Visibility Analysis Research Articles

More than words: a study on the visibility of hand gestures in public spaces

Hand gestures play an important role in human communication. Although the study of their repertoires and roles for past communities is a popular field of research, there has been no attempt so far to study their visibility during public events. The aim of this study was to determine the maximum number of people who could see hand gestures well enough to understand their meaning. Using gestures taken from ancient Roman rhetorical treatises, which we divided into three classes related to the detail of the gestures (fingers, hand, arm, or arms), we conducted a series of experiments to determine the maximum distance from which each class of gestures could be seen. We used the results, including regression analysis, to conduct visibility analyses for two case studies: one on the rostra on the Late Republican Forum Romanum in Rome; and the other on Pyramid No 3 in the centre of Late-Classical Mayan Tikal. We used the calculation of the areas where gestures were visible to estimate crowd sizes by drawing on crowd behaviour observation during contemporary public gatherings. They show not only how many people could have potentially seen the gestures, but also what percentage of the theoretically available space could have been occupied by people who had the potential to see them. According to the findings, only a little under half (44.8%) of the maximum possible audience were able to detect all types of gestures (various levels of detail) at the LR Roman Forum, while at Pyramid No 3 in Tikal, just a mere 16.7% were able to do so. We believe that the results presented and the methodology used can be applied to analyse any public space, regardless of place and time, thus providing a valuable tool to comprehend past public assemblies.

Multi-agent simulation of pedestrian activity in historic district

AbstractMulti-agent simulation has received a lot of attention in recent years as an emerging design method. To improve the accuracy of the simulation results, the authors provide an optimization scheme that combines multi-agent simulation and visibility graph analysis. Investigate how to improve forecasting accuracy through model optimization.

Using airborne lidar and machine learning to predict visibility across diverse vegetation and terrain conditions

Visibility analyses, used in many disciplines, rely on viewshed algorithms that map locations visible to an observer based on a given surface model. Mapping continuous visibility over broad extents is uncommon due to extreme computational expense. This study introduces a novel method for spatially-exhaustive visibility mapping using airborne lidar and random forests that requires only a sparse sample of viewsheds. In 24 topographically and vegetatively diverse landscapes across the contiguous US, 1000 random point viewsheds were generated at four different observation radii (125 m, 250 m, 500 m, 1000 m), using a 1 m resolution lidar-derived digital surface model. Visibility index – the proportion of visible area to total area – was used as the target variable for site-scale and national-scale modeling, which used a diverse set of 146 terrain- and vegetation-based 10 m resolution metrics as predictors. Variables based on vegetation, especially those based on local neighborhoods, were more important than those based on terrain. Visibility at shorter distances was more accurately estimated. National-scale models trained on a wider range of vegetation and terrain conditions resulted in improved R2, although at some sites error increased compared to site-scale models. Results from an independent test site demonstrate potential for application of this methodology to diverse landscapes.

Evaluation of the Spatial Quality of Apartments from Different Price Categories Using the Visibility Graph Analysis: A Case of Tirana, Albania

During the last decade, there has been massive growth in the construction of large residential complexes and apartment blocks in Tirana. Urban density is increasing due to the fact that traditional low-story villas are demolished, and the space of the former private gardens is used for the new construction with high built ratio. The public areas which are adequate for such dense cities are not provided and therefore residents have a tendency to spend more time indoors. This research aims to evaluate the spatial qualities of the newly constructed 3+1 apartments using the Space Syntax visibility graph analysis (VGA). VGA allows to compare the overall exposure of the room, to estimate its level of privacy and control and to check if it is suitable for the assigned function. Analysis is performed for the apartments of different price levels in order to find the influence of price to the design quality and residential comfort. The results show that the degree of separation of the public and private domains corresponds to an increase in the price of the apartment. The visual exposure of the hall is higher in comparison with the living room, which facilitates the movement towards the individual rooms without interaction with the other family members.

