Introducing Close-Range Photogrammetry for Characterizing Forest Understory Plant Diversity and Surface Fuel Structure at Fine Scales-Reference-Cited by-同舟云学术

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Introducing Close-Range Photogrammetry for Characterizing Forest Understory Plant Diversity and Surface Fuel Structure at Fine Scales

Published:2016-09-02 Issue:5 Volume:42 Page:460-472
ISSN:0703-8992
Container-title:Canadian Journal of Remote Sensing
language:en
Short-container-title:Canadian Journal of Remote Sensing

Author:

Bright Benjamin C.¹,Loudermilk E. Louise²,Pokswinski Scott M.³,Hudak Andrew T.¹,O'Brien Joseph J.²

Affiliation:

1. USDA Forest Service, Rocky Mountain Research Station, Forestry Sciences Laboratory, 1221 South Main Street, Moscow, ID 83843, USA

2. USDA Forest Service, Southern Research Station, Center for Forest Disturbance Science, 320 Green Street, Athens, GA 30602, USA

3. University of Nevada at Reno, 1664 North Virginia MS 0314, Reno, NV 89557, USA

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/07038992.2016.1229598

Reference54 articles.

1. Estimating forest canopy fuel parameters using LIDAR data

2. A comparison between photogrammetry and laser scanning

3. Forest variable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM

4. A dendrite method for cluster analysis

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Tracking Darwin's footprints but with LiDAR for booting up the 3D and even beyond-3D understanding of plant intelligence;Remote Sensing of Environment;2024-09

2. Developing customized fuel models for shrub and bracken communities in Galicia (NW Spain);Journal of Environmental Management;2024-02

3. Wildland Fuel Characterization Across Space and Time;Landscape Fire, Smoke, and Health;2023-10-20

4. Evaluating Close-Range Photogrammetry for 3D Understory Fuel Characterization and Biomass Prediction in Pine Forests;Remote Sensing;2023-10-06

5. Forest fuel type classification: Review of remote sensing techniques, constraints and future trends;Journal of Environmental Management;2023-09

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