Assessment of airborne scanning laser altimetry (lidar) in a deltaic wetland environment

Töyrä, Jessika; Pietroniro, Alain; Hopkinson, C.; Kalbfleisch, William

doi:10.5589/m03-040

Cited by 44 publications

(18 citation statements)

References 6 publications

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“…It is not possible to estimate whether LiDAR ground return did in fact come from the ground surface and not from the top of the surface vegetation layer. Previous accuracy assessments of DTM retrieval show their lowest random error of 0.12/0.19 m in unburned/burned tropical peat forest [15], 0.58 m in unburned tropical forest as a result of incomplete canopy penetration [45], and up to 0.26 m in densely vegetated wetlands [46]-values that are in some cases larger than the DoB estimates made in this study. We have no way of quantifying pre-burn DTM error in our study area because there were no control point measurements taken beneath vegetation at the time.…”

Section: Discussioncontrasting

confidence: 45%

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

et al. 2016

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Abstract:We provide the first assessment of tropical peatland depth of burn (DoB) using structure from motion (SfM) photogrammetry, applied to imagery collected using a low-cost, low-altitude unmanned aerial vehicle (UAV) system operated over a 5.2 ha tropical peatland in Jambi Province on Sumatra, Indonesia. Tropical peat soils are the result of thousands of years of dead biomass accumulation, and when burned are globally significant net sources of carbon emissions. The El Niño year of 2015 saw huge areas of Indonesia affected by tropical peatland fires, more so than any year since 1997. However, the Depth of Burn (DoB) of these 2015 fires has not been assessed, and indeed has only previously been assessed in few tropical peatland burns in Kalimantan. Therefore, DoB remains arguably the largest uncertainty when undertaking fire emissions calculations in these tropical peatland environments. We apply a SfM photogrammetric methodology to map this DoB metric, and also investigate combustion heterogeneity using orthomosaic photography collected using the UAV system. We supplement this information with pre-burn airborne light detection and ranging (LiDAR) data, reducing uncertainty by estimating pre-burn soil height more accurately than from interpolation of adjacent unburned areas alone. Our pre-and post-fire Digital Terrain Models (DTMs) show accuracies of 0.04 and 0.05 m (root-mean-square error, RMSE) respectively, compared to ground-based global navigation satellite system (GNSS) surveys. Our final DoB map of a 5.2 ha degraded peat swamp forest area neighboring Berbak National Park (Sumatra, Indonesia) shows burn depths extending from close to zero to over 1 m, with a mean (±1σ) DoB of 0.23 ± 0.19 m. This lies well within the range found by the few other studies available (on Kalimantan; none are available on Sumatra). Our combustion heterogeneity analysis suggests the deepest burns, which extend to~1.3 m, occur around tree roots. We use these DoB data within the Intergovernmental Panel on Climate Change (IPCC) default equation for fire emissions to estimate mean carbon emissions as 134 ± 29 t·C·ha −1 for this peatland fire, which is in an area that had not had a recorded fire previously. This is amongst the highest per unit area fuel consumption anywhere in the world for landscape fires. Our approach provides significant uncertainty reductions in such emissions calculations via the reduction in DoB uncertainty, and by using the UAV SfM approach this is accomplished at a fraction of the cost of airborne LiDAR-albeit over limited sized areas at present. Deploying this approach at locations across Indonesia, sampling a variety of fire-affected landscapes, would provide new and important DoB statistics for producing optimized carbon and greenhouse gas (GHG) emissions estimates from peatland fires.