Senorady/Mohelno – ‘Boleniska’: A strategic position within the landscape with palimpsest of prehistoric occupation

The landscapes of the Mohelno settlement microregion are mostly gently undulating, but also dissected by two deeply incised river valleys – the Oslava River valley in the north and the Jihlava River valley in the south. The western boundary is formed by Zelený kopec (491 m above sea level, while the eastern boundary is marked by Biskoupský kopec (397.3 m above sea level) and Vodanský kopec (397.5 m above sea level). This microregion was settled at different intensities during the whole duration of prehistory. The ‘Boleniska’ elevation is located in the central part of the microregion and forms a strategic point – the entire microregion is visible from this elevation. This elevation comprise of an occupational palimpsest with intensive occupation during three different periods: at the beginning of the Upper Paleolithic (probably more than one techno-complex), the Late Neolithic (Lengyel culture) and at the end of the Eneolithic period (Bell Beaker culture). There is a high density of sites in this microregion from all three periods of interest. A similar settlement pattern (similar topography and cultural sequences) is known from other Moravian microregions. A preliminary testing of the site’s spatial distribution and a visibility analysis support the hypothesis indicating Mohelno – ‘Boleniska’ as a central site within the entire microregion only in the Paleolithic. The number of similar palimpsests composed of Paleolithic, Neolithic and Eneolithic sites is low within the entire microregion and the interpretation of this phenomenon must also take into consideration climatic factors, subsistence strategies, and socio-economic conditions in future research.

An integrated image visibility graph and topological data analysis for extracting time series features

A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular techniques, one from the persistence diagram, a summary of topological data analysis, and another from the visibility graph, a popular approach for constructing complex networks. We further present a method for extracting features from time series by transforming the series into a two-dimensional array and applying a 2-dimensional visibility graph. The 2-dimensional visibility graph improves the quality of the features for clustering. The features extracted from the techniques are utilized for clustering 1100 time series samples simulated from 11 classes. The two clustering quality evaluation metrics namely normalized mutual info score and adjusted rand score, which are scores given to clustering algorithms, are used to measure the clustering quality. Inclusion of 2-dimensional visibility graph features increases the values of these metrics for classifying the time series. Therefore, the results confirm the usefulness of including a 2-dimensional visibility graph from time series clustering and analysis.

A Review of Cityscape Research Based on Dynamic Visual Perception

Dynamic visual experience is the most common way for people to perceive a cityscape. Previous research reviews on cityscapes have mainly focused on spatial planning, social culture, economic development, ecological protection, etc., with little consideration of the impact of dynamic visual perception on the formation of cityscapes, which hinders the provision of references for the practice of people-centered urban design concepts. Therefore, this article selected 94 works in the relevant literature from 1940 to 2022 to conduct a critical review. First, we conceptualized the cityscape in light of earlier substantial discussions on the intimate relationship between dynamic visual perception and the cityscape. Then, we divided the relevant research from the past century and a half into three periods and summarized theoretical and practical research on the cityscape in these different periods from the perspective of dynamic visual perception. Among these, the refined research on interdisciplinary methods, including Visual Quality Assessment based on dynamic visual perception and visibility analysis algorithms based on digital technology, is emphatically described and discussed. Based on a comprehensive review, this article concludes that the main application scenarios for the existing research on dynamic visual perception are cityscape assessment and decision making. Finally, three avenues for future research are proposed.

Calculating and Mapping the Naturalness of Peri-Urban Greenways

Peri-urban forests often have extensive greenway networks that allow for outdoor recreation. However, information associated with these greenways often does not include their degree of naturalness, which is usually reduced to descriptions of the flora and fauna and often overlooks the factors that reduce naturalness. Therefore, in some cases, the naturalness of these greenways is lower than expected. Quantifying their naturalness would be helpful, especially for hikers interested in appreciating and enjoying nature. Additionally, this information would help outdoor recreation managers to design trails or decide which ones to promote as “greenways”. The objectives of this study are (1) to design a method to calculate and map the naturalness of greenways using two approaches, one based on perceptual fieldwork and the other on geographic information systems (GIS); (2) to apply the designed method to a specific greenway; and (3) to compare both methodological approaches. The results show that, for the greenway studied, the naturalness scores obtained are low in all three types of analyses used. Around 70% of the greenway sections in the GIS visibility analysis and 80% in the GIS proximity analysis have a low naturalness index. In comparison, this value is reduced to 40% with the fieldwork analysis. Although the results of the GIS approach (proximity and visibility) generate naturalness indices and spatial patterns that are very similar, they differ significantly from those derived from the fieldwork analysis. The discussion of the results suggests that the three methodologies used are valid for analyzing the degree of naturalness of the trails. However, if used together, it could add flexibility to the type of variables incorporated in the analysis.

