Species level mapping of a seagrass bed using an unmanned aerial vehicle and deep learning technique.

ABSTRACT:

Background

Seagrass beds are essential habitats in coastal ecosystems, providing valuable ecosystem services, but are threatened by various climate change and human activities. Seagrass monitoring by remote sensing have been conducted over past decades using satellite and aerial images, which have low resolution to analyze changes in the composition of different seagrass species in the meadows. Recently, unmanned aerial vehicles (UAVs) have allowed us to obtain much higher resolution images, which is promising in observing fine-scale changes in seagrass species composition. Furthermore, image processing techniques based on deep learning can be applied to the discrimination of seagrass species that were difficult based only on color variation. In this study, we conducted mapping of

SUBMITTER: Tahara S 

PROVIDER: S-EPMC9583862 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature