TY - GEN
T1 - Towards Global Forest Biomass Estimators from Tree Height Data
AU - Song, Qian
AU - Albrecht, Conrad M.
AU - Xiong, Zhitong
AU - Zhu, Xiao Xiang
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In order to estimate tree biomass, allometric equations take tree parameters such as tree height, wood density, circumference of trunk, and crown diameter as input parameters. Given that most of these quantities are challenging to be extracted from remote sensing data, we evaluate the option to approximate biomass by tree height only. We study our approach by evaluating linear regression, random forest, and Gaussian process regressor models when applied to the 2016 Jucker dataset. Results indicate that linear models fail to properly capture the relationship between biomass and tree height, but the Gaussian process regressor outperms the other two candidate models.
AB - In order to estimate tree biomass, allometric equations take tree parameters such as tree height, wood density, circumference of trunk, and crown diameter as input parameters. Given that most of these quantities are challenging to be extracted from remote sensing data, we evaluate the option to approximate biomass by tree height only. We study our approach by evaluating linear regression, random forest, and Gaussian process regressor models when applied to the 2016 Jucker dataset. Results indicate that linear models fail to properly capture the relationship between biomass and tree height, but the Gaussian process regressor outperms the other two candidate models.
KW - Gaussian process regression
KW - Tree biomass estimation
KW - allometric equation
KW - random forest models
UR - https://www.scopus.com/pages/publications/85141897521
U2 - 10.1109/IGARSS46834.2022.9884904
DO - 10.1109/IGARSS46834.2022.9884904
M3 - Conference contribution
AN - SCOPUS:85141897521
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 5652
EP - 5655
BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Y2 - 17 July 2022 through 22 July 2022
ER -