Using the U‐net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images

Using the U‐net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images

Abstract Mapping forest types and tree species at regional scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. Here, we assess the potential of a U‐net convolutional network, a recent deep learning algorithm, to identify and segment (...

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Bibliographic Details
Main Authors: Fabien H. Wagner, Alber Sanchez, Yuliya Tarabalka, Rodolfo G. Lotte, Matheus P. Ferreira, Marcos P. M. Aidar, Emanuel Gloor, Oliver L. Phillips, Luiz E. O. C. Aragão
Format: Article
Language:English
Published: Wiley 2019-12-01
Series:Remote Sensing in Ecology and Conservation
Subjects:
Deep learning
Image segmentation
Keras
Rstudio
Tensorflow
Tree crown delineation
Online Access:https://doi.org/10.1002/rse2.111

Internet

https://doi.org/10.1002/rse2.111

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