A Comparison of Individual Tree and Forest Plot Height Derived from Lidar and InSAR

Huang, Shengli; Hager, Stacey; Halligan, Kerry Q.; Fairweather, Ian S.; Swanson, Alan; Crabtree, Robert L.

doi:10.14358/pers.75.2.159

Cited by 19 publications

(16 citation statements)

References 44 publications

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“…Airborne LiDAR tends to slightly underestimate field-measured estimates in the case of dense forest stands because of its poor ability to penetrate the canopy and reach the forest floor. Also, tree height estimates may be underestimated because laser pulses are not always reflected from treetops, particularly for trees with smaller crown diameters or conically shaped crowns, whereby the laser pulse may detect the sides of the tree instead of the treetop [7,8]. One of the main advantages of airborne laser scanning (ALS) is that it covers large areas, but costs can be relatively high and lower point densities tend to limit tree detection accuracy, according to [9].…”

Section: Introductionmentioning

confidence: 99%

“…However, the modern laser scanners with a sufficiently wide beam, either terrestrials or installed on Unmanned Aerial Vehicles (UAVs) (for example Riegl Vux-1), appear to be very promising. To evaluate DBH, [7] implemented a circle approximation and concluded that it estimated DBH capably if there were a sufficient number of surface laser points, but DBH estimates were smaller with too few data points. Similarly, [15] estimated DBH efficiently using a circle-fitting algorithm; they concluded that the use of TLS could be fraught with errors if there were an inadequate number of laser points due to occlusion from other stems.…”

Section: Introductionmentioning

confidence: 99%

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Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

2016

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Airborne laser scanning (ALS) allows for extensive coverage, but the accuracy of tree detection and form can be limited. Although terrestrial laser scanning (TLS) can improve on ALS accuracy, it is rather expensive and area coverage is limited. Multi-view stereopsis (MVS) techniques combining computer vision and photogrammetry may offer some of the coverage benefits of ALS and the improved accuracy of TLS; MVS combines computer vision research and automatic analysis of digital images from common commercial digital cameras with various algorithms to reconstruct three-dimensional (3D) objects with realistic shape and appearance. Despite the relative accuracy (relative geometrical distortion) of the reconstructions available in the processing software, the absolute accuracy is uncertain and difficult to evaluate. We evaluated the data collected by a common digital camera through the processing software (Agisoft PhotoScan ©) for photogrammetry by comparing those by direct measurement of the 3D magnetic motion tracker. Our analyses indicated that the error is mostly concentrated in the portions of the tree where visibility is lower, i.e., the bottom and upper parts of the stem. For each reference point from the digitizer we determined how many cameras could view this point. With a greater number of cameras we found increasing accuracy of the measured object space point positions (as expected), with a significant positive change in the trend beyond five cameras; when more than five cameras could view this point, the accuracy began to increase more abruptly, but eight cameras or more provided no increases in accuracy. This method allows for the retrieval of larger datasets from the measurements, which could improve the accuracy of estimates of 3D structure of trees at potentially reduced costs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

2016

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“…Nevertheless, small footprint discrete return airborne LiDAR tend to slightly underestimate field measured tree heights, as the laser pulses are not always reflected from treetops. For trees with smaller crown widths or conically shaped crowns, there are chances for the laser pulse to hit the sides of the tree instead of the treetop [10,11]. Airborne LiDAR fails to capture the complete vertical distribution of the canopy [5].…”

Section: Introductionmentioning

confidence: 99%

Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter

Srinivasan¹,

Popescu²,

Eriksson³

et al. 2015

Remote Sensing

124

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Accurate measures of forest structural parameters are essential to forest inventory and growth models, managing wildfires, and modeling of carbon cycle. Terrestrial laser scanning (TLS) fills the gap between tree scale manual measurements and large scale airborne LiDAR measurements by providing accurate below crown information through non-destructive methods. This study developed innovative methods to extract individual tree height, diameter at breast height (DBH), and crown width of trees in East Texas. Further, the influence of scan settings, such as leaf-on/leaf-off seasons, tree distance from the scanner, and processing choices, on the accuracy of deriving tree measurements were also investigated. DBH was retrieved by cylinder fitting at different height bins. Individual trees were extracted from the TLS point cloud to determine tree heights and crown widths. The R-squared value ranged from 0.91 to 0.97 when field measured DBH was validated against TLS derived DBH using different methods. An accuracy of 92% (RMSE = 1.51 m) was obtained for predicting tree heights. The R-squared value was 0.84 and RMSE was 1.08 m when TLS derived crown widths were validated using field measured crown widths. Examples of underestimations of field measured forest structural parameters due to tree shadowing have also been discussed in this study. The results from this study will benefit foresters and remote sensing studies from airborne and spaceborne platforms, for map upscaling or calibration purposes, for aboveground biomass estimation, and prudent decision making by the forest management. OPEN ACCESSRemote Sens. 2015, 7 1878

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“…A similar study explored LiDAR-radar synergy for predicting aboveground biomass, and found only negligible improvement by including radar [117]. LiDAR has also been found to be superior to radar for accurately detecting the height of individual trees and forest plots [118]. However, others argue that because LiDAR and radar sensitivities differ so markedly at fine scales, LiDAR-radar comparisons are only useful at broad scales [119].…”

Section: Sensor Integrationmentioning

confidence: 99%

LiDAR Utility for Natural Resource Managers

2009

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Applications of LiDAR remote sensing are exploding, while moving from the research to the operational realm. Increasingly, natural resource managers are recognizing the tremendous utility of LiDAR-derived information to make improved decisions. This review provides a cross-section of studies, many recent, that demonstrate the relevance of LiDAR across a suite of terrestrial natural resource disciplines including forestry, fire and fuels, ecology, wildlife, geology, geomorphology, and surface hydrology. We anticipate that interest in and reliance upon LiDAR for natural resource management, both alone and in concert with other remote sensing data, will continue to rapidly expand for the foreseeable future.

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A Comparison of Individual Tree and Forest Plot Height Derived from Lidar and InSAR

Cited by 19 publications

References 44 publications

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter

LiDAR Utility for Natural Resource Managers

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