Capabilities and performance of dual-wavelength Echidna<sup>®</sup>lidar

Howe, Glenn A.; Hewawasam, Kuravi; Douglas, Ewan S.; Martel, Jason; Ли, Жан; Strahler, Alan H.; Schaaf, Crystal B.; Cook, Timothy A.; Chakrabarti, Supriya

doi:10.1117/1.jrs.9.095979

Cited by 13 publications

(20 citation statements)

References 8 publications

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“…; Howe et al. ). More capable instruments such as DWEL, SALCA and Riegl may also record all or parts of the return waveform, at the very least providing more returns per pulse than the CBL, which only records the first and last.…”

Section: Discussionmentioning

confidence: 98%

“…There are, however, still clear information benefits offered by highly capable commercial and research terrestrial lidars. For example, DWEL and SALCA use lasers of different wavelengths (1064 nm and 1548 nm) to separately identify returns from leaves and branches (Danson et al 2014;Howe et al 2015). More capable instruments such as DWEL, SALCA and Riegl may also record all or parts of the return waveform, at the very least providing more returns per pulse than the CBL, which only records the first and last.…”

Section: Discussionmentioning

confidence: 99%

“…Capability is characterized by improvements in the attributes of individual lidar pulses, such as range, resolution and emitted wavelengths, increasing the maximum capabilities of an instrument. Contemporary archetypes include the research instruments, the Dual-Wavelength Echidna Lidar (DWEL) (Strahler et al 2008;Douglas et al 2012;Howe et al 2015;Li et al 2016) and the SALford Advanced Canopy Analyzer (SALCA) (Danson et al 2014), and commercially available instruments such as the Riegl VZ-400 . While some of these highly capable instruments allow for variable scanning settings to decrease resolution and increase scanning speed, small, practical terrestrial lidar instruments offer the means to augment and extend the extensive, high-caliber information acquired with more capable scanners.…”

Section: Introductionmentioning

confidence: 99%

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Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

Paynter

Saenz

Genest

et al. 2016

Remote Sens Ecol Conserv

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A new wave of terrestrial lidar scanners, optimized for rapid scanning and portability, such as the Compact Biomass Lidar (CBL), enable and improve observations of structure across a range of important ecosystems. We performed studies with the CBL in temperate and tropical forests, caves, salt marshes and coastal areas subject to erosion. By facilitating additional scanning points, and therefore view angles, this new class of terrestrial lidar alters observation coverage within samples, potentially reducing uncertainty in estimates of ecosystem properties. The CBL has proved competent at reconstructing trees and mangrove roots using the same cylinder-based Quantitative Structure Models commonly utilized for data from more capable instruments (Raumonen et al. 2013). For tropical trees with morphologies that challenge standard reconstruction techniques, such as the buttressed roots of Ceiba trees and the multiple stems of strangler figs, the CBL was able to provide the versatility and the speed of deployment needed to fully characterize their unique features. For geomorphological features, the deployment flexibility of the CBL enabled sampling from optimal view-angles, including from a novel suspension system for sampling salt marsh creeks. Overall, the practical aspects of these instruments, which improve deployment logistics, and therefore data acquisition rate, are shown to be emerging capabilities, greatly increasing the potential for observation, particularly in highly temporally dynamic, inaccessible and geometrically complex ecosystems. In order to better analyze information quality across these diverse and challenging ecosystems, we also provide a novel and much-needed conceptual framework, the microstate model, to characterize and mitigate uncertainties in terrestrial lidar observations.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

Paynter

Saenz

Genest

et al. 2016

Remote Sens Ecol Conserv

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“…Firstly, a group of metaproperties should include pulse metaproperties that utilize as much of the information captured in the lidar pulses of the relevant TLS instrument as possible. TLS instruments other than the CBL may capture more returns per pulse or full waveform data (Calders et al., ), or return intensity at multiple wavelengths (Douglas et al., ; Gaulton, Danson, Pearson, Lewis, & Disney, ; Howe et al., ), resulting in many potential pulse metaproperties. In general, pulse metaproperties will take the form of descriptive statistics of the entire population of pulses, such as the mean, minimum, maximum, standard deviation, range, or ratio.…”

