Assessment of Errors Caused by Forest Vegetation Structure in Airborne LiDAR-Derived DTMs
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TLDR
The need for adequate ground control schemes to accompany any forest-based airborne LiDAR survey which require highly accurate DTMs is highlighted, particularly in relation to analysis of pre- and post-burn surface height maps used to quantify the combustion of organic soils.Abstract:
Airborne Light Detection and Ranging (LiDAR) is a survey tool with many applications in forestry and forest research. It can capture the 3D structure of vegetation and topography quickly and accurately over thousands of hectares of forest. However, very few studies have assessed how accurately LiDAR can measure surface topography under forest canopies, which may be important, for example, in relation to analysis of pre- and post-burn surface height maps used to quantify the combustion of organic soils. Here, we use ground survey equipment to assess digital terrain model (DTM) accuracy in a deciduous broadleaf forest, during both leaf-on and leaf-off conditions. Using the leaf-on LiDAR dataset we quantitatively assess vertical vegetation structure, and use this as a categorical explanatory variable for DTM accuracy. In the presence of leaf-on vegetation, DTM accuracy is severely reduced, with low-stature undergrowth vegetation (such as ferns) causing the greatest errors (RMSE > 1 m). Errors are lower under leaf-off conditions (RMSE = 0.22 m), but still of a magnitude similar to that reported for mean depths of burn in fires involving organic soils. We highlight the need for adequate ground control schemes to accompany any forest-based airborne LiDAR survey which require highly accurate DTMs.read more
Citations
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Accuracy Assessment of Point Clouds from LiDAR and Dense Image Matching Acquired Using the UAV Platform for DTM Creation
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TL;DR: In this article, the point densities of point clouds acquired photogrammetrically under leaf-off and leaf-on conditions were compared to those acquired under leafon conditions and uniformly covered ground of the entire study area.
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References
More filters
Review on determining number of Cluster in K-Means Clustering
TL;DR: Six different approaches to determine the right number of clusters in a dataset are explored, including k-means method, a simple and fast clustering technique that addresses the problem of cluster number selection by using a k-Means approach.
Journal ArticleDOI
Processing of laser scanner data-algorithms and applications
TL;DR: This paper presents some methods and algorithms concerning filtering for determining the ground surface, DEM, classification of buildings for 3D City Models and the detection of electrical power lines.
Journal ArticleDOI
Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests
TL;DR: In this paper, the capacity of current airborne and ground-based ranging systems to provide data from which useful forest inventory parameters can be derived is investigated and four contrasting study sites were established within an existing study area in the Bago and Maragle State Forests, New South Wales, Australia.
Journal ArticleDOI
Detection of individual tree crowns in airborne lidar data
TL;DR: In this paper, a method to automatically delineate single trees automatically in small footprint light detection and ranging (lidar) data in deciduous and mixed temperate forests is presented.
Journal ArticleDOI
Accuracy of a high-resolution lidar terrain model under a conifer forest canopy
TL;DR: In this article, a high-resolution digital terrain model (DTM) was produced from high-density lidar data, and the mean DTM error was 0.22 ± 0.24 m (mean ± SD).