The Latent Dirichlet Allocation model applied to airborne <scp>LiDAR</scp> data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region-Reference-Cited by-同舟云学术

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

Published:2022-03-16 Issue:6 Volume:13 Page:1329-1342
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Valle Denis¹^ORCID,Silva Carlos Alberto¹^ORCID,Longo Marcos²^ORCID,Brando Paulo³^ORCID

Affiliation:

1. School of Forest, Fisheries, and Geomatics Sciences University of Florida Gainesville FL USA

2. Climate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USA

3. Department of Earth System Science University of California Irvine Irvine CA USA

Funder

National Science Foundation of Sri Lanka

U.S. Department of Energy

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13836

Reference61 articles.

1. A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions

2. Bayesian LDA for mixed-membership clustering analysis: The Rlda package

3. Landscape fragmentation, severe drought, and the new Amazon forest fire regime

4. Monitoring selective logging in western Amazonia with repeat lidar flights

5. The Susceptibility of Southeastern Amazon Forests to Fire: Insights from a Large-Scale Burn Experiment

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