Estimation of above-ground biomass of large tropical trees with terrestrial LiDAR
Gonzalez De Tanago, Jose ; Lau, Alvaro ; Bartholomeus, Harm ; Herold, Martin ; Avitabile, Valerio ; Raumonen, Pasi ; Martius, Christopher ; Goodman, Rosa C. ; Disney, Mathias ; Manuri, Solichin ; Burt, Andrew ; Calders, Kim - \ 2018
Methods in Ecology and Evolution 9 (2018)2. - ISSN 2041-210X - p. 223 - 234.
1. Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above-ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three-dimensional (3D) tree modelling of TLS point clouds. 2. Twenty-nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species-specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements. 3. AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV-RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV-RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics. 4. Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non-destructive method can be further used for testing and calibrating new allometric models, reducing the current under-representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.
Above-ground biomass assessment of tropical trees with Terrestrial LiDAR and 3D architecture models
Lau Sarmiento, A.I. ; Gonzalez de Tanago Meñaca, J. ; Bartholomeus, H.M. ; Herold, M. ; Avitabile, V. ; Raumonen, Pasi ; Martius, Christopher ; Goodman, R.C. ; Disney, Mathias ; Manuri, Solichin ; Burt, Andrew ; Calders, Kim - \ 2017
In: SilviLaser 2017 Program. - Blacksburg : Virginia Tech - p. 123 - 124.
Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences
Wijedasa, Lahiru S. ; Jauhiainen, Jyrki ; Könönen, Mari ; Lampela, Maija ; Vasander, Harri ; Leblanc, Marie-Claire ; Evers, Stephanie ; Smith, Thomas E.L. ; Yule, Catherine M. ; Varkkey, Helena ; Lupascu, Massimo ; Parish, Faizal ; Singleton, Ian ; Clements, Gopalasamy R. ; Aziz, Sheema Abdul ; Harrison, Mark E. ; Cheyne, Susan ; Anshari, Gusti Z. ; Meijaard, Erik ; Goldstein, Jenny E. ; Waldron, Susan ; Hergoualc'h, Kristell ; Dommain, Rene ; Frolking, Steve ; Evans, Christopher D. ; Posa, Mary Rose C. ; Glaser, Paul H. ; Suryadiputra, Nyoman ; Lubis, Reza ; Santika, Truly ; Padfield, Rory ; Kurnianto, Sofyan ; Hadisiswoyo, Panut ; Lim, Teck Wyn ; Page, Susan E. ; Gauci, Vincent ; Meer, Peter J. Van Der; Buckland, Helen ; Garnier, Fabien ; Samuel, Marshall K. ; Choo, Liza Nuriati Lim Kim ; O'reilly, Patrick ; Warren, Matthew ; Suksuwan, Surin ; Sumarga, Elham ; Jain, Anuj ; Laurance, William F. ; Couwenberg, John ; Joosten, Hans ; Vernimmen, Ronald ; Hooijer, Aljosja ; Malins, Chris ; Cochrane, Mark A. ; Perumal, Balu ; Siegert, Florian ; Peh, Kelvin S.H. ; Comeau, Louis-Pierre ; Verchot, Louis ; Harvey, Charles F. ; Cobb, Alex ; Jaafar, Zeehan ; Wösten, Henk ; Manuri, Solichin ; Müller, Moritz ; Giesen, Wim ; Phelps, Jacob ; Yong, Ding Li ; Silvius, Marcel ; Wedeux, Béatrice M.M. ; Hoyt, Alison ; Osaki, Mitsuru ; Hirano, Takashi ; Takahashi, Hidenori ; Kohyama, Takashi S. ; Haraguchi, Akira ; Nugroho, Nunung P. ; Coomes, David A. ; Quoi, Le Phat ; Dohong, Alue ; Gunawan, Haris ; Gaveau, David L.A. ; Langner, Andreas ; Lim, Felix K.S. ; Edwards, David P. ; Giam, Xingli ; Werf, Guido Van Der; Carmenta, Rachel ; Verwer, Caspar C. ; Gibson, Luke ; Gandois, Laure ; Graham, Laura Linda Bozena ; Regalino, Jhanson ; Wich, Serge A. ; Rieley, Jack ; Kettridge, Nicholas ; Brown, Chloe ; Pirard, Romain ; Moore, Sam ; Capilla, B.R. ; Ballhorn, Uwe ; Ho, Hua Chew ; Hoscilo, Agata ; Lohberger, Sandra ; Evans, Theodore A. ; Yulianti, Nina ; Blackham, Grace ; Onrizal, O. ; Husson, Simon ; Murdiyarso, Daniel ; Pangala, Sunita ; Cole, Lydia E.S. ; Tacconi, Luca ; Segah, Hendrik ; Tonoto, Prayoto ; Lee, Janice S.H. ; Schmilewski, Gerald ; Wulffraat, Stephan ; Putra, Erianto Indra ; Cattau, Megan E. ; Clymo, R.S. ; Morrison, Ross ; Mujahid, Aazani ; Miettinen, Jukka ; Liew, Soo Chin ; Valpola, Samu ; Wilson, David ; Arcy, Laura D'; Gerding, Michiel ; Sundari, Siti ; Thornton, Sara A. ; Kalisz, Barbara ; Chapman, Stephen J. ; Su, Ahmad Suhaizi Mat ; Basuki, Imam ; Itoh, Masayuki ; Traeholt, Carl ; Sloan, Sean ; Sayok, Alexander K. ; Andersen, Roxane - \ 2017
Global Change Biology 23 (2017)3. - ISSN 1354-1013 - p. 977 - 982.
