Unmanned aerial vehicle-based structure from motion biomass inventory estimates-Reference-Cited by-同舟云学术

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Unmanned aerial vehicle-based structure from motion biomass inventory estimates

Published:2017-05-31 Issue:2 Volume:11 Page:026026
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:en
Short-container-title:J. Appl. Remote Sens

Author:

Bedell Emily¹,Leslie Monique²,Fankhauser Katie³,Burnett Jonathan⁴,Wing Michael G.⁴,Thomas Evan A.¹

Affiliation:

1. Portland State University, Department of Mechanical and Materials Engineering, Portland, Oregon, United States

2. The Freshwater Trust, Portland, Oregon, United States

3. Oregon Health and Science University, Department of Public Health and Preventive Medicine, Portland, Oregon, United States

4. Oregon State University, Department of Forest Engineering, Resources, and Management, Corvallis, Oregon, United States

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference33 articles.

1. The problem of environmental monitoring;Biber,2011

2. Monitoring restored riparian vegetation: how can recent developments in remote sensing sciences help?

3. Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery

4. LiDAR remote sensing of forest structure

5. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

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1. Assessing Borneo’s tropical forests and plantations: a multi-sensor remote sensing and geospatial MCDA approach to environmental sustainability;Frontiers in Forests and Global Change;2024-07-03

2. Deep Unsupervised Visual Odometry Via Bundle Adjusted Pose Graph Optimization;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

3. Forest measurements and forestry related data;Introduction to Forestry and Natural Resources;2022

4. A Review of Unoccupied Aerial Vehicle Use in Wetland Applications: Emerging Opportunities in Approach, Technology, and Data;Drones;2021-05-25

5. Remotely sensed rivers in the Anthropocene: state of the art and prospects;Earth Surface Processes and Landforms;2020-01

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