Assessment of Image-Based Point Cloud Products to Generate a Bare Earth Surface and Estimate Canopy Heights in a Woodland Ecosystem

Jensen, Jennifer; Mathews, Adam J.

doi:10.3390/rs8010050

Cited by 116 publications

(84 citation statements)

References 31 publications

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“…This well-known limitation of digital photogrammetry known as dead ground [29] is caused by the canopy obscuring the ground, resulting in significant omissions. Consistent with previous studies [39,40,46], our results revealed that the UAV-SfM technique is capable of capturing terrain over certain vegetated surfaces, such as sparse forests with large open areas, but does not function very well in forested areas with dense or closed canopies. This finding highlights the need for an accurate DTM from an alternative source to calculate canopy height with photogrammetric surface models in dense forest areas.…”

Section: Characterisation Of Forest Canopy Using the Uav-sfm Techniquesupporting

confidence: 80%

“…However, Jensen and Mathews [46] (RMSE = 1.24 m for Oak-Ash Juniper Savanah and closed canopy woodland using Hawkeye II UAV imagery) reported lower RMSE values for dominant height than ours. Puliti et al [38] also reported lower RMSE values for dominant height (RMSE = 0.72 m and relative RMSE = 3.5%), and basal area (RMSE = 4.49 m 2 /ha, relative RMSE = 15.4%).…”

Section: Estimation and Plot-level Validation Of Forest Structural Atcontrasting

confidence: 43%

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Evaluating the Performance of Photogrammetric Products Using Fixed-Wing UAV Imagery over a Mixed Conifer–Broadleaf Forest: Comparison with Airborne Laser Scanning

2018

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Unmanned aerial vehicles (UAVs) and digital photogrammetric techniques are two recent advances in remote sensing (RS) technology that are emerging as alternatives to high-cost airborne laser scanning (ALS) data sources. Despite the potential of UAVs in forestry applications, very few studies have included detailed analyses of UAV photogrammetric products at larger scales or over a range of forest types, including mixed conifer-broadleaf forests. In this study, we assessed the performance of fixed-wing UAV photogrammetric products of a mixed conifer-broadleaf forest with varying levels of canopy structural complexity. We demonstrate that fixed-wing UAVs are capable of efficiently collecting image data at local scales and that UAV imagery can be effectively utilized with digital photogrammetric techniques to provide detailed automated reconstruction of the three-dimensional (3D) canopy surface of mixed conifer-broadleaf forests. When combined with an accurate digital terrain model (DTM), UAV photogrammetric products are promising for producing reliable structural measurements of the forest canopy. However, the performance of UAV photogrammetric products is likely to be influenced by the structural complexity of the forest canopy. Furthermore, we highlight the potential of fixed-wing UAVs in operational forest management at the forest management compartment level, for acquiring high-resolution imagery at low cost. A future direction of this research would be to address the issue of how well the photogrammetric products can predict the actual structure of mixed conifer-broadleaf forests.

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Section: Characterisation Of Forest Canopy Using the Uav-sfm Techniquesupporting

confidence: 80%

Section: Estimation and Plot-level Validation Of Forest Structural Atcontrasting

confidence: 43%

Evaluating the Performance of Photogrammetric Products Using Fixed-Wing UAV Imagery over a Mixed Conifer–Broadleaf Forest: Comparison with Airborne Laser Scanning

2018

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“…Instead, the minimum elevation value point within each pixel was used to provide the best approximation of the terrain surface within vegetated areas, acknowledging that this can sometimes result in the extraction of false elevation values as a result of point scatter below the ground surface [29]. Vegetation filtering from the SfM-MVS datasets was not the focus of this study, but is an active area of research, e.g., [111][112][113]. If suitable vegetation filtering methods can be developed and easily applied to SfM-MVS datasets, it will greatly enhance the ability of SfM-MVS to accurately reconstruct ground topography in densely vegetated areas.…”

Section: Vegetationmentioning

confidence: 99%

Assessment of UAV and Ground-Based Structure from Motion with Multi-View Stereo Photogrammetry in a Gullied Savanna Catchment