Investigation of Spatial and Cultural Features in Contemporary Qatari Housing

Housing is a basic human need and a fundamental component of settlement status. The architectural form and spatial provisions of housing evolve in line with—and transform to meet—a specific era’s needs. Globalization has been responsible for changing the nature of housing in Qatar over the last thirty years. It has led to a standardization of construction methods and built form, representing a dramatic departure from past models of vernacular residential architecture. In light of these challenges, the ultimate purpose of this study is to explore the spatial and cultural features in a small sample of contemporary housing in Qatar. It explores the spatial layout of four Qatari residential villas to assess the social and cultural roles in contemporary housing models against the background of previous research. In the study, the authors utilized space syntax as an analytical tool to demonstrate patterns of visibility and room relations in the samples to understand occupants’ system of activities in the contemporary domestic setting, deploying visibility graph analysis (VGA) and relational graphs. Key findings include the interpretation of the probable relation to socio-cultural factors such as gender roles, hospitality, and privacy. Hence, this study fills gaps in knowledge about Qatari and Middle Eastern housing today.

Towards urbanistic geosituation delineation

Introduction. Modern cities are complex and rapidly expanding systems. For their more effective study, it is necessary to use methods of urban remote sensing, in particular, LiDAR survey. Processed LiDAR survey data, visualized in a 3D scene, model a certain urban configuration that represents a static picture of the relationships between objects, processes and phenomena in the urban environment. The representation of such configurations in the dynamic plane are urbanistic geosituations. The main research objective of the paper is to define the concept and present the essence of the urbanistic geosituation. Results. The urbanistic geosituation is a dynamic aspect of a certain state of the urban environment, in which there are objects, processes and phenomena that are in dialectical unity with this urban environment. The urbanistic geosituation can be represented as a separate area of the urban environment in a certain research context with a specific state that is currently not inherent in other areas. The article describes in detail the property of the structural heredity of geosituations, which can be traced during the growth of cities. New buildings and roads are laid out taking into account the existing layout, thus inheriting the structure of the original geosituations. On the example of the city of Washington using 2D and 3D maps, the article discusses the features of identifying inherited urbanistic geosituations using the general functionality of visual analysis. On the example of the city of Kharkiv are described urban problems that arise as a result of unplanned development and ignoring the structural heredity of urbanistic geosituations. Repeating geosituations with common properties and internal configurations are combined into different rank geosituational patterns, which are tracked on city maps with the naked eye. The higher the rank of the pattern, the more stable it is, and the larger territories it covers in terms of more generalized properties. The formation of geosituations patterns is successfully combined with the feature of collecting and storing LiDAR data, which are divided into many areas of the same size – tiles. An important property of urbanistic geosituations is their variability, which manifests itself in the city study in the context of the daily population concentration. Diverse internal urban processes and phenomena often lead to the emergence of urbanistic geosituations that characterize the temporary gravity centers of the population. To search, identify and analyze urbanistic geosituations, it is necessary to use two key components – global coverage maps and geographic information systems (GIS). The article describes a special web-GIS that combines these components and provides an environment for exploring urbanistic geosituations in a 3D scene. Three use-cases are also proposed for analyzing urban systems at the geosituational level: visibility analysis, buildings energy consumption estimation, and population estimation [11, 21]. Conclusions. The geosituational approach in urban research can significantly improve the urban environment study. The repeatability of urban geosituations and the small data sets that can be obtained using LiDAR surveys provide grounds for their effective analysis and visualization in GIS, as a result of which it is possible to extract urban geosystem properties that can be relevant for the entire city.

