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Open AccessArticle

Sensitivity Analysis of the DART Model for Forest Mensuration with Airborne Laser Scanning

1
Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK
2
Coillte Teoranta, Castletroy, V94 C780 Limerick, Ireland
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(2), 247; https://doi.org/10.3390/rs12020247
Received: 25 November 2019 / Revised: 26 December 2019 / Accepted: 7 January 2020 / Published: 10 January 2020
(This article belongs to the Special Issue Lidar Remote Sensing of Forest Structure, Biomass and Dynamics)
Airborne Laser Scanning (ALS) measurements are increasingly vital in forest management and national forest inventories. Despite the growing reliance on ALS data, comparatively little research has examined the sensitivity of ALS measurements to varying survey conditions over commercially important forests. This study investigated: (i) how accurately the Discrete Anisotropic Radiative Transfer (DART) model was able to replicate small-footprint ALS measurements collected over Irish conifer plantations, and (ii) how survey characteristics influenced the precision of discrete-return metrics. A variance-based global sensitivity analysis demonstrated that discrete-return height distributions were accurately and consistently simulated across 100 forest inventory plots with few perturbations induced by varying acquisition parameters or ground topography. In contrast, discrete return density, canopy cover and the proportion of multiple returns were sensitive to fluctuations in sensor altitude, scanning angle, pulse repetition frequency and pulse duration. Our findings corroborate previous studies indicating that discrete-return heights are robust to varying acquisition parameters and may be reliable predictors for the indirect retrieval of forest inventory measurements. However, canopy cover and density metrics are only comparable for ALS data collected under similar acquisition conditions, precluding their universal use across different ALS surveys. Our study demonstrates that DART is a robust model for simulating discrete-return measurements over structurally complex forests; however, the replication of foliage morphology, density and orientation are important considerations for radiative transfer simulations using synthetic trees with explicitly defined crown architectures. View Full-Text
Keywords: airborne laser scanning; forest inventory; radiative transfer modeling; sensitivity analysis airborne laser scanning; forest inventory; radiative transfer modeling; sensitivity analysis
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MDPI and ACS Style

Roberts, O.; Bunting, P.; Hardy, A.; McInerney, D. Sensitivity Analysis of the DART Model for Forest Mensuration with Airborne Laser Scanning. Remote Sens. 2020, 12, 247.

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