The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning

Abstract

Airborne Laser Scanning (ALS), also known as Light Detection and Ranging (LiDAR) enables an accurate three-dimensional characterization of vertical forest structure. ALS has proven to be an information-rich asset for forest managers, enabling the generation of highly detailed bare earth digital elevation models (DEMs) as well as estimation of a range of forest inventory attributes (including height, basal area, and volume). Recently, there has been increasing interest in the advanced processing of high spatial resolution digital airborne imagery to generate image-based point clouds, from which vertical information with similarities to ALS can be produced. Digital airborne imagery is typically less costly to acquire than ALS, is well understood by inventory practitioners, and in addition to enabling the derivation of height information, allows for visual interpretation of attributes that are currently problematic to estimate from ALS (such as species, health status, and maturity). At present, there are two limiting factors associated OPEN ACCESSForests 2013, 4 519 with the use of image-based point clouds. First, a DEM is required to normalize the image-based point cloud heights to aboveground heights; however DEMs with sufficient spatial resolution and vertical accuracy, particularly in forested areas, are usually only available from ALS data. The use of image-based point clouds may therefore be limited to those forest areas that already have an ALS-derived DEM. Second, image-based point clouds primarily characterize the outer envelope of the forest canopy, whereas ALS pulses penetrate the canopy and provide information on sub-canopy forest structure. The impact of these limiting factors on the estimation of forest inventory attributes has not been extensively researched and is not yet well understood. In this paper, we review the key similarities and differences between ALS data and image-based point clouds, summarize the results of current research related to the comparative use of these data for forest inventory attribute estimation, and highlight some outstanding research questions that should be addressed before any definitive recommendation can be made regarding the use of image-based point clouds for this application.

Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution

“…Although the DTM has a specific high vertical accuracy (RMSE Z =0.04 m), its accuracy in forested areas may be lower. It is well known that the DTM of forested areas created with classic photogrammetric methods has a lower accuracy because of the ground being obscured by vegetation (Järndstedt et al 2012, White et al 2013. As it shown in Figure 2, the accuracy assessment of DTM was conducted based on 15 ground control points, and most of them (11) were located in non-forested areas.…”

“…The previously mentioned LiDAR technology, which uses laser pulses to penetrate the forest canopy to the ground, allows for the acquisition of dense and accurate ground elevation data. Therefore, the DTM generated from LiDAR data is of higher accuracy than the DTM generated from photogrammetric methods (Vega & St-Onge 2008, White et al 2013). However, the visual interpretation of forest attributes, such as tree species, health status, and maturity, cannot currently be estimated from LiDAR data (White et al 2013).…”

“…Therefore, the DTM generated from LiDAR data is of higher accuracy than the DTM generated from photogrammetric methods (Vega & St-Onge 2008, White et al 2013). However, the visual interpretation of forest attributes, such as tree species, health status, and maturity, cannot currently be estimated from LiDAR data (White et al 2013). To utilise the advantages of each method, the option to combine photogrammetry and LiDAR for forest inventory purposes has attracted the attention of many researchers (Popescu et al 2004, StOnge et al 2004, 2008, Holmgren et al 2008, Bohlin et al 2012, Nurminen et al 2013.…”

“…The same 'photoLiDAR' approach was later used by to estimate tree height growth. Currently, the only advantage of choosing photogrammetric DTM over LiDAR DTM is the lower image acquisition cost in relation to LiDAR data acquisition (White et al 2013). …”

Estimation of the Timber Quality of Scots Pine with Terrestrial Laser Scanning

“…Laser scanning-based applications have been widely studied (e.g., [5][6][7]) and are already in operational use [8][9][10][11][12]. Airborne laser scanning (ALS) has been used to estimate forest structural parameters from single trees (e.g., tree species, height (H), diameter-at-breast height (dbh) and volume (v)) to area levels (stand-level mean characteristics) [13][14][15][16][17].…”