Geometric-Based Method for Regional-Target Coverage Analysis

This study proposes a geometric-based method of providing regional target visibility from a satellite considering the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$J_2$</tex-math></inline-formula> perturbation. First, the basic mathematical model is introduced followed by the field-element equations for ground-point visibility analysis and envelope equations of a family of curves. Then, the concept of a regional-field-mapping envelope and its subset baseline field-mapping envelope are presented for calculating visible intervals. The envelopes transform the complex problem of calculating a visible interval into a simple intersection problem for a group of parallel lines representing a satellite's trajectory and the regional-field-mapping envelope. Based on the analytical partial differential of the field-element equations, the baseline-field-mapping envelope for smooth and non-smooth field of views can be rapidly calculated where the regional-field-mapping envelope can be obtained by splicing the baseline-field-mapping envelopes. The simulation results show that the proposed method is rapid, accurate, and intuitive, demonstrating its wide applications for regional-target coverage analysis.

Visibility Graph Analysis of the Seismic Activity of Three Areas of the Cocos Plate Mexican Subduction Where the Last Three Large Earthquakes (M > 7) Occurred in 2017 and 2022.

The understanding of the dynamical behavior of seismic phenomena is currently an open problem, mainly because seismic series can be considered to be produced by phenomena exhibiting dynamic phase transitions; that is, with some complexity. For this purpose, the Middle America Trench in central Mexico is considered a natural laboratory for examining subduction because of its heterogenous natural structure. In this study, the Visibility Graph method was applied to study the seismic activity of three regions within the Cocos plate: the Tehuantepec Isthmus, the Flat slab and Michoacan, each one with a different level of seismicity. The method maps time series into graphs, and it is possible to connect the topological properties of the graph with the dynamical features underlying the time series. The seismicity analyzed was monitored in the three areas studied between 2010 and 2022. At the Flat Slab and Tehuantepec Isthmus, two intense earthquakes occurred on 7 and 19 September 2017, respectively, and, on 19 September 2022, another one occurred at Michoacan. The aim of this study was to determine the dynamical features and the possible differences between the three areas by applying the following method. First, the time evolution of the a- and b-values in the Gutenberg-Richter law was analyzed, followed by the relationship between the seismic properties and topological features using the VG method, the k-M slope and the characterization of the temporal correlations from the γ-exponent of the power law distribution, P(k) ∼ k-γ, and its relationship with the Hurst parameter, which allowed us to identify the correlation and persistence of each zone.

Visibility Analysis and Time Series Forecasting

Visibility prediction and time series forecasting are two important fields in the domain of data analysis and machine learning. Visibility prediction deals with the estimation of atmospheric visibility or the distance over which objects can be clearly seen in a particular location, while time series forecasting involves predicting future values based on historical data. Both these fields have a wide range of applications, including transportation safety, air quality monitoring, and renewable energy management. However, the current prediction of visibility is mostly based on the numerical prediction method similar to the weather prediction [1]. In the present study the authors proposed a method using XGBoost(Extreme Gradient Boosting) and Unsupervised Models(ARIMA, ARMA, LSTM) models to build a weather visibility prediction system. The results obtained were very close to actual dataset.

Hybrid quantitative mesoscale analyses for simulating pedestrians’ visual perceptions: Comparison of three New York City streets

To improve pedestrians’ wellbeing and walkability in urban environments, designs must address a range of factors. To enhance such designs, spatial assessments of urban attributes are important, as they may contribute to our understanding of the impact of the urban setting on peoples’ perceptions when traversing these areas. This research proposes a novel hybrid tool for conducting mesoscale analyses that enables the capturing of parameters that influence pedestrians’ visual perceptions, and in turn, generates opportunities for examining specific urban attributes. Such analysis is based on empirical, data-driven methodologies, bridging the gap between microscale and macroscale evaluations. A comparative analysis of three walkable New York City case studies is conducted to demonstrate the hybrid analysis tool, that is comprised of three models: dynamic visibility analysis for predicting perceived density (DVA-D); dynamic visibility analysis for predicting potential interactions with the defining street facades (DVA-I); and dynamic enclosure street section analysis (DESSA). Combined, these models simulate the pedestrians’ perceptions of the urban scape. While all three environments are similarly ranked in Walk Score®, they inherently differ in their perceived density, potential interactions, and enclosure. The hybrid assessment highlights the physical urban attributes of each case study with regards to pedestrians’ visual perception. The readability and visibility of this analysis results may provide architects, urban planners, and stakeholders with a valuable tool for urban decision-making.

