A new approach to retrieve leaf normal distribution using terrestrial laser scanners

Leaf normal distribution is an important structural characteristic of the forest canopy. Although terrestrial laser scanners（TLS） have potential for estimating canopy structural parameters, distinguishing between leaves and nonphotosynthetic structures to retrieve the leaf normal has been challenging. We used here an approach to accurately retrieve the leaf normals of camphorwood（Cinnamomum camphora） using TLS point cloud data.First, nonphotosynthetic structures were filtered by using the curvature threshold of each point. Then, the point cloud data were segmented by a voxel method and clustered by a Gaussian mixture model in each voxel. Finally, the normal vector of each cluster was computed by principal component analysis to obtain the leaf normal distribution. We collected leaf inclination angles and estimated the distribution, which we compared with the retrieved leaf normal distribution. The correlation coefficient between measurements and obtained results was 0.96, indicating a good coincidence.

Applicability of an ultra-long-range terrestrial laser scanner to monitor the mass balance of Muz Taw Glacier,Sawir Mountains,China

Glacier mass balance is a key component of glacier monitoring programs. Information on the mass balance of Sawir Mountains is poor due to a dearth of in-situ measurements. This paper introduces the applicability of an ultra-long-range terrestrial laser scanner(TLS) to monitor the mass balance of Muz Taw Glacier, Sawir Mountains, China. The Riegl VZ?-6000 TLS is exceptionally well-suited for measuring snowy and icy terrain. Here, we use TLS to create repeated high spatiotemporal resolution DEMs, focusing on the annual mass balance(June 2, 2015 to July 25, 2016). According to TLS-derived high spatial resolution point clouds, the front variation(glacier retreat) of Muz Taw Glacier was 9.3 m. The mean geodetic elevation change was 4.55 m at the ablation area. By comparing with glaciological measurements, the glaciological elevation change of individual stakes and the TLS-derived geodetic elevation change of corresponding points matched closely, and the calculated balance was-3.864±0.378 m w.e.. This data indicates that TLS provides accurate results and is therefore suitable to monitor mass balance evolution of Muz Taw Glacier.

Usingvery long-range terrestriallaser scanner to analyze the temporal consistency of the snowpack distribution in a high mountain environment

This study demonstrated the usefulness of very long-range terrestrial laser scanning(TLS) for analysis of the spatial distribution of a snowpack, to distances up to 3000 m, one of the longest measurement range reported to date. Snow depth data were collected using a terrestrial laser scanner during 11 periods of snow accumulation and melting,over three snow seasons on a Pyrenean hillslopecharacterized by a large elevational gradient, steep slopes, and avalanche occurrence. The maximum and mean absolute snow depth error found was 0.5-0.6 and 0.2-0.3 m respectively, which may result problematic for areas with a shallow snowpack, but it is sufficiently accurate to determine snow distribution patterns in areas characterized by a thick snowpack. The results indicated that in most cases there was temporal consistency in the spatial distribution of thesnowpack, even in different years. The spatial patterns were particularly similar amongst thesurveys conducted during the period dominated by snow accumulation(generally until end of April), or amongst those conducted during the period dominated by melting processes(generally after mid of April or early May). Simple linear correlation analyses for the 11 survey dates, and the application of Random Forests analysis to two days representative of snow accumulation and melting periods indicated the importance of topography to the snow distribution. The results also highlight that elevation and the Topographic Position index(TPI) were the main variables explaining the snow distribution, especially during periods dominated by melting. The intra-and inter-annual spatial consistency of the snowpack distribution suggests that the geomorphological processes linked to presence/absence of snow cover act in a similar way in the long term, and that these spatial patternscan be easily identifiedthrough several years of adequate monitoring.

The importance of proleptic branch traits in biomass production of poplar in high-density plantations

Branch phenotypic traits determine tree crown architecture,which in turn governs leaf display,light interception,and biomass production.Sylleptic and proleptic branches are the obviously different branch phenotypes in the poplar crown.Many studies have focused on the influence of sylleptic branch numbers(SBN)on biomass production,but the research on the influence of proleptic branch phenotypes was only a few.To explore the relationship between proleptic branch traits and biomass generation production in a high-density poplar plantation,we investigated the branch phenotypic traits of three poplar genotypes,all of which have high survival rates in forests(>95%)and significantly different crown architecture and biomass performance in the high-density plantations(1667 stems ha−1).The plantation site was established in 2007.A terrestrial laser scanner was used to measure branch characteristics such as length,angle of origin and termination,and azi-muth angle.A hierarchical cluster analysis performed on branch characteristics showed that SBN,crown depth,and proleptic branch curvature(PBC)were clustered with bio-mass production and leaf area index(LAI).Among all of the monitored traits,PBC played the second most important role in biomass production after SBN and was significantly correlated with SBN,LAI,and biomass production.The positive correlation between PBC and SBN indicated that a larger PBC was associated with more sylleptic branches within the monitored genotypes planted in the high-density plantation,providing greater leaf area and biomass produc-tion.The results of this study will improve the identification of high-production poplar varieties for cultivation in high-density plantations for biofuel production.