Koci

Jarihani

Leon

et al. 2017

IJGI

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Abstract:Structure from Motion with Multi-View Stereo photogrammetry (SfM-MVS) is increasingly used in geoscience investigations, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via Unmanned Aerial Vehicle, 'UAV') and ground-based (via handheld digital camera, 'ground') SfM-MVS in modelling hillslope gully systems in a dry-tropical savanna, and to assess the strengths and limitations of the approach at a hillslope scale and an individual gully scale. UAV surveys covered three separate hillslope gully systems (with areas of 0.412-0.715 km 2 ), while ground surveys assessed individual gullies within the broader systems (with areas of 350-750 m 2 ). SfM-MVS topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate that UAV SfM-MVS can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., approximately 0.1 m resolution with 0.4-1.2 m elevation error), while ground-based SfM-MVS is more capable of quantifying gully morphology (e.g., approximately 0.01 m resolution with 0.04-0.1 m elevation error). Despite difficulties in reconstructing vegetated surfaces, uncertainty as to optimal survey and processing designs, and high computational demands, this study has demonstrated great potential for SfM-MVS to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in savanna landscapes and elsewhere.

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“…Vegetation filtering is still a significant challenge at this very fine scale and reduces our ability to automate DTM difference processing. Our approach was to use the topographic position of points in the cloud to identify ground points, however, other SfM studies have used a variety of methods to filter vegetation with no clear consensus on a superior workflow [27,51,52,67,77]. In our semi-arid shrubland study area, there is a distinct difference in color between the creosote/mesquite shrubs and the bare ground.…”

Section: Dtm Errorsmentioning

confidence: 99%

Fine-Resolution Repeat Topographic Surveying of Dryland Landscapes Using UAS-Based Structure-from-Motion Photogrammetry: Assessing Accuracy and Precision against Traditional Ground-Based Erosion Measurements

et al. 2017

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Structure-from-motion (SfM) photogrammetry from unmanned aerial system (UAS) imagery is an emerging tool for repeat topographic surveying of dryland erosion. These methods are particularly appealing due to the ability to cover large landscapes compared to field methods and at reduced costs and finer spatial resolution compared to airborne laser scanning. Accuracy and precision of high-resolution digital terrain models (DTMs) derived from UAS imagery have been explored in many studies, typically by comparing image coordinates to surveyed check points or LiDAR datasets. In addition to traditional check points, this study compared 5 cm resolution DTMs derived from fixed-wing UAS imagery with a traditional ground-based method of measuring soil surface change called erosion bridges. We assessed accuracy by comparing the elevation values between DTMs and erosion bridges along thirty topographic transects each 6.1 m long. Comparisons occurred at two points in time (June 2014, February 2015 which enabled us to assess vertical accuracy with 3314 data points and vertical precision (i.e., repeatability) with 1657 data points. We found strong vertical agreement (accuracy) between the methods (RMSE 2.9 and 3.2 cm in June 2014 and February 2015, respectively) and high vertical precision for the DTMs (RMSE 2.8 cm). Our results from comparing SfM-generated DTMs to check points, and strong agreement with erosion bridge measurements suggests repeat UAS imagery and SfM processing could replace erosion bridges for a more synoptic landscape assessment of shifting soil surfaces for some studies. However, while collecting the UAS imagery and generating the SfM DTMs for this study was faster than collecting erosion bridge measurements, technical challenges related to the need for ground control networks and image processing requirements must be addressed before this technique could be applied effectively to large landscapes.

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Assessment of Image-Based Point Cloud Products to Generate a Bare Earth Surface and Estimate Canopy Heights in a Woodland Ecosystem

Cited by 116 publications

References 31 publications

Evaluating the Performance of Photogrammetric Products Using Fixed-Wing UAV Imagery over a Mixed Conifer–Broadleaf Forest: Comparison with Airborne Laser Scanning

Evaluating the Performance of Photogrammetric Products Using Fixed-Wing UAV Imagery over a Mixed Conifer–Broadleaf Forest: Comparison with Airborne Laser Scanning

Assessment of UAV and Ground-Based Structure from Motion with Multi-View Stereo Photogrammetry in a Gullied Savanna Catchment

Fine-Resolution Repeat Topographic Surveying of Dryland Landscapes Using UAS-Based Structure-from-Motion Photogrammetry: Assessing Accuracy and Precision against Traditional Ground-Based Erosion Measurements

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