Airborne Tree Crown Detection for Predicting Spatial Heterogeneity of Canopy Transpiration in a Tropical Rainforest

Joyson Ahongshangbam,Dirk Hölscher,Hendrayanto Hendrayanto,Florian Ellsäßer,Alexander Röll

doi:10.3390/rs12040651

Joyson Ahongshangbam, Dirk Hölscher + Show 3 more

Open Access

https://doi.org/10.3390/rs12040651

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Abstract

Tropical rainforests comprise complex 3D structures and encompass heterogeneous site conditions; their transpiration contributes to climate regulation. The objectives of our study were to test the relationship between tree water use and crown metrics and to predict spatial variability of canopy transpiration across sites. In a lowland rainforest of Sumatra, we measured tree water use with sap flux techniques and simultaneously assessed crown metrics with drone-based photogrammetry. We observed a close linear relationship between individual tree water use and crown surface area (R2 = 0.76, n = 42 trees). Uncertainties in predicting stand-level canopy transpiration were much lower using tree crown metrics than the more conventionally used stem diameter. 3D canopy segmentation analyses in combination with the tree crown–water use relationship predict substantial spatial heterogeneity in canopy transpiration. Among our eight study plots, there was a more than two-fold difference, with lower transpiration at riparian than at upland sites. In conclusion, we regard drone-based canopy segmentation and crown metrics to be very useful tools for the scaling of transpiration from tree- to stand-level. Our results indicate substantial spatial variation in crown packing and thus canopy transpiration of tropical rainforests.

Highlights

Tropical rainforests comprise a complex 3D structure, rich tree species diversity and encompass heterogeneous site conditions [1,2]
The objectives of our study were to test the relationship between tree water use and crown metrics and to predict spatial variability of canopy transpiration across sites
Ahongshangbam et al [5] found that drone-derived crown metrics correlated much better with tree water use than diameter at breast height (DBH)

Summary

Introduction

Tropical rainforests comprise a complex 3D structure, rich tree species diversity and encompass heterogeneous site conditions [1,2]. The prediction of canopy Et by tropical rainforests including its spatial heterogeneity may be fostered by a better understanding of the linkage between structure and function and forest structure variability across sites. Due to often relatively high unexplained variability in the DBH to water use relationship, resulting uncertainties of Et at the stand-level are relatively high. Ahongshangbam et al [5] found that drone-derived crown metrics correlated much better with tree water use than DBH. The reported crown metrics vs water use relationship cannot be applied to other vegetation types such as more heterogeneous tropical forest without further testing. Airborne tree crown assessments are potentially promising for reducing Et scaling uncertainties in tropical forests, but there are no studies confirming this yet

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