<scp>viewshed3d</scp>: An <scp>r</scp> package for quantifying 3D visibility using terrestrial lidar data

Lecigne, Bastien; Eitel, Jan U. H.; Rachlow, Janet L.

doi:10.1111/2041-210x.13385

Cited by 26 publications

(31 citation statements)

References 17 publications

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“…The hazel grouse forest habitat, from the ground up to 10 m, were described by two different forest stand traits defined using MLS data: (1) the Plant Density Index (PDI) to estimate vegetation density at different point heights (Puletti et al, 2021), and (2) the percentage of Potential Hiding Refugees (PHR) assessed using R package (Lecigne et al, 2020).…”

Section: Methodsmentioning

confidence: 99%

“…The lower understory (LU, 0-5 m) voxel-grid were processed by viewsheds() function of R package to identify potential hiding refugees. This function allows to quantify the relative visibility of the environment by combining viewsheds from multiple, user-selected viewpoints into a single variable that estimates a cumulative viewshed (Lecigne et al, 2020).…”

Section: Methodsmentioning

confidence: 99%

“…Recent ecological studies based on viewshed ecology have used TLS data to understand and quantify the effect of vegetation on animal visibility (Lecigne et al, 2020). Based on these studies TLS allows ecologists to investigate vegetation structure and quantify patterns across heterogeneous and complex habitats and to move beyond two-dimensional measures.…”

Section: Introductionmentioning

confidence: 99%

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

Galluzzi

Puletti

Armanini³

et al. 2022

Preprint

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Galluzzi

Puletti

Armanini³

et al. 2022

Preprint

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“…Wheatley et al ., 2020). Terrestrial LiDAR (Light Detection and Ranging) scanning is one approach that could be used to create three‐dimensional images of vegetation structure pre‐ and post‐fire and assess changes in visibility at different scales (Olsoy et al ., 2015; Lecigne, Eitel & Rachlow, 2020). Additionally, we have focused on visual encounters between predators and prey themselves, but fire could also make it easier for predators to detect the signs of prey, such as their tracks or shelter sites, thus aiding hunting efficiency.…”

Section: Outstanding Questions and Future Directionsmentioning

confidence: 99%

Fire as a driver and mediator of predator–prey interactions

et al. 2022

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Both fire and predators have strong influences on the population dynamics and behaviour of animals, and the effects of predators may either be strengthened or weakened by fire. However, knowledge of how fire drives or mediates predatorprey interactions is fragmented and has not been synthesised. Here, we review and synthesise knowledge of how fire influences predator and prey behaviour and interactions. We develop a conceptual model based on predator-prey theory and empirical examples to address four key questions: (i) how and why do predators respond to fire; (ii) how and why does prey vulnerability change post-fire; (iii) what mechanisms do prey use to reduce predation risk post-fire; and (iv) what are the outcomes of predator-fire interactions for prey populations? We then discuss these findings in the context of wildlife conservation and ecosystem management before outlining priorities for future research. Fire-induced changes in vegetation structure, resource availability, and animal behaviour influence predator-prey encounter rates, the amount of time prey are vulnerable during an encounter, and the conditional probability of prey death given an encounter. How a predator responds to fire depends on fire characteristics (e.g. season, severity), their hunting behaviour (ambush or pursuit predator), movement behaviour, territoriality, and intra-guild dynamics. Prey species that rely on habitat structure for avoiding predation often experience increased predation rates and lower survival in recently burnt areas. By contrast, some prey species benefit from the opening up of habitat after fire because it makes it easier to detect predators and to modify their behaviour appropriately. Reduced prey body condition after fire can increase predation risk either through impaired ability to escape predators, or increased need to forage in risky areas due to being energetically stressed. To reduce risk of predation in the post-fire environment, prey may change their habitat use, increase sheltering behaviour, change their movement behaviour, or use camouflage through cryptic colouring and background matching. Field

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“…Despite its long history within GIS analysis, there has been little uptake of viewshed analysis within ecology. Recent work has called for the use of the approach within ecological research, demonstrating the utility of the method from the perspective of wildlife ecology (Aben et al., 2018; Lecigne et al., 2020). Here, we extend this call and recommend the use of viewsheds by forest ecologists and invasion biologists.…”

Section: Introductionmentioning

confidence: 99%

Combining laser rangefinder and viewshed technologies to improve ground surveys of invasive tree distributions

2021

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Quantifying the spatial extent, location and habitat associations of invasive tree species is critical to predict their future spread and prioritise areas for management. Species–environment relationship analyses are useful tools for understanding and predicting the potential geographical distribution of these species; however, such tools require rigorous and extensive data about species presence and, crucially, the area surveyed. Here, we describe a method for performing ground‐based visual surveys of invasive trees from a set of viewpoints that utilises laser rangefinder and global navigation satellite system (GNSS) technology to detect tree locations. We then highlight the novel use of geographical information system (GIS) viewsheds as a tool to define the area surveyed. Using the invasive conifer, Pinus radiata, as our target, we undertook a ground‐truthing exercise for 50 trees established in the wild to assess the accuracy of the method and determine the suitable spatial resolution for GIS data that would be used in subsequent species–environment relationship analyses. For these trees, location error was positively related to distance from the tree to the viewpoint. The calculated locations for all trees within 600 m of the observer were within 25 m of the location as determined by the GNSS unit, with a median location error of 4 m. These results indicate that data of a resolution suitable for mapping invasive trees can be efficiently collected over large areas. We also outline suggestions and instructions for computing the viewsheds to determine the surveyed area. This approach allows for efficient collection of accurate data on the occurrence of non‐native trees and the land area surveyed. These data can underpin species–environment relationship analyses that then form the basis of risk maps for areas prone to future invasion. Given the speed and accuracy with which data can be obtained using this method, and the use of standard and easily accessible field equipment and GIS software, we recommend this approach to other spatial and invasion ecologists.

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viewshed3d: An r package for quantifying 3D visibility using terrestrial lidar data

Cited by 26 publications

References 17 publications

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

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

Fire as a driver and mediator of predator–prey interactions

Combining laser rangefinder and viewshed technologies to improve ground surveys of invasive tree distributions

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