Allometric equations for integrating remote sensing imagery into forest monitoring programmes

Jucker, Tommaso; Caspersen, John P.; Chave, Jérôme; Antin, Cécile; Barbier, Nicolas; Bongers, Frans; Dalponte, Michele; Ewijk, Karin Y. van; Forrester, David I.; Haeni, Matthias; Higgins, Steven I.; Holdaway, Robert J.; Iida, Yoshihiro; Lorimer, Craig G.; Marshall, Peter; Takoudjou, Stéphane Momo; Moncrieff, Glenn R.; Ploton, Pierre; Poorter, Lourens; Rahman, K. Abd; Schlund, Michael; Sonké, Bonaventure; Sterck, Frank J.; Trugman, Anna T.; Usoltsev, Vladimir А.; Vanderwel, Mark C.; Waldner, Peter; Wedeux, B. M. M.; Wirth, Christian; Wöll, Hannsjörg; Woods, Murray; Xiang, Wenhua; Zimmermann, Niklaus E.; Coomes, David A.

doi:10.1111/gcb.13388

Cited by 287 publications

(347 citation statements)

References 64 publications

(112 reference statements)

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“…, Jucker et al. ), and tree crown architecture depends on ecological strategies (Bohlman and O'Brien , Poorter et al. , Iida et al.…”

Section: Model Descriptionmentioning

confidence: 99%

An individual‐based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications

Maréchaux

Chave

2017

Ecological Monographs

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Forest dynamic models predict the current and future states of ecosystems and are a nexus between physiological processes and empirical data, forest plot inventories and remote‐sensing information. The problem of biodiversity representation in these models has long been an impediment to a detailed understanding of ecosystem processes. This challenge is amplified in species‐rich and high‐carbon tropical forests. Here we describe an individual‐based and spatially explicit forest growth simulator, TROLL, that integrates recent advances in plant physiology. Processes (carbon assimilation, allocation, reproduction, and mortality) are linked to species‐specific functional traits, and the model was parameterized for an Amazonian tropical rainforest. We simulated a forest regeneration experiment from bare soil, and we validated it against observations at our sites. Simulated forest regeneration compared well with observations for stem densities, gross primary productivity, aboveground biomass, and floristic composition. After 500 years of regrowth, the simulated forest displayed structural characteristics similar to observations (e.g., leaf area index and trunk diameter distribution). We then assessed the model's sensitivity to a number of key model parameters: light extinction coefficient and carbon quantum yield, and to a lesser extent mortality rate, and carbon allocation, all influenced ecosystem features. To illustrate the potential of the approach, we tested whether variation in species richness and composition influenced ecosystem properties. Overall, species richness had a positive effect on ecosystem processes, but this effect was controlled by the identity of species rather by richness per se. Also, functional trait community means had a stronger effect than functional diversity on ecosystem processes. TROLL should be applicable to many tropical forests sites, and data requirement is tailored to ongoing trait collection efforts. Such a model should foster the dialogue between ecology and the vegetation modeling community, help improve the predictive power of models, and eventually better inform policy choices.

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“…, Jucker et al. ), and tree crown architecture depends on ecological strategies (Bohlman and O'Brien , Poorter et al. , Iida et al.…”

Section: Model Descriptionmentioning

confidence: 99%

An individual‐based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications

Maréchaux

Chave

2017

Ecological Monographs

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“…Improved plot‐level knowledge of height–diameter relationships would also help improve remote sensing‐based estimates of local and global forest biomass. For example space‐ and airborne LIDAR measure canopy height (Baccini et al., ; Saatchi et al., ) and high‐quality ground estimates of AGB are needed to calibrate height–AGB allometries (Jucker et al., ).…”

Section: Introductionmentioning

confidence: 99%

Field methods for sampling tree height for tropical forest biomass estimation

et al. 2018

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Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site‐to‐site variation in height–diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan‐tropical or regional allometric equations to estimate height.Using a pan‐tropical dataset of 73 plots where at least 150 trees had in‐field ground‐based height measurements, we examined how the number of trees sampled affects the performance of locally derived height–diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement.Using cross‐validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate‐based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand‐level biomass produced using local allometries to estimate tree height show no over‐ or under‐estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height–diameter models with low height prediction error) entirely random or diameter size‐class stratified approaches.Our results indicate that even limited sampling of heights can be used to refine height–diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.

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“…In the various reports, utilizing airborne-based investigation methods, including UAS observations, relationships between canopy width or canopy area and DBH have rarely been reported. Results shown by Jucker et al [36] present the relation of tree height and crown diameter with the stem diameter, which is utilizing airborne LiDAR information. From such works, we can determine that relations between the two parameters can be considered with relation, yet direct measurement of only canopy information and DBH is unclear with the use of photogrammetry.…”

Section: Introductionmentioning

confidence: 99%

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

et al. 2017

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Methods for accurately measuring biophysical parameters are a key component for quantitative evaluation regarding to various forest applications. Conventional in situ measurements of these parameters take time and expense, encountering difficultness at locations with heterogeneous microtopography. To obtain precise biophysical data in such situations, we deployed an unmanned aerial system (UAS) multirotor drone in a cypress forest in a mountainous area of Japan. The structure from motion (SfM) method was used to construct a three-dimensional (3D) model of the forest (tree) structures from aerial photos. Tree height was estimated from the 3D model and compared to in situ ground data. We also analyzed the relationships between a biophysical parameter, diameter at breast height (DBH), of individual trees with canopy width and area measured from orthorectified images. Despite the constraints of ground exposure in a highly dense forest area, tree height was estimated at an accuracy of root mean square error = 1.712 m for observed tree heights ranging from 16 to 24 m. DBH was highly correlated with canopy width (R 2 = 0.7786) and canopy area (R 2 = 0.7923), where DBH ranged from 11 to 58 cm. The results of estimating forest parameters indicate that drone-based remote-sensing methods can be utilized to accurately analyze the spatial extent of forest structures.

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Allometric equations for integrating remote sensing imagery into forest monitoring programmes

Cited by 287 publications

References 64 publications

An individual‐based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications

An individual‐based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications

Field methods for sampling tree height for tropical forest biomass estimation

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

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