Remote sensing of eelgrass using OBIA and Sentinel-2 imagery

Session

Workshop om anvendelse af satellitdata

Abstract

This study was prepared for my master thesis in geoinformatics at Aalborg University.

Eelgrass is an ecologically significant marine plant and the coverage of eelgrass is used to assess waterway health under EU regulations. Collection of eelgrass field data for research and sampling is based on existing knowledge, modelling and estimation of where eelgrass populations could be located. However, a more targeted approach could be used to improve results.

This study proposes such an approach to identify potential areas of eelgrass coverage using satellite imagery. Using eCognition software, remote sensing of eelgrass in Roskilde Fjord is undertaken using object based image analysis (OBIA) and Sentinel-2 imagery to a depth of 4 m.

Various machine learning algorithms and OBIA are showcased, as well as the challenges distinguishing eelgrass from other types of submerged aquatic vegetation (SAV).

Målgruppe

Remote sensing specialists, marine ecologists, and GIS people.

Yderligere uddybning af abstract