Sustainable Application of Automatically Generated Multi-Agent System Model in Urban Renewal

As cities expand, many old towns face the threat of being renovated or demolished. In recent years, the drawbacks of extensive urban renewal have become increasingly apparent, and the focus of urban development is gradually shifting from efficiency to quality. This study aims to combine urban renewal with emerging technologies to address the dilemma between efficiency and quality in urban renewal. The study found that algorithm models based on graph theory, topology, and shortest path principles neglect the influence of internal states and visual features on pedestrian activity, resulting in lower simulation accuracy. Although incorporating internal states and visual features into the core of the algorithm further improved the simulation accuracy, the model operates in a 3D environment with lower efficiency. To address the problems of insufficient simulation accuracy and low efficiency, this study proposes a dynamic pedestrian activity model based on a multi-agent system and incorporating visual features. The model simulates pedestrian daily activity paths using pheromones and virtual sensors as the core, and it was found that using Visibility Graph Analysis could accurately divide pheromones in the environment, thus obtaining more accurate simulation results. Subsequently, based on the optimized pedestrian model’s agent activity rules and dynamic pheromone theory, a model for automatically generating road paving in urban renewal projects was developed, and the generated results were verified for their rationality through design practice. This technology can effectively promote urban renewal and the preservation of historic neighborhoods, providing technical support for achieving sustainable urban development.

Simulation of the circulation complexity in student residence buildings using space syntax analyses (Case studies: Highland hall, Rita Atkinson, Rutgers University and Tooker Residences, USA)

ABSTRACT Investigating the spatial configuration can effectively interpret the circulation of an architectural plan layout. Student residences are among the most critical but neglected buildings in which the circulation system plays a vital role in efficient orientation and wayfinding. This study seeks to simulate and quantitatively assess the complexity of circulation spaces in student residence buildings in four different plan layouts. Space syntax analyses include the visual integration and connectivity drawn from Visibility Graph Analysis (VGA) maps for accessibility assessment, intelligibility calculated through all-line axial maps for wayfinding assessment, the field of view from the isovist map for visibility assessment, and agent-based analysis from the VGA map for the overall flow of occupants. Results revealed the strength and weaknesses of each layout. They indicated that the courtyard-shaped and figure-eight-shaped layouts could satisfy the highest degree of circulation efficiency. At the same time, the U-shaped and double-L-shaped plans had the weakest circulation. The study concludes by highlighting the practical implications for future strategies and the importance of syntactical analysis in the early stages of design.

Visibility Graph Analysis of Heartbeat Time Series: Comparison of Young vs. Old, Healthy vs. Diseased, Rest vs. Exercise, and Sedentary vs. Active.

Using the visibility graph algorithm (VGA), a complex network can be associated with a time series, such that the properties of the time series can be obtained by studying those of the network. Any value of the time series becomes a node of the network, and the number of other nodes that it is connected to can be quantified. The degree of connectivity of a node is positively correlated with its magnitude. The slope of the regression line is denoted by k-M, and, in this work, this parameter was calculated for the cardiac interbeat time series of different contrasting groups, namely: young vs. elderly; healthy subjects vs. patients with congestive heart failure (CHF); young subjects and adults at rest vs. exercising young subjects and adults; and, finally, sedentary young subjects and adults vs. active young subjects and adults. In addition, other network parameters, including the average degree and the average path length, of these time series networks were also analyzed. Significant differences were observed in the k-M parameter, average degree, and average path length for all analyzed groups. This methodology based on the analysis of the three mentioned parameters of complex networks has the advantage that such parameters are very easy to calculate, and it is useful to classify heartbeat time series of subjects with CHF vs. healthy subjects, and also for young vs. elderly subjects and sedentary vs. active subjects.

