Generalized models for subtropical forest inventory attribute estimations using a rule-based exhaustive combination approach with airborne LiDAR-derived metrics-Reference-Cited by-同舟云学术

Generalized models for subtropical forest inventory attribute estimations using a rule-based exhaustive combination approach with airborne LiDAR-derived metrics

Published:2023-04-11 Issue:1 Volume:60 Page:
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Li Chungan¹^ORCID,Chen Zhongchao¹²,Zhou Xiangbei¹³,Zhou Mei⁴,Li Zhen⁵

Affiliation:

1. Forestry College, Guangxi University, Nanning, Guangxi, China

2. Guizhou Lifa Survey & Design Co. Ltd, Guiyang, Guizhou, China

3. Guangxi Natural Resources Vocational and Technical College, Fushui, Guangxi, China

4. School of Computer, Electronics and Information, Guangxi University, Nanning, Guangxi, China

5. Guangxi Forest Inventory & Planning Institute, Nanning, China

Funder

the Forest Department of Guangxi Zhuang Autonomous Region, China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2023.2194601

Reference70 articles.

1. High-resolution mapping of forest carbon stocks in the Colombian Amazon

2. A universal airborne LiDAR approach for tropical forest carbon mapping

3. Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data

4. Comparison of UAV LiDAR and Digital Aerial Photogrammetry Point Clouds for Estimating Forest Structural Attributes in Subtropical Planted Forests

5. Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data

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1. Stratification of vertical canopy structure to improve estimation of forest inventory attributes using airborne LiDAR data in a large subtropical region of China;Annals of Forest Research;2023-12-31

2. Effect of sample size on the estimation of forest inventory attributes using airborne LiDAR data in large-scale subtropical areas;Annals of Forest Science;2023-10-20