Explainable identification and mapping of trees using UAV RGB image and deep learning
Abstract The identification and mapping of trees via remotely sensed data for application in forest management is an active area of research. Previously proposed methods using airborne and hyperspectral sensors can identify tree species with high accuracy but are costly and are thus unsuitable for s...
Main Authors: | Masanori Onishi, Takeshi Ise |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-01-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-020-79653-9 |
Similar Items
-
Mapping Tobacco Fields Using UAV RGB Images
by: Xiufang Zhu, et al.
Published: (2019-04-01) -
Deep Learning in Forestry Using UAV-Acquired RGB Data: A Practical Review
by: Yago Diez, et al.
Published: (2021-07-01) -
Deep Learning Applied to Phenotyping of Biomass in Forages with UAV-Based RGB Imagery
by: Wellington Castro, et al.
Published: (2020-08-01) -
Using Deep Learning and Low-Cost RGB and Thermal Cameras to Detect Pedestrians in Aerial Images Captured by Multirotor UAV
by: Diulhio Candido de Oliveira, et al.
Published: (2018-07-01) -
UAV IMAGING AT RGB FOR CROP CONDITION MONITORING
by: T. Choroś, et al.
Published: (2020-08-01)