A Machine-Learning Approach to Intertidal Mudflat Mapping Combining Multispectral Reflectance and Geomorphology from UAV-Based Monitoring

A Machine-Learning Approach to Intertidal Mudflat Mapping Combining Multispectral Reflectance and Geomorphology from UAV-Based Monitoring

Remote sensing is a relevant method to map inaccessible areas, such as intertidal mudflats. However, image classification is challenging due to spectral similarity between microphytobenthos and oyster reefs. Because these elements are strongly related to local geomorphic features, including biogenic...

Full description

Bibliographic Details
Main Authors: Guillaume Brunier, Simon Oiry, Nicolas Lachaussée, Laurent Barillé, Vincent Le Fouest, Vona Méléder
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Remote Sensing
Subjects:
UAV
multispectral
temperate mudflat
geomorphic mapping
random forest classification
microphytobenthos
Online Access:https://www.mdpi.com/2072-4292/14/22/5857

Internet

https://www.mdpi.com/2072-4292/14/22/5857

Similar Items