LiDAR Utility for Natural Resource Managers

Hudak, Andrew T.; Evans, Jeffrey S.; Smith, Alistair M. S.

doi:10.3390/rs1040934

Cited by 149 publications

(81 citation statements)

References 115 publications

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“…Hudak et al (2009) reviewed LiDAR applications for natural resource management [38]. With increasing amounts and improved data quality, acquired simultaneously, LiCHy expands these possibilities.…”

Section: Potential Forest Applications Of Data From Lichy Systemmentioning

confidence: 99%

LiCHy: The CAF’s LiDAR, CCD and Hyperspectral Integrated Airborne Observation System

Pang

et al. 2016

Remote Sensing

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Abstract:We describe the design, implementation and performance of a novel airborne system, which integrates commercial waveform LiDAR, CCD (Charge-Coupled Device) camera and hyperspectral sensors into a common platform system. CAF's (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System is a unique system that permits simultaneous measurements of vegetation vertical structure, horizontal pattern, and foliar spectra from different view angles at very high spatial resolution (~1 m) on a wide range of airborne platforms. The horizontal geo-location accuracy of LiDAR and CCD is about 0.5 m, with LiDAR vertical resolution and accuracy 0.15 m and 0.3 m, respectively. The geo-location accuracy of hyperspectral image is within 2 pixels for nadir view observations and 5-7 pixels for large off-nadir observations of 55˝with multi-angle modular when comparing to LiDAR product. The complementary nature of LiCHy's sensors makes it an effective and comprehensive system for forest inventory, change detection, biodiversity monitoring, carbon accounting and ecosystem service evaluation. The LiCHy system has acquired more than 8000 km 2 of data over typical forests across China. These data are being used to investigate potential LiDAR and optical remote sensing applications in forest management, forest carbon accounting, biodiversity evaluation, and to aid in the development of similar satellite configurations. This paper describes the integration of the LiCHy system, the instrument performance and data processing workflow. We also demonstrate LiCHy's data characteristics, current coverage, and potential vegetation applications.

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Section: Potential Forest Applications Of Data From Lichy Systemmentioning

confidence: 99%

LiCHy: The CAF’s LiDAR, CCD and Hyperspectral Integrated Airborne Observation System

Pang

et al. 2016

Remote Sensing

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“…As such, the existing Landsat TCC uncertainty estimates may be regarded as preliminary with regard to biome-specific studies. Now, with increasing coverage worldwide, high-resolution spaceborne imagery (HRSI) as well as LiDAR samples offer additional and often superior means of reference data collection [38][39][40][41]. Tree cover is estimated from HRSI by visual analysis [33] or by semi-automated object-oriented methods [1,[42][43][44].…”

Section: Assessing Spaceborne Maps Of Tree Cover Across the Ttementioning

confidence: 99%

Calibration and Validation of Landsat Tree Cover in the Taiga−Tundra Ecotone

et al. 2016

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Abstract:Monitoring current forest characteristics in the taiga´tundra ecotone (TTE) at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal forest tree cover. This domain-specific calibration model used estimates of forest height to determine reference forest cover that best matched Landsat estimates. The model removed the systematic under-estimation of tree canopy cover >80% and indicated that Landsat estimates of tree canopy cover more closely matched canopies at least 2 m in height rather than 5 m. The validation improved estimates of uncertainty in tree canopy cover in discontinuous TTE forests for three temporal epochs (2000, 2005, and 2010) by reducing systematic errors, leading to increases in tree canopy cover uncertainty. Average pixel-level uncertainties in tree canopy cover were 29.0%, 27.1% and 31.1% for the 2000, 2005 and 2010 epochs, respectively. Maps from these calibrated data improve the uncertainty associated with Landsat tree canopy cover estimates in the discontinuous forests of the circumpolar TTE.

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“…One of the first attempts to use airborne lidar for vegetation mapping was reported by the Canadian Forestry Service, which demonstrated the applicability of profiling airborne lidar for the estimation of height and density of the forest canopy and the ground elevation underneath [1]. This and numerous subsequent studies showed that lidar measurements of vegetation canopy can be used to characterize vegetation vertical structure and derive various physical attributes used for academic research, environmental studies and natural resources management programs [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Airborne Lidar: Advances in Discrete Return Technology for 3D Vegetation Mapping

Ussyshkin

Theriault

2011

Remote Sensing

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Conventional discrete return airborne lidar systems, used in the commercial sector for efficient generation of high quality spatial data, have been considered for the past decade to be an ideal choice for various mapping applications. Unlike two-dimensional aerial imagery, the elevation component of airborne lidar data provides the ability to represent vertical structure details with very high precision, which is an advantage for many lidar applications focusing on the analysis of elevated features such as 3D vegetation mapping. However, the use of conventional airborne discrete return lidar systems for some of these applications has often been limited, mostly due to relatively coarse vertical resolution and insufficient number of multiple measurements in vertical domain. For this reason, full waveform airborne sensors providing more detailed representation of target vertical structure have often been considered as a preferable choice in some areas of 3D vegetation mapping application, such as forestry research. This paper presents an overview of the specific features of airborne lidar technology concerning 3D mapping applications, particularly vegetation mapping. Certain key performance characteristics of lidar sensors important for the quality of vegetation mapping are discussed and illustrated by the advanced capabilities of the ALTM-Orion, a new discrete return sensor manufactured by Optech Incorporated. It is demonstrated that advanced discrete return sensors with enhanced 3D mapping capabilities can produce data of enhanced quality, which can represent complex structures of vegetation targets at the level of details equivalent in some aspects to the content of full waveform data. It is also shown that recent advances in conventional airborne lidar technology bear the potential to create a new application niche, where high quality dense point clouds, enhanced by fully recorded intensity for multiple OPEN ACCESSRemote Sens. 2011, 3 417 returns, may provide sufficient information for modeling and analysis, which have traditionally been applied mostly to full waveform data.

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LiDAR Utility for Natural Resource Managers

Cited by 149 publications

References 115 publications

LiCHy: The CAF’s LiDAR, CCD and Hyperspectral Integrated Airborne Observation System

LiCHy: The CAF’s LiDAR, CCD and Hyperspectral Integrated Airborne Observation System

Calibration and Validation of Landsat Tree Cover in the Taiga−Tundra Ecotone

Airborne Lidar: Advances in Discrete Return Technology for 3D Vegetation Mapping

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