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A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing

1
School of Science, RMIT University, Melbourne 3000, Australia
2
Bushfire and Natural Hazards Cooperative Research Centre, East Melbourne 3002, Australia
3
Department of Environment Land Water and Planning, Victorian Government, East Melbourne 3002, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(18), 2118; https://doi.org/10.3390/rs11182118
Received: 28 June 2019 / Revised: 6 September 2019 / Accepted: 8 September 2019 / Published: 12 September 2019
Characteristics describing below canopy vegetation are important for a range of forest ecosystem applications including wildlife habitat, fuel hazard and fire behaviour modelling, understanding forest recovery after disturbance and competition dynamics. Such applications all rely on accurate measures of vegetation structure. Inherent in this is the assumption or ability to demonstrate measurement accuracy. 3D point clouds are being increasingly used to describe vegetated environments, however limited research has been conducted to validate the information content of terrestrial point clouds of understory vegetation. This paper describes the design and use of a field frame to co-register point intercept measurements with point cloud data to act as a validation source. Validation results show high correlation of point matching in forests with understory vegetation elements with large mass and/or surface area, typically consisting of broad leaves, twigs and bark 0.02 m diameter or greater in size (SfM, MCC 0.51–0.66; TLS, MCC 0.37–0.47). In contrast, complex environments with understory vegetation elements with low mass and low surface area showed lower correlations between validation measurements and point clouds (SfM, MCC 0.40 and 0.42; TLS, MCC 0.25 and 0.16). The results of this study demonstrate that the validation frame provides a suitable method for comparing the relative performance of different point cloud generation processes. View Full-Text
Keywords: structure from motion; terrestrial laser scanning; validation; 3D remote sensing; vegetation structure; biomass; forest measurement structure from motion; terrestrial laser scanning; validation; 3D remote sensing; vegetation structure; biomass; forest measurement
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MDPI and ACS Style

Hillman, S.; Wallace, L.; Reinke, K.; Hally, B.; Jones, S.; Saldias, D.S. A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing. Remote Sens. 2019, 11, 2118. https://doi.org/10.3390/rs11182118

AMA Style

Hillman S, Wallace L, Reinke K, Hally B, Jones S, Saldias DS. A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing. Remote Sensing. 2019; 11(18):2118. https://doi.org/10.3390/rs11182118

Chicago/Turabian Style

Hillman, Samuel, Luke Wallace, Karin Reinke, Bryan Hally, Simon Jones, and Daisy S. Saldias 2019. "A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing" Remote Sensing 11, no. 18: 2118. https://doi.org/10.3390/rs11182118

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