Tree Height Growth Measurement with Single-Scan Airborne, Static Terrestrial and Mobile Laser Scanning

Lin, Yi; Hyyppä, Juha; Kukko, Antero; Jaakkola, Anttoni; Kaartinen, Harri

doi:10.3390/s120912798

Cited by 22 publications

(15 citation statements)

References 31 publications

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“…According to such studies, tree height underestimation occurs because tree tops cannot be accurately determined in analogue aerial photographs of low spatial resolution and because terrain elevations (next to the tree) cannot be read because of dense crown canopies. The underestimation of tree heights also commonly occurs with other remote sensing methods, such as the most up-to-date LiDAR technology, whether it is the height estimation of individual trees (e.g., Falkowski et al 2006, Heurich 2008, Lin et al 2012, Hunter et al 2012 or of the mean stand heights (e.g., Naesset 2002b, Coops et al 2007, Hyyppä et al 2008. The underestimations of LiDAR-estimated individual tree heights reported by above-mentioned studies ranged from 0.43 to 1.20 m, whereas underestimations of LiDAR-estimated mean stand heights ranged up to 3.30 m. The magnitude of underestimation, i.e.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2015

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. Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution. Ann. For. Res. 58(1): 125-143.Abstract. Tree height is one of the more fundamental measurements in forest inventories. In addition to classical field measurements, tree height may be estimated by remote sensing methods, such as by photogrammetric measurements of aerial images. Since it has been found and generally accepted that the extraction of forest and tree data from classical analogue aerial photographs has certain limitations, especially in the densely canopied forests, the usefulness of photogrammetric-based forest inventory in many countries remains a controversial issue. Therefore, this paper focuses on investigating the possibility of applying digital photogrammetric method to estimate mean stand height. Photogrammetric stereo-measurements of tree height were conducted on colour infrared images of high spatial resolution (ground sample distance -GSD -of 30 cm and 10 cm) using a digital photogrammetric workstation. The height of each tree within 183 sample plots (14 subcompartments) were calculated as the difference between the tree top elevations determined with the aerial images and the corresponding tree bottom elevations determined from the digital terrain model. To compare the photogrammetric-and field-estimated mean stand heights, the mean plot heights were calculated for both photogrammetric and field estimates of tree heights. Repeated measurements using ANOVA testing did not reveal a statistically significant difference (p > 0.05) between the field-estimated and photogrammetric-estimated mean stand heights using the 30 cm and 10 cm GSD digital aerial images. Deviations of the mean stand heights estimated using the images of both spatial resolutions were similar to the field-estimated heights. Using the 30 cm images the deviations of the photogrammetrically estimated mean stand height amounted to 0.35 m (1.59%) on average, whereas using the 10 cm images the deviations amounted to 0.31 m (1.41%) compared to the field estimation. Therefore, it can be concluded that the 30 cm GSD aerial images allow for the photogrammetric measurement of mean stand heights with accuracy similar to 10 cm GSD aerial images. In addition, 30 cm GSD aerial images are more favourable financially since the same area of interest could be covered with a considerably smaller number of images than of the 10 cm GSD aerial images.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2015

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“…2, and the resulting "-par max " can be merged into the final-step classification. This can expand the applications of the framework into various studies on forest ecology, meteorology and management, in which the strategy of combining aerospace/aerial imagery or LiDAR data with TLS reference data is often used (Hopkinson et al, 2004;Lin et al, 2012;Heinzel and Koch, 2012).…”

Section: Framework Applicabilitymentioning

confidence: 99%

A comprehensive but efficient framework of proposing and validating feature parameters from airborne LiDAR data for tree species classification

Lin

Hyyppä

2016

International Journal of Applied Earth Observation and Geoinfor

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“…In fact, the theme of stop-and-go measurement mode has been proposed and applied in a variety of domains, such as for solar energy accumulation in Mars Rover exploration [11] and for simultaneous localization and mapping (SLAM) in robot navigation [12]. Specifically for MLS, data collections in the stop-and-go mapping mode have been utilized as the reference data for, e.g., the calibration of the low-cost mobile mapping system [8] and the assessment of the mapping performance of different MLS systems [13]. Meantime, it is worth mentioning that the stop-and-go mode did not stem only from the process of improving MLS by incorporating the opposite strengths of TLS.…”

Section: Introductionmentioning

confidence: 99%

Stop-and-Go Mode: Sensor Manipulation as Essential as Sensor Development in Terrestrial Laser Scanning

Lin

Hyyppä

Kukko

2013

Sensors

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This study was dedicated to illustrating the significance of sensor manipulation in the case of terrestrial laser scanning, which is a field now in quick development. In fact, this quickness was mainly rooted in the emergence of new sensors with better performance, while the implications of sensor manipulation have not been fully recognized by the whole community. For this technical gap, the stop-and-go mapping mode can be reckoned as one of the potential solution plans. Stop-and-go was first proposed to handle the low efficiency of traditional static terrestrial laser scanning, and then, it was re-emphasized to improve the stability of sample collections for the state-of-the-art technology of mobile laser scanning. This work reviewed the previous efforts of trying the stop-and-go mode for improving the performance of static and mobile terrestrial laser scanning and generalized their principles respectively. This work also analyzed its advantages compared to the fully-static and fully-kinematic terrestrial laser scanning, and suggested the plans with more automatic measures for raising the efficacy of terrestrial laser scanning. Overall, this literature review indicated that the stop-and-go mapping mode as a case with generic sense can verify the presumption of sensor manipulation as essential as sensor development.

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Tree Height Growth Measurement with Single-Scan Airborne, Static Terrestrial and Mobile Laser Scanning

Cited by 22 publications

References 31 publications

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

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

A comprehensive but efficient framework of proposing and validating feature parameters from airborne LiDAR data for tree species classification

Stop-and-Go Mode: Sensor Manipulation as Essential as Sensor Development in Terrestrial Laser Scanning

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