Estimation of Forest Variable and Aboveground Biomass using Terrestrial Laser Scanning in the Tropical Rainforest

2020 ◽  
Vol 48 (6) ◽  
pp. 853-863
Author(s):  
Solomon Mulat Beyene
2020 ◽  
Vol 42 (3) ◽  
pp. 884-901
Author(s):  
Om P.P. Kalwar ◽  
Yousif A. Hussin ◽  
Michael J.C. Weir ◽  
C.A.J.M. de Bie ◽  
Yogendra Karna

Trees ◽  
2021 ◽  
Author(s):  
Miro Demol ◽  
Kim Calders ◽  
Sruthi M. Krishna Moorthy ◽  
Jan Van den Bulcke ◽  
Hans Verbeeck ◽  
...  

Abstract Key message Stump-to-tip trends in basic wood density complicate the conversion of tree volume into aboveground biomass. We use 3D tree models from terrestrial laser scanning to obtain tree-level volume-weighted wood density. Abstract Terrestrial laser scanning (TLS) is used to generate realistic 3D tree models that enable a non-destructive way of quantifying tree volume. An accurate value for basic wood density is required to convert tree volume into aboveground biomass (AGB) for forest carbon assessments. However, basic density is characterised by high inter-, intra-species and within-tree variability and a likely source of error in TLS-derived biomass estimates. Here, 31 adult trees of 4 important European timber species (Fagus sylvatica, Larix decidua, Pinus sylvestris, Fraxinus excelsior) were scanned using TLS and then felled for several basic wood density measurements. We derived a reference volume-weighted basic density (ρw) by combining volume from 3D tree models with destructively assessed vertical density profiles. We compared this to basic density retrieved from a single basal disc over bark (ρbd), two perpendicular pith-to-bark increment cores at breast height (ρic), and sourcing the best available local basic wood density from publications. Stump-to-tip trends in basic wood density caused site-average woody AGB estimation biases ranging from −3.3 to + 7.8% when using ρbd and from −4.1 to + 11.8% when using ρic. Basic wood density from publications was in general a bad predictor for ρw as the bias ranged from −3.2 to + 17.2%, with little consistency across different density repositories. Overall, our density-attributed biases were similar to several recently reported biases in TLS-derived tree volume, leading to potentially large compound errors in biomass assessments with TLS if patterns of vertical basic wood density variation are not properly accounted for.


2021 ◽  
Vol 7 (1) ◽  
pp. 51-83
Author(s):  
Davide Tanasi ◽  
Stephan Hassam ◽  
Kaitlyn Kingsland ◽  
Paolo Trapani ◽  
Matthew King ◽  
...  

Abstract The archaeological site of the Domus Romana in Rabat, Malta was excavated almost 100 years ago yielding artefacts from the various phases of the site. The Melite Civitas Romana project was designed to investigate the domus, which may have been the home of a Roman Senator, and its many phases of use. Pending planned archaeological excavations designed to investigate the various phases of the site, a team from the Institute for Digital Exploration from the University of South Florida carried out a digitization campaign in the summer of 2019 using terrestrial laser scanning and aerial digital photogrammetry to document the current state of the site to provide a baseline of documentation and plan the coming excavations. In parallel, structured light scanning and photogrammetry were used to digitize 128 artefacts in the museum of the Domus Romana to aid in off-site research and create a virtual museum platform for global dissemination.


2021 ◽  
Vol 13 (3) ◽  
pp. 507
Author(s):  
Tasiyiwa Priscilla Muumbe ◽  
Jussi Baade ◽  
Jenia Singh ◽  
Christiane Schmullius ◽  
Christian Thau

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.


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