Unlock insights from hydrographic data with GeoAI

Abstract

Hydrographic offices are collecting hundreds of terabytes of data every day. This information not only comes from bathymetry data sensors, but also from weather stations, radar, ships, satellites, aerial and drone imagery, and other sensors. With all this data pouring in, hydrographic offices need to be able to automate time consuming processes and adopt modern technologies. One such technology is GeoAI, the intersection of spatial data and artificial intelligence. GeoAI can be considered an enabling technology, in that it allows you collect the data once and apply different algorithms to the data for it to be for multiple purposes. Data collected from multibeam echo sounders can be analyzed to update ENCs by finding new obstructions such as rocks and shipwrecks. Using that same point cloud, GeoAI can then be used to understand marine animal habitat by identifying underwater structures and seafloor patterns that lead to increased biodiversity. GeoAI can be used to aid in coastal resilience projects by analyzing aerial imagery from drones captured in multiple seasons and years for change detection, highlight the areas that need the most attention. Machine Learning, a part of the GeoAI portfolio, can additionally use that same imagery data set to run predictive analytics, highlighting areas that are susceptible to erosion, flooding, and landslides. Many of the same GeoAI algorithms can be used to help maximize investments in the blue economy by bringing location intelligence to the decision-making process. Models can predict the best locations to establish aquaculture, Marine Protected Areas, and offshore energy production. In addition to its applications in coastal resilience projects and maximizing investments in the blue economy, GeoAI offers a wide array of benefits in the domain of hydrospatial data management. The integration of GeoAI in hydrographic offices revolutionizes the way hydrographic data is processed and utilized. Traditionally, processing and interpreting vast amounts of hydrospatial data, including bathymetry, weather, radar, and imagery, required extensive human resources and time-consuming manual efforts. However, with GeoAI, these offices can automate complex tasks and streamline data analysis, significantly improving efficiency and accuracy.