Biology subjects

Puletti, N.

Publications and source records attributed to Puletti, N..

6 recordsLinked to original sources

bioRxiv2024

Streamlining the alignment of UAV and ULS forest point clouds: an approach based on ground and tree stems

Accurate co-registration of terrestrial and aerial point clouds may provide a high-resolution description of tree components for large forest areas. However, an automated approach for co-registering point clouds is still needed, given the challenges in geospatial data processing, particularly in complex topographical conditions. The main objective of this study is to present the application of a novel procedure for the co-registration of point clouds obtained from terrestrial and UAV surveys in Mediter-ranean forests.

bioinformatics↗

bioRxiv2023

TreeArchTraits: an R package to analyse the architectural traits of trees using TLS data

1O_LIThe architecture of trees is significantly influenced by their interactions, directly affecting their functioning and structural development. Different tree architectural indicators (TAT) have evolved, including these interactions measurements. C_LIO_LIRecent advances in Terrestrial Laser Scanning data collection make measuring the three-dimensional characteristics of trees more more efficient. C_LIO_LIThe R package TreeArchTraits facilitates the processing of three-dimensional tree characteristics obtained through Terrestrial Laser Scanning, enabling the computation of various indices. C_LIO_LIA set of trees belonging to different forest conditions was used to demonstrate the TreeArchTraits potential for characterizing tree architectures. C_LI O_FIG O_LINKSMALLFIG WIDTH=173 HEIGHT=200 SRC="FIGDIR/small/560266v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@9a6dc5org.highwire.dtl.DTLVardef@9cae28org.highwire.dtl.DTLVardef@6dcc9dorg.highwire.dtl.DTLVardef@946706_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2023

treespat:an R package for spatial tree diversity analysis

Forest structure is a key element in understanding functionality and resilience of forest ecosystems. Analyses of forest structure and diversity have traditionally employed non-spatial measures, due to the simplicity of such approach. However, spatial structure can provide a deeper understanding of tree patterns, but widespread use of a spatially-explicit approach has been often limited by the complexity of theoretical equations and formulas, and the lack of freely distributed tools to calculate such spatial indices. To fill this gap we created the R package treespat, which allows to calculate some of the most diffuse stand-level spatial diversity indices. The document describes theory, basic definition and example application for using the treespat package. O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/541683v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@b631f7org.highwire.dtl.DTLVardef@18a85dcorg.highwire.dtl.DTLVardef@15a5f84org.highwire.dtl.DTLVardef@35146e_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2023

crossing3dforest: an R package for evaluating empty space structure in forest ecosystems

O_LITraditionally, forest structure is mostly described by vegetative elements; however, the complementary empty space also contributes to the forest spatial structure. C_LIO_LIWe developed an R package (crossing3dforest) to support the entire processing of Terrestrial Laser Scanning point clouds to quantify the size, shape, and connectivity of empty spaces within the mid and low strata of forest stands, using an approach based on the percolation theory. The package functions, which are designed for step-by-step single stand analysis, can be executed sequentially in a pipeline. C_LIO_LIA case study is presented to demonstrate the crossing3dforest potentials for characterising the forest empty space architecture. TLS point clouds collected in ten different pure beech (Fagus sylvatica L.) stands, representative of five distinct forest management regimes, were analysed and characterised. C_LIO_LIThe adopted empty space approach can be integrated into forest structural analysis to identify animal-habitat associations and establish appropriate habitat structure for wildlife management. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=173 HEIGHT=200 SRC="FIGDIR/small/526548v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1235647org.highwire.dtl.DTLVardef@f56364org.highwire.dtl.DTLVardef@503ab9org.highwire.dtl.DTLVardef@13f8043_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2022

Mobile Laser Scanner understory characterization: an exploratory study on hazel grouse in Italian Alps

Forest vegetation structure assessment is a time expensive effort with traditional methods. The Mobile Laser Scanner (MLS) technology can greatly speed up field works, achieve detailed quantification of three-dimensional forest structure at detailed resolution and drive forest management to increase the conservation status of forests-specialist bird species. In this study, using Mobile hand-held Laser Scanner (MLS), we calculated a fine-scale vegetation density index (namely the Plant Density Index, PDI) to characterize the vertical structure of forest subcanopy (0-10 m). The collected MLS point clouds were used to estimate the abundance of Potential Hiding Refuges (PHR) for the hazel grouse (Tetrastes bonasia), a sedentary bird extremely sensitive to forest structure and composition. The study was carried out in 10 plots located in the Adamello Brenta Geopark (Southern Alps, Italy). The species was detected in 8 out of 18 transects in an uneven-aged spruce forest with a discontinuous tree cover. The PDI decreases as the height increases, showing greater value in the shrub and herbaceous layer while the upper values are represented by trees stems, and branches. Visibility analysis of lower understory, highlighted PHR mean value of 73.2% (sd = 9.2%). In our area, PDI and PHR revealed that the environmental factors for hazel grouse occurrence are forests with open habitats, understory vegetation, and good hiding opportunities. Our study is the first application that uses MLS derived parameters to describe the ecological niche of a grouse and we presented the surveyed area as "case report" of hazel grouse habitat.

ecology↗

bioRxiv2022

coveR: An R package for processing Digital Cover Photography images to retrieve forest canopy attributes

O_LIDigital Cover Photography (DCP) is an increasingly popular tool for estimating canopy cover and leaf area index (LAI). However, existing solutions to process canopy images are predominantly tailored for fisheye photography, whereas open-access tools for DCP are lacking. C_LIO_LIWe developed an R package (coveR) to support the whole processing of DCP images in an automated, fast, and reproducible way. The package functions, which are designed for step-by-step single-image analysis, can be performed sequentially in a pipeline, while also allowing simple implementation for batch-processing bunches of images. C_LIO_LIA case study is presented to demonstrate the reliability of canopy attributes derived from coveR in pure beech (Fagus sylvatica L.) stands with variable canopy density and structure. Estimates of gap fraction and effective LAI from DCP were validated against reference measurements obtained from terrestrial laser scanning. C_LIO_LIBy providing a simple, transparent, and flexible image processing procedure, coveR supported the use of DCP for routine measurements and monitoring of forest canopy attributes. This, combined with the implementability of DCP in many devices, including smartphones, micro-cameras, and remote trail cameras, can greatly expand the accessibility of the method also by non-experts. C_LI

plant biology↗