scholarly journals A Novel Tree Biomass Estimation Model Applying the Pipe Model Theory and Adaptable to UAV-Derived Canopy Height Models

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 258
Author(s):  
Takashi Machimura ◽  
Ayana Fujimoto ◽  
Kiichiro Hayashi ◽  
Hiroaki Takagi ◽  
Satoru Sugita
Keyword(s):  
Model Theory ◽  
Canopy Height ◽  
Stem Volume ◽  
Biomass Estimation ◽  
Tree Biomass ◽  
Estimation Model ◽  
Individual Tree ◽  
Pipe Model ◽  
Plant Form ◽  
Pipe Model Theory

Aiming to develop a new tree biomass estimation model that is adaptable to airborne observations of forest canopies by unmanned aerial vehicles (UAVs), we applied two theories of plant form; the pipe model theory (PMT) and the statical model of plant form as an extension of the PMT for tall trees. Based on these theories, tree biomass was formulated using an individual tree canopy height model derived from a UAV. The advantage of this model is that it does not depend on diameter at breast height which is difficult to observe using remote-sensing techniques. We also proposed a treetop detection method based on the fractal geometry of the crown and stand. Comparing surveys in plantations of Japanese cedar (Cryptomeria japonica D. Don) and Japanese cypress (Chamaecyparis obtusa Endl.) in Japan, the root mean square error (RMSE) of the estimated stem volume was 0.26 m3 and was smaller than or comparative to that of models using different methodologies. The significance of this model is that it contains only one empirical parameter to be adjusted which was found to be rather stable among different species and sites, suggesting the wide adaptability of the model. Finally, we demonstrated the potential applicability of the model to light detection and ranging (LiDAR) data which can provide vertical leaf density distribution.

scholarly journals Models for biomass prediction of Cunninghamia lanceolata tree and stands in Southeastern China

2016 ◽  
Author(s):  
Mei Guangyi ◽  
Sun Yujun
Keyword(s):  
Wood Density ◽  
Forest Stand ◽  
Chinese Fir ◽  
Cunninghamia Lanceolata ◽  
Biomass Estimation ◽  
Tree Biomass ◽  
Estimation Model ◽  
Individual Tree ◽  
Natural Logarithm ◽  
Total Tree

Large uncertainties still remain when using existing biomass equations to estimate total tree and forest stand scale. In this paper, we develop individual-tree biomass models for Chinese fir (Cunninghamia lanceolata （Lamb.）Hook.) stands in Fujian Province, southeast of China. For this, we used 74 previously established models that are most commonly used to estimate tree biomass, and selected the best fit models and modified it. The results showed the published model with ln(B) (biomass), ln(D) (diameter at breast height), (ln(H)) 2, (total height) (ln(H))3 and ln(WD) (wood density) to be the best fitting model for estimating the tree biomass of Chinese fir. Furthermore, we observed that variables D, H (height), WD significantly correlated with the total tree biomass estimation model, as a result of it portraying the natural logarithm structure to be the best tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the analytic model with TV (tree volume), WD and BECF (biomass wood density conversion factor), achieved the highest accuracy simulation. Therefore, when combined with TV, WD and BECF to tree biomass volume coefficient bi for Chinese fir, the optimal model is the forest stand biomass (SB) estimation model, model with variables of stand volume (SV) and coefficient bi.

scholarly journals Models for biomass prediction of Cunninghamia lanceolata tree and stands in Southeastern China

2016 ◽  
Author(s):  
Mei Guangyi ◽  
Sun Yujun
Keyword(s):  
Wood Density ◽  
Forest Stand ◽  
Chinese Fir ◽  
Cunninghamia Lanceolata ◽  
Biomass Estimation ◽  
Tree Biomass ◽  
Estimation Model ◽  
Individual Tree ◽  
Natural Logarithm ◽  
Total Tree

Large uncertainties still remain when using existing biomass equations to estimate total tree and forest stand scale. In this paper, we develop individual-tree biomass models for Chinese fir (Cunninghamia lanceolata （Lamb.）Hook.) stands in Fujian Province, southeast of China. For this, we used 74 previously established models that are most commonly used to estimate tree biomass, and selected the best fit models and modified it. The results showed the published model with ln(B) (biomass), ln(D) (diameter at breast height), (ln(H)) 2, (total height) (ln(H))3 and ln(WD) (wood density) to be the best fitting model for estimating the tree biomass of Chinese fir. Furthermore, we observed that variables D, H (height), WD significantly correlated with the total tree biomass estimation model, as a result of it portraying the natural logarithm structure to be the best tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the analytic model with TV (tree volume), WD and BECF (biomass wood density conversion factor), achieved the highest accuracy simulation. Therefore, when combined with TV, WD and BECF to tree biomass volume coefficient bi for Chinese fir, the optimal model is the forest stand biomass (SB) estimation model, model with variables of stand volume (SV) and coefficient bi.

ESTIMATING SINGLE TREE STEM AND BRANCH BIOMASS USING TERRESTRIAL LASER SCANNING

2015 ◽  
Vol 77 (26) ◽  
Author(s):  
Nurliyana Izzati Ishak ◽  
Md Afif Abu Bakar ◽  
Muhammad Zulkarnain Abdul Rahman ◽  
Abd Wahid Rasib ◽  
Kasturi Devi Kanniah ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Stem Volume ◽  
Biomass Estimation ◽  
Forest Plot ◽  
Individual Tree ◽  
Matching Process ◽  
Branch Biomass ◽  
Individual Trees ◽  
Tree Stem

This paper presents a novel non-destructive approach for individual tree stem and branch biomass estimation using terrestrial laser scanning data. The study area is located at the Royal Belum Reserved Forest area, Gerik, Perak. Each forest plot was designed with a circular shape and contains several scanning locations to ensure good visibility of each tree. Unique tree signage was located on trees with diameter at breast height (DBH) of 10cm and above.  Extractions of individual trees were done manually and the matching process with the field collected tree properties were relied on the tree signage and tree location as collected by total station. Individual tree stems were reconstructed based on cylinder models from which the total stem volume was calculated. Biomass of individual tree stems was calculated by multiplying stem volume with specific wood density. Biomass of individual was estimated using similar concept of tree stem with the volume estimated from alpha-hull shape. The root mean squared errors (RMSE) of estimated biomass are 50.22kg and 27.20kg for stem and branch respectively. 

scholarly journals On the applicability of the pipe model theory on the chestnut tree (Castanea sativa Mill.)

Trees ◽  
2015 ◽  
Vol 29 (2) ◽  
pp. 321-332 ◽  
Author(s):  
Eric Gehring ◽  
Gianni Boris Pezzatti ◽  
Patrik Krebs ◽  
Stefano Mazzoleni ◽  
Marco Conedera
Keyword(s):  
Model Theory ◽  
Castanea Sativa ◽  
Chestnut Tree ◽  
Pipe Model ◽  
Castanea Sativa Mill ◽  
Pipe Model Theory
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