Innovations in Ground and Airborne Technologies as Reference and for Training and Validation: Terrestrial Laser Scanning (TLS) View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03-29

AUTHORS

M. Disney, A. Burt, K. Calders, C. Schaaf, A. Stovall

ABSTRACT

The use of terrestrial laser scanning (TLS) to provide accurate estimates of 3D forest canopy structure and above-ground biomass (AGB) has developed rapidly. Here, we provide an overview of the state of the art in using TLS for estimating forest structure for AGB. We provide a general overview of TLS methods and then outline the advantages and limitations of TLS for estimating AGB. We discuss the specific type of measurements that TLS can provide, tools and methods that have been developed for turning TLS point clouds into quantifiable metrics of tree size and volume, as well as some of the challenges to improving these measurements. We discuss the role of TLS for enabling accurate calibration and validation (cal/val) of Earth observation (EO)-derived estimates of AGB from spaceborne lidar and RADAR missions. We give examples of the types of TLS equipment that are in use and how these might develop in future, and we show examples of where TLS has already been applied to measuring AGB in the tropics in particular. Comparing TLS with harvested AGB shows r2 > 0.95 for all studies thus far, with absolute agreement to within 10% at the individual tree level for all trees and to within 2% in the majority of cases. Current limitations to the uptake of TLS include the capital cost of some TLS equipment, processing complexity and the relatively small coverage that is possible. We argue that combining TLS measurements with the existing ground-based survey approaches will allow improved allometric models and better cal/val, resulting in improved regional and global estimates of AGB from space, with better-characterised, lower uncertainties. The development of new, improved equipment and methods will accelerate this process and make TLS more accessible. More... »

PAGES

1-22

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10712-019-09527-x

DOI

http://dx.doi.org/10.1007/s10712-019-09527-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113106804


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