to provide valuable information in dynamic areas.