Landslide Identification in Human-Modified Alpine and Canyon Area of the Niulan River Basin Based on SBAS-InSAR and Optical Images

Landslide identification in alpine and canyon areas is difficult due to the terrain limitations. The main objective of this research was to explore the method of combining small baseline subset interferometric synthetic aperture radar (SBAS-InSAR), multi-temporal optical images and field surveys to identify potential landslides in the human-modified alpine and canyon area of the Niulan River in southwestern China based on terrain visibility analysis. The visibility of the terrain is analyzed using the different incident and heading angles of the Sentinel satellite’s ascending and descending orbits. Based on the SAR image data of Sentinel-1A satellites from 2016 to 2019, the SBAS-InSAR method was used to identify landslides, and then multi-temporal optical images were used to facilitate landslide identification. Field surveys were carried out to verify the identification accuracy. A total of 28 landslides were identified, including 13 indicated by SBAS-InSAR, 8 by optical imaging and 7 by field investigation. Many landslides were induced by the impoundment and fluctuation of reservoir water. The comparison and verification of typical landslide monitoring data and reservoir water fluctuations revealed that a sudden drop of reservoir water had a great influence on landslide stability. These research results can facilitate a comprehensive understanding of landslide distribution in the reservoir area and guide the follow-up landslide risk management.

Market With Visibility Graph Analysis Method in Palmerah Central Jakarta

Visibility is an important element in commercial spaces. However, the importance of visibility in traditional markets–especially in Indonesia–are often overlooked during the design process. One of the markets with this problem is Palmerah Market in Central Jakarta. Palmerah Market is an intriguing topic for architecture research since Palmerah Market has three different functions in one building, such as traditional market, modern supermarket, and auto parts center. Yet, the elements that are supposed to be Palmerah Market’s potential is not operating the way it’s supposed to. This is a result of low visibility and low permeability to each of the market’s zones. This research uses a qualitative method. The data will be analyzed using space syntax theory specifically Visibility Graph Analysis (VGA), that will be simulated through depthmapX software. Visibility Graph Analysis is one of the innovative methods to resolve architectural problems such as visibility. Since visibility can be relative from person to person, it is important to have an indisputable instrument to prove the best visibility value. Visibility Graph Analysis can greatly help on the matter of visibility in the design stage. As a result, this instrument can improve future architectural designs innovatively and have a positive impact on the environmental aspect surrounding the design. The research output will be completed as a design concept of Palmerah Market that solves the design issues related to visibility, accessibility, as well as function. The simulation result has shown that there are several areas in the proposed floor plans that has high visibility points, and thus can be optimized as the main commerce area. Whereas areas with low visibility can be operated for the supporting facilites, such as service area.

TheK−MSlope: A Potential Supplement forb-Value

AbstractThe b-value of the Gutenberg–Richter law describes the relationship of size and frequency distribution of earthquakes. Its variations may be related to stress state, hence has been used for short-term earthquake forecasting. However, estimation of b-value faces many uncertainties, making it difficult to interpret b-value changes as tectonic signals or statistical artifacts. Some recent studies have suggested that the b-values of some seismic catalogs are proportional to the K−M slope (KMS) obtained from the visibility graph analysis. If confirmed, the KMS may provide additional constraints to the b-value and its variations. In this study, we used synthetic seismic catalogs that obey various probability distributions to demonstrate that the proportional relationship between KMS and b-value is universal and stable, and that the KMS/b ratio is dependent on the catalog size. We found that the KMS estimation can perform better than the commonly used b-value estimation methods, especially when the catalogs are incomplete or have variations in the magnitude–frequency relations. We proposed an improved KMS method to ensure that the KMS value provides pure magnitude information and is not affected by the occurrence time or orders of the events. We used the KMS to estimate the spatiotemporal variations of b-value in the northeastern Tibetan plateau; the results are consistent with those derived from traditional b-value estimation methods. We suggest that the KMS can be used as a verification of or a supplement to the b-value.