The first International Peat Congress (IPC) held in the tropics – in Kuching (Malaysia) – brought together over 1000 international peatland scientists and industrial partners from across the world (“International Peat Congress with over 1000 participants!,” 2016). The congress covered all aspects of peatland ecosystems and their management, with a strong focus on the environmental, societal and economic challenges associated with contemporary large-scale agricultural conversion of tropical peat.
|Terrestrial LiDAR and 3D Reconstruction Models for Estimation of Large Tree Biomass in the Tropics
Lau Sarmiento, A.I. ; Gonzalez de Tanago Meñaca, J. ; Bartholomeus, H.M. ; Herold, M. ; Raumonen, P. ; Avitabile, V. ; Martius, Christopher ; Goodman, R.M. ; Manuri, Solichin - \ 2016
- 1 p.
A review of forest and tree plantation biomass equations in Indonesia
Anitha, Kamalakumari ; Verchot, Louis V. ; Joseph, Shijo ; Herold, Martin ; Manuri, Solichin ; Avitabile, Valerio - \ 2015
Annals of Forest Science 72 (2015)8. - ISSN 1286-4560 - p. 981 - 997.
Aboveground biomass - Allometric equations - Forest inventory - Indonesia - REDD+
Key message: We compiled 2,458 biomass equations from 168 destructive sampling studies in Indonesia. Unpublished academic theses contributed the largest share of the biomass equations. The availability of the biomass equations was skewed to certain regions, forest types, and species. Further research is necessary to fill the data gaps in emission factors and to enhance the implementation of climate change mitigation projects and programs. Context: Locally derived allometric equations contribute to reducing the uncertainty in the estimation of biomass, which may be useful in the implementation of climate change mitigation projects and programs in the forestry sector. Many regional and global efforts are underway to compile allometric equations. Aims: The present study compiles the available allometric equations in Indonesia and evaluates their adequacy in estimating biomass in the different types of forest across the archipelago. Methods: A systematic survey of the scientific literature was conducted to compile the biomass equations, including ISI publications, national journals, conference proceedings, scientific reports, and academic theses. The data collected were overlaid on a land use/land cover map to assess the spatial distribution with respect to different regions and land cover types. The validation of the equations for selected forest types was carried out using independent destructive sampling data. Results: A total of 2,458 biomass equations from 168 destructive sampling studies were compiled. Unpublished academic theses contributed the majority of the biomass equations. Twenty-one habitat types and 65 species were studied in detail. Diameter was the most widely used single predictor in all allometric equations. The cumulative number of individual trees cut was 5,207. The islands of Java, Kalimantan, and Sumatra were the most studied, while other regions were underexplored or unexplored. More than half of the biomass equations were for just seven species. The majority of the studies were carried out in plantation forests and secondary forests, while primary forests remain largely understudied. Validation using independent data showed that the allometric models for peat swamp forest had lower error departure, while the models for lowland dipterocarp forest had higher error departure. Conclusion: Although biomass studies are a major research activity in Indonesia due to its high forest cover, the majority of such activities are limited to certain regions, forest types, and species. More research is required to cover underrepresented regions, forest types, particular growth forms, and very large tree diameter classes.