Design and Evaluation of Multispectral LiDAR for the Recovery of Arboreal Parameters

Wallace, Andrew M.; McCarthy, Aongus; Nichol, Caroline; Ren, Ximing; Morak, Simone; Martínez-Ramírez, Daniel; Woodhouse, Iain; Buller, Gerald S.

doi:10.1109/tgrs.2013.2285942

Cited by 104 publications

(76 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This indicates the validity of our assumption. While this study concentrated on a single wavelength in the short-wave infra-red domain, current developments of multi-spectral and hyperspectral lidar systems give the motivation for further research in this field; see, among others, , Hakala et al, 2012, Wallace et al, 2014.…”

Section: Discussion and Outlookmentioning

confidence: 99%

Assessment of Bottom-of-Atmosphere Reflectance in Lidar Data As Reference for Hyperspectral Imagery

Roncat

Pfeifer

Briese³

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:While airborne lidar has confirmed its leading role in delivering high-resolution 3D topographic information during the last decade, its radiometric potential has not yet been fully exploited. However, with the increasing availability of commercial lidar systems which (a) make use of full-waveform information and (b) operate at several wavelengths simultaneously, this potential is increasing as well. Radiometric calibration of the full-waveform information mentioned before allows for the derivation of physical target surface parameters such as the backscatter coefficient and a diffuse reflectance value at bottom of atmosphere (BOA), i.e. the target surface. With lidar being an active remote sensing technique, these parameters can be derived from lidar data itself, accompanied by the measurement or estimation of reference data for diffuse reflectance. In contrast to this, such a radiometric calibration for passive hyperspectral imagery (HSI) requires the knowledge and/or estimation of much more unknowns. However, in case of corresponding wavelength(s) radiometrically calibrated lidar datasets can deliver an areawide reference for BOA reflectance. This paper presents criteria to check where the assumption of diffuse BOA reflectance behaviour is fulfilled and how these criteria are assessed in lidar data; the assessment is illustrated by an extended lidar dataset. Moreover, for this lidar dataset and an HSI dataset recorded over the same area, the corresponding reflectance values are compared for different surface types.

show abstract

Section: Discussion and Outlookmentioning

confidence: 99%

Assessment of Bottom-of-Atmosphere Reflectance in Lidar Data As Reference for Hyperspectral Imagery

Roncat

Pfeifer

Briese³

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…While this study concentrated on a single wavelength, current developments of multi-spectral lidar systems , Hakala et al, 2012, Wallace et al, 2014 give the motivation for further research in this field. Figure 8: Results for test area 4, evaluated for a minimum echo ratio of 50% (top), 75% (middle) and 95% (bottom).…”

Section: Discussion and Outlookmentioning

confidence: 99%

A Comparison of Lidar Reflectance and Radiometrically Calibrated Hyperspectral Imagery

Roncat¹,

Briese²,

Pfeifer³

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a "single-wavelength reflectometer" to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.

show abstract

“…However, one application for which it can excel is providing high resolution active multispectral data derived from lidar intensity. In theory and in practice, multispectral lidar intensity can be used for many applications, including return/target classification [28,29]; individual tree identification, parameterization and classification [30]; water/land interface identification; and archaeological feature detection [31], among many others. Several years will go by before scientists in each of the above-mentioned fields will have an opportunity to assess the utility of the Titan multispectral lidar datasets as compared to what has been theorized or experimented so far.…”

Section: Multispectral Capabilitiesmentioning

confidence: 99%

Capability Assessment and Performance Metrics for the Titan Multispectral Mapping Lidar

et al. 2016

View full text Add to dashboard Cite

Abstract:In this paper we present a description of a new multispectral airborne mapping light detection and ranging (lidar) along with performance results obtained from two years of data collection and test campaigns. The Titan multiwave lidar is manufactured by Teledyne Optech Inc. (Toronto, ON, Canada) and emits laser pulses in the 1550, 1064 and 532 nm wavelengths simultaneously through a single oscillating mirror scanner at pulse repetition frequencies (PRF) that range from 50 to 300 kHz per wavelength (max combined PRF of 900 kHz). The Titan system can perform simultaneous mapping in terrestrial and very shallow water environments and its multispectral capability enables new applications, such as the production of false color active imagery derived from the lidar return intensities and the automated classification of target and land covers. Field tests and mapping projects performed over the past two years demonstrate capabilities to classify five land covers in urban environments with an accuracy of 90%, map bathymetry under more than 15 m of water, and map thick vegetation canopies at sub-meter vertical resolutions. In addition to its multispectral and performance characteristics, the Titan system is designed with several redundancies and diversity schemes that have proven to be beneficial for both operations and the improvement of data quality.

show abstract

Design and Evaluation of Multispectral LiDAR for the Recovery of Arboreal Parameters

Cited by 104 publications

References 41 publications

Assessment of Bottom-of-Atmosphere Reflectance in Lidar Data As Reference for Hyperspectral Imagery

Assessment of Bottom-of-Atmosphere Reflectance in Lidar Data As Reference for Hyperspectral Imagery

A Comparison of Lidar Reflectance and Radiometrically Calibrated Hyperspectral Imagery

Capability Assessment and Performance Metrics for the Titan Multispectral Mapping Lidar

Contact Info

Product

Resources

About