Section: Discussionmentioning

confidence: 99%

Classifying ecosystems with metaproperties from terrestrial laser scanner data

et al. 2017

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In this study, we introduce metaproperty analysis of terrestrial laser scanner (TLS) data, and demonstrate its application through several ecological classification problems. Metaproperty analysis considers pulse level and spatial metrics derived from the hundreds of thousands to millions of lidar pulses present in a single scan from a typical contemporary instrument. In such large aggregations, properties of the populations of lidar data reflect attributes of the underlying ecological conditions of the ecosystems.In this study, we provide the Metaproperty Classification Model to employ TLS metaproperty analysis for classification problems in ecology. We applied this to a proof‐of‐concept study, which classified 88 scans from rooms and forests with 100% accuracy, to serve as a template.We then applied the Metaproperty Classification Model in earnest, to separate scans from temperate and tropical forests with 97.09% accuracy (N = 224), and to classify scans from inland and coastal tropical rainforests with 84.07% accuracy (N = 270).The results demonstrate the potential for metaproperty analysis to identify subtle and important ecosystem conditions, including diseases and anthropogenic disturbances. Metaproperty analysis serves as an augmentation to contemporary object reconstruction applications of TLS in ecology, and can characterize regional heterogeneity.

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“…The lack of consolidated correction methods has also led to a prevalent neglect of correction [40,59]. This topic needs to be addressed with dedicated devices, e.g., dual-wavelength lidar [60].…”

Section: Discussionmentioning

confidence: 99%

Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57

et al. 2018

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Land Surface Phenology (LSP) and Leaf Area Index (LAI) are important variables that describe the photosynthetically active phase and capacity of vegetation. Both are derived on the global scale from optical satellite sensors and require robust validation based on in situ sensors at high temporal resolution. This study assesses the PAI Autonomous System from Transmittance Sensors at 57 • (PASTiS-57) instrument as a low-cost transmittance sensor for simultaneous monitoring of LSP and LAI in forest ecosystems. In a field experiment, spring leaf flush and autumn senescence in a Dutch beech forest were observed with PASTiS-57 and illumination independent, multi-temporal Terrestrial Laser Scanning (TLS) measurements in five plots. Both time series agreed to less than a day in Start Of Season (SOS) and End Of Season (EOS). LAI magnitude was strongly correlated with a Pearson correlation coefficient of 0.98. PASTiS-57 summer and winter LAI were on average 0.41 m 2 m −2 and 1.43 m 2 m −2 lower than TLS. This can be explained by previously reported overestimation of TLS. Additionally, PASTiS-57 was implemented in the Discrete Anisotropic Radiative Transfer (DART) Radiative Transfer Model (RTM) model for sensitivity analysis. This confirmed the robustness of the retrieval with respect to non-structural canopy properties and illumination conditions. Generally, PASTiS-57 fulfilled the CEOS LPV requirement of 20% accuracy in LAI for a wide range of biochemical and illumination conditions for turbid medium canopies. However, canopy non-randomness in discrete tree models led to strong biases. Overall, PASTiS-57 demonstrated the potential of autonomous devices for monitoring of phenology and LAI at daily temporal resolution as required for validation of satellite products that can be derived from ESA Copernicus' optical missions, Sentinel-2 and -3.

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Capabilities and performance of dual-wavelength Echidna^®lidar

Cited by 13 publications

References 8 publications

Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

Classifying ecosystems with metaproperties from terrestrial laser scanner data

Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57

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Capabilities and performance of dual-wavelength Echidna®lidar

Cited by 13 publications

References 8 publications

Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

Classifying ecosystems with metaproperties from terrestrial laser scanner data

Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57

Contact Info

Product

Resources

About

Capabilities and performance of dual-wavelength Echidna^®lidar