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Close-range laser scanning in forests: towards physically based semantics across scales


Morsdorf, Felix; Kükenbrink, Daniel; Schneider, Fabian D; Abegg, M; Schaepman, Michael E (2018). Close-range laser scanning in forests: towards physically based semantics across scales. Interface Focus, 8(2):2017.0046.

Abstract

Laser scanning with its unique measurement concept holds the potential to revolutionize the way we assess and quantify three-dimensional vegetation structure. Modern laser systems used at close range, be it on terrestrial, mobile or unmanned aerial platforms, provide dense and accurate three-dimensional data whose information just waits to be harvested. However, the transformation of such data to information is not as straightforward as for airborne and space-borne approaches, where typically empirical models are built using ground truth of target variables. Simpler variables, such as diameter at breast height, can be readily derived and validated. More complex variables, e.g. leaf area index, need a thorough understanding and consideration of the physical particularities of the measurement process and semantic labelling of the point cloud. Quantified structural models provide a framework for such labelling by deriving stem and branch architecture, a basis for many of the more complex structural variables. The physical information of the laser scanning process is still underused and we show how it could play a vital role in conjunction with three-dimensional radiative transfer models to shape the information retrieval methods of the future. Using such a combined forward and physically based approach will make methods robust and transferable. In addition, it avoids replacing observer bias from field inventories with instrument bias from different laser instruments. Still, an intensive dialogue with the users of the derived information is mandatory to potentially re design structural concepts and variables so that they profit most of the rich data that close range laser scanning provides.

Abstract

Laser scanning with its unique measurement concept holds the potential to revolutionize the way we assess and quantify three-dimensional vegetation structure. Modern laser systems used at close range, be it on terrestrial, mobile or unmanned aerial platforms, provide dense and accurate three-dimensional data whose information just waits to be harvested. However, the transformation of such data to information is not as straightforward as for airborne and space-borne approaches, where typically empirical models are built using ground truth of target variables. Simpler variables, such as diameter at breast height, can be readily derived and validated. More complex variables, e.g. leaf area index, need a thorough understanding and consideration of the physical particularities of the measurement process and semantic labelling of the point cloud. Quantified structural models provide a framework for such labelling by deriving stem and branch architecture, a basis for many of the more complex structural variables. The physical information of the laser scanning process is still underused and we show how it could play a vital role in conjunction with three-dimensional radiative transfer models to shape the information retrieval methods of the future. Using such a combined forward and physically based approach will make methods robust and transferable. In addition, it avoids replacing observer bias from field inventories with instrument bias from different laser instruments. Still, an intensive dialogue with the users of the derived information is mandatory to potentially re design structural concepts and variables so that they profit most of the rich data that close range laser scanning provides.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2018
Deposited On:26 Jun 2018 12:54
Last Modified:24 Sep 2019 23:31
Publisher:Royal Society Publishing
ISSN:2042-8898
OA Status:Closed
Publisher DOI:https://doi.org/10.1098/rsfs.2017.0046

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