Integrated GIS software for computing landscape visibility metrics

Abstract

As an important component of the quality of the living environment, landscape is increasingly addressed in terms of its visual dimension. In contrast to the point‐like character of in situ observations and photographic analyses, the modeling of landscape visibility from digital data has the advantage of scanning geographical space in a systematic way. However, the tools currently available for visibility modeling are limited to the mapping of viewsheds. They require complementary operations for a complete landscape assessment, including direct and easy computation of landscape metrics. Furthermore, none of those tools integrates recent technical advances to better characterize the visible landscape by tangential vision (i.e., from ground level as opposed to vision by viewshed from above). Starting from this, PixScape software proposes to integrate a large set of functions for modeling landscape visibility while remaining interfaced with GIS software. This software can be used to perform a complete landscape assessment by computing a wide range of original landscape metrics. It performs tangential analysis in addition to viewshed analysis, which can produce more realistic outcomes. Because landscape visibility analysis over large areas implies significant computation time, the software also integrates a multi‐resolution process intended to speed up calculations while also taking into account the cognitive abilities of human vision.

Coupling crowd-sourced imagery and visibility modelling to identify landscape preferences at the panorama level

“…For a given photo, this consisted in (1) positioning a virtual observer at the pixel corresponding to the point of view using the geographic coordinates recorded in the file, (2) applying the visibility rays method to identify the visible pixels from the point of view (Fisher, 1996) and (3) computing visibility metrics for characterising landscape features. We used the open access PixScape software (Sahraoui, Vuidel, Joly, & Foltête, 2018; https://sourcesup.renater.fr/www/pixscape/fr.html) to carry out these three steps and to benefit from specific functions. PixScape provides visibility metrics based on the tangential approach (i.e.…”

“…A third group was applied to the geometry of the view, including the degree of openness (average and maximum distances) and three metrics for describing the texture of the visual scene: the Shannon index applied to the distribution of distances of the visibility rays, expressing the statistical variation of the view depth, the "depthline" to characterise the spatial variation of the view depth, and the "skyline" to measure the more or less jagged aspect of the horizon (a low value meaning a flat horizon). For the computational details of all these metrics, see Sahraoui et al (2018).…”

“…The use of visibility metrics to create an analytical representation of views is facilitated by userfriendly tools such as Pixscape (Sahraoui et al, 2018). While most visibility modelling approaches work by counting visible pixels, the tangential approach provided by this tool yields more realistic metrics of composition and geometry for representing the content of a photo.…”

On How Crowdsourced Data and Landscape Organisation Metrics Can Facilitate the Mapping of Cultural Ecosystem Services: An Estonian Case Study

“…We then performed a viewshed analysis, identifying the visible surface from the set of observation points, namely the geolocations of the selected photographs from each group of CESs (see Section 2.2) and for the same number of randomly selected locations, which serve as pseudo-absence data ( Figure 2). We used the PixScape software [49] on the European Digital Elevation Model (EU-DEM), version 1.1 [50] with the maximum visible distance and observer height set to 5 km and 1.6 m, respectively. The median LCI, hue homogeneity, and saturation homogeneity were calculated for each viewshed and compared between the actual (presence) and random (pseudo-absence) geolocations using Wilcoxon's rank-sum test with continuity correction (see Appendix A for details), implemented in the Exploratory software (Exploratory Inc. (Delaware US) Sacramento, CA, USA).…”

r.survey: a tool for calculating visibility of variable-size objects based on orientation

“…During recent decades, significant progress has been made to objectively quantify what is visible or not visible from certain observation locations. This process is known as viewshed analysis (Higuchi 1983), and many GIS tools have been developed for it (Domingo-Santos and Fernández de Villarán 2017, Sahraoui et al 2018, Fábrega-Álvarez and Parcero-Oubiña 2019.…”