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Section: Discussioncontrasting

confidence: 45%

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

et al. 2016

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“…For instance, [39] stated that the use of total station provided accuracy with an error of approximately 1 cm in horizontal position and about 2 cm in vertical position (elevation). The studies [40,41] used total station ground-truthed data to assess the accuracy of LiDAR, and [42] used it to assess the accuracy of GPS.…”

Section: Discussionmentioning

confidence: 99%

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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“…Hopkinson et al (2004) noted, "ground class point density was highly variable, however, with higher densities over open dry ground and lower densities over areas of dense canopy and wet ground. " Töyrä et al (2003) also noted this limitation for wetlands and omitted areas of water in their follow-up ground validation survey for this reason.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, this acquisition had a point density of 3 points per square meter to maximize ground return probability. Finally, while Töyrä et al (2003) conducted their LiDAR survey when vegetation was partially foliated the sensors maximum scan angle was 20° and the average flying height was 1300 m, allowing for point densities ranging from 0.25 to 0.08 points per square meter. Thus, average flying height and resultant point density, maximum scan angle and flight line overlap are crucial sensor parameters for reducing absolute error and ensuring proper terrain morphology in vegetated environments.…”

Section: Introductionmentioning

confidence: 99%

An evaluation of DEMs derived from LiDAR and photogrammetry for wetland mapping

Hogg¹,

Holland²

2008

The Forestry Chronicle

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The Ontario Ministry of Natural Resources (OMNR) and Ducks Unlimited Canada (DUC) have been engaged in developing an efficient and accurate methodology for inventorying wetlands. Their progress in this area has demonstrated that Digital Elevation Models (DEMs) are crucial input for wetland identification and boundary delineation. The provincial DEM, however, has known precision limitations in areas of minimal topographic relief that cause considerable mapping error. This study explored whether wetland mapping derived from bare-earth light detection and ranging (LiDAR) data would overcome the limitations of the provincial DEM. An automated wetland mapping approach was applied to the 2 elevation datasets and the results were compared using 2 methods of validation. One hundred aerial-photo-interpreted sample plots were used to quantitatively measure the ability of each source to separate upland from wetland. An overlay of wetland maps created from the 2 DEM sources was then qualitatively assessed to further clarify the magnitude of discrepancy between the 2 mapping sources. The study concluded that LiDAR showed a significant improvement at p = 0.05 over the provincial DEM for mapping wetlands, improving overall mapping accuracy from 76% to 84%. However, an overlay analysis and qualitative assessment showed the magnitude of this reported improvement is greater than was quantified by the accuracy assessment and that an assessment scheme with different sample units may further elucidate this discrepancy.Key words: LiDAR, DEM, wetland, mapping RÉSUMÉLe Ministère des Richesses naturelles de l'Ontario (MRNO) et Canards illimités Canada (CIC) ont entrepris le développe-ment d'une méthodologie efficace et précise d'inventaire des milieux humides. Les progrès enregistrés dans ce domaine indiquent que les modèles de numérisation de l'altitude (MNA) constituent un élément clé de l'identification des milieux humides et de leur cartographie. Le MNA provincial, cependant, a révélé des limites dans la précision des zones à relief peu accidenté qui ont entraîné d'importantes erreurs cartographiques. Cette étude a cherché à savoir si la cartographie des milieux humides dérivée des données de détection de la lumière et de calcul de la distance (LiDAR) sur zone dénudée pouvait permettre de pallier les limites du MNA provincial. Une approche automatisée de cartographie des milieux humides a été utilisée pour deux ensembles de données altimétriques et les résultats ont été comparés au moyen de deux méthodes de validation. Cent parcelles-échantillons interprétées à partir de photos aériennes ont été utilisées pour mesurer quantativement la capacité de chaque source à séparer les zones sèches des milieux humides. Une superposition des cartes de milieux humides produites à partir de deux sources de MNA a été par la suite évaluée qualitativement pour identifier plus en détail l'importance des différences entre les deux sources de cartographie. L' étude permet de conclure que le LiDAR a démontré une amélioration significative, p =. ...

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Assessment of airborne scanning laser altimetry (lidar) in a deltaic wetland environment

Cited by 44 publications

References 6 publications

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

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

An evaluation of DEMs derived from LiDAR and photogrammetry for wetland mapping

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