Assessing soil CO2 emission on eucalyptus species using UAV-based reflectance and vegetation indices

Eucalyptus species play an important role in the global carbon cycle, especially in reducing the greenhouse effect as well as storing atmospheric CO₂. Thus, assessing the amount of CO₂ released by the soil in forest areas can generate important information for environmental monitoring. This study aims to verify the relation between soil carbon dioxide (CO₂) flux (FCO₂), spectral bands, and vegetation indices (VIs) derived from a UAV-based multispectral camera over an area of eucalyptus species. Multispectral imageries (green, red-edge, and near-infrared) from the Parrot Sequoia sensor, derived vegetation indices, and the FCO₂ data from a LI-COR 8100 analyzer, combined with soil moisture and temperature data, were collected and related. The vegetation indices ATSAVI (Adjusted Transformed Soil-Adjusted VI), GSAVI (Green Soil Adjusted Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), which use soil correction factors, exhibited a strong negative correlation with FCO₂ for the species E. camaldulensis, E. saligna, and E. urophylla species. A Multivariate Analysis of Variance showed significance (p < 0.01) for the species factor, which indicates that there are differences when considering all variables simultaneously. The results achieved in this study show a specific correlation between the data of soil CO₂ emission and the eucalypt species, providing a distinction of values between the species in the statistical data.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-08-31
DOI
https://doi.org/10.1038/s41598-024-71430-2
Citations
7
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
1.44

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing soil CO2 emission on eucalyptus species using UAV-based reflectance and vegetation indices

Dthenifer Cordeiro Santana, Luís Guilherme Teixeira Crusiol, João Lucas Della-Silva, Fernando Saragosa Rossi et al.
7 citations
Scientific Reports
Remote Sensing and LiDAR Applications
1.44
article

Assessing soil CO2 emission on eucalyptus species using UAV-based reflectance and vegetation indices

Dthenifer Cordeiro Santana, Luís Guilherme Teixeira Crusiol, João Lucas Della-Silva, Fernando Saragosa Rossi, Paulo Eduardo Teodoro, Newton La Scala, Fábio Henrique Rojo Baio, Larissa Pereira Ribeiro Teodoro, Carlos Antônio da Silva, Wendel Bueno Morinigo
article en
7 citations

Abstract

Eucalyptus species play an important role in the global carbon cycle, especially in reducing the greenhouse effect as well as storing atmospheric CO₂. Thus, assessing the amount of CO₂ released by the soil in forest areas can generate important information for environmental monitoring. This study aims to verify the relation between soil carbon dioxide (CO₂) flux (FCO₂), spectral bands, and vegetation indices (VIs) derived from a UAV-based multispectral camera over an area of eucalyptus species. Multispectral imageries (green, red-edge, and near-infrared) from the Parrot Sequoia sensor, derived vegetation indices, and the FCO₂ data from a LI-COR 8100 analyzer, combined with soil moisture and temperature data, were collected and related. The vegetation indices ATSAVI (Adjusted Transformed Soil-Adjusted VI), GSAVI (Green Soil Adjusted Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), which use soil correction factors, exhibited a strong negative correlation with FCO₂ for the species E. camaldulensis, E. saligna, and E. urophylla species. A Multivariate Analysis of Variance showed significance (p < 0.01) for the species factor, which indicates that there are differences when considering all variables simultaneously. The results achieved in this study show a specific correlation between the data of soil CO₂ emission and the eucalypt species, providing a distinction of values between the species in the statistical data.

Scientific ReportsVol. 14(1)
Universidade Federal de Mato Grosso do Sul (BR), Universidade de São Paulo (BR), Brazilian Agricultural Research Corporation (BR), Universidade do Estado de Mato Grosso (BR), Universidade Federal de Mato Grosso (BR), Agricultural Research Corporation (SD), Universidade Estadual Paulista (Unesp) (BR)
Universidade do Estado de Mato Grosso, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul, Universidade Federal de Mato Grosso do Sul
Life in Land
Openalex Percentile: Top 20%
Remote Sensing and LiDAR Applications
1.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.