Identification and characterization of gaps and roads in the Amazon rainforest with LiDAR data

doi:10.3832/ifor4295-017

Identification and characterization of gaps and roads in the Amazon rainforest with LiDAR data

José Augusto Spiazzi Favarin⁽¹⁾ , Mateus Sabadi Schuh⁽²⁾, Juliana Marchesan⁽²⁾, Elisiane Alba⁽³⁾, Rudiney Soares Pereira⁽⁴⁾

iForest - Biogeosciences and Forestry, Volume 17, Issue 4, Pages 229-235 (2024)
doi: https://doi.org/10.3832/ifor4295-017
Published: Aug 03, 2024 - Copyright © 2024 SISEF

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Geo-mapping

Gap formations in the forest canopy have natural causes, such as bad weather, and anthropic ones, such as sustainable selective extraction of trees and illegal logging, which can already be detected through orbital remote sensing. However, the Amazon region is under frequent cloud cover, which makes it challenging to detect gaps using passive sensors. This study aimed to identify and delimit gaps in the Amazon forest canopy through airborne LiDAR (Light Detection and Ranging) sensor application while testing six different return densities. LiDAR and forest inventory data were obtained over an Amazon rainforest region, defining the minimum area as a forest canopy gap. The point cloud was processed to obtain six return densities with the generation of their respective CHM (Canopy Height Model), which were applied for segmentation and subsequent identification of gap areas and roads. The minimum gap area found was 34 m², and the Kruskal Wallis test showed no significant difference among the six densities in gap detection; however, road identification decreased as the return density decreased. We concluded that LiDAR data proved promising as point clouds with low return density can be used without impairing gap identification. However, reducing the return density for road identification is not recommended.

Keywords

Forest Canopy Gaps, Aerial Laser Scanning, Point Density, Remote Sensing

Authors’ address

(1)

0000-0001-8870-5942
Postgraduate Program in Forest Sciences, Federal University of Paraná /UFPR, Lothário Meissner Avenue, 632, Jardim Botnico, 80210-170, Curitiba, PR (Brazil)

(2)

0000-0003-4996-0902
0000-0002-2167-5862
Postgraduate Program in Forest Engineering, Federal University of Santa Maria/UFSM, Roraima Avenue, 1000, Camobi, 97105-900, Santa Maria, RS (Brazil)

(3)

0000-0001-6210-4559
Academic Unity of Serra Talhada, Federal Rural University of Pernambuco/UFRPE, Gregório Ferraz Nogueira Av., 56909-535, Serra Talhada, PE (Brazil)

(4)

0000-0002-9846-4879
Rural Engineering Department, Federal University of Santa Maria/UFSM, Roraima Avenue, 1000, Camobi, 97105-900, Santa Maria, RS (Brazil)

Corresponding author

José Augusto Spiazzi Favarin
jaspiazzi@gmail.com

Citation

Spiazzi Favarin JA, Sabadi Schuh M, Marchesan J, Alba E, Soares Pereira R (2024). Identification and characterization of gaps and roads in the Amazon rainforest with LiDAR data. iForest 17: 229-235. - doi: 10.3832/ifor4295-017

Academic Editor

Matteo Garbarino

Paper history

Received: Dec 27, 2022
Accepted: Jun 11, 2024

First online: Aug 03, 2024
Publication Date: Aug 31, 2024
Publication Time: 1.77 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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