A Study on Visual Diversity of Japanese Residential Streetscapes

This study was conducted to find out the available visual diversity in Japanese residential streetscapes. The visual diversity occurs when the visual elements on streetscapes are different to each other. In this study, a field survey as a subjective method and the entropy as an objective method were used as measures of visual diversity. Data were collected from 80 residential streetscapes from four sites in the Saitama Prefecture, Japan. The sequential perspective views of streetscapes were analyzed for eight visual elements： shape of houses, shape of roofs, shape of windows, positions of the main openings of houses, availability of the ornaments on houses, height, color and the appearance of the boundary walls of premises to calculate the entropy. A field survey with multicultural subjects was used to find out the correlation between entropy and the human perception on the visual diversity. According to the results, the residential streetscapes displayed high diversity variations largely due to the shape of the roofs, shape of the windows and the appearance of the boundary walls of the premises. Moreover, the results concluded that the residential streetscapes at the study area are neither visually diverse nor visually uniform in considering the visual diversity aspect.

Current design guidelines’streetscape improvement for visual perception and walkability:A case study of Sejong City,Republic of Korea

This study explores how recent design guidelines have focused on the visual variety of streetscapes making them more attractive.To date,this topic has been one of the most challenging parts of constructing walkable streets.We evaluated the streetscape features of Sejong City,recently constructed as Republic of Korea’s new capital city,and investigated their relationships with design guidelines.Consequently,we identified three principal reasons related to the design guidelines for the visual monotony in the street produced by the most up-to-date design guidelines compared with an ordinary street.First,the design guidelines cannot restrict the construction of large-scale buildings on the street,hindering visual changes caused by the zoning ordinance regulations because zoning regulations took priority when it comes to urban planning and regulatory governance.Second,design standards intending for a consistent street wall of buildings,which were used only in regard to the street enclosure standard,produced less spatial diversity and indistinct building bases,presenting weak vertical articulation.Third,applying the uniform standards for each building created repetitive architecture despite design standards for visual variety,such as recessed top floors,arcades,and retail uses for the ground floors facing a street.

Exploring associations between streetscape factors and crime behaviors using Google Street View images

Understanding the influencing mechanism of the urban streetscape on crime is fairly important to crime prevention and urban management.Recently,the development of deep learning technology and big data of street view images,makes it possible to quantitatively explore the relationship between streetscape and crime.This study computed eight streetscape indexes of the street built environment using Google Street View images firstly.Then,the association between the eight indexes and recorded crime events was revealed with a poisson regression model and a geographically weighted poisson regression model.An experiment was conducted in downtown and uptown Manhattan,New York.Global regression results show that the influences of Motorization Index on crimes are significant and positive,while the effects of the Light View Index and Green View Index on crimes depend heavily on the socioeconomic factors.From a local perspective,the Pedestrian Space Index,Green View Index,Light View Index and Motorization Index have a significant spatial influence on crimes,while the same visual streetscape factors have different effects on different streets due to the combination differences of socioeconomic,cultural and streetscape elements.The key streetscape elements of a given street that affect a specific criminal activity can be identified according to the strength of the association.The results provide both theoretical and practical implications for crime theories and crime prevention efforts.

Importance and performance of streetscapes at a tourism destination in Indonesia:The residents’perspectives

The present study examined the importance and performance of streetscapes at a tourism destination in Makassar,Indonesia,from the residents’perspectives using the importance-performance analysis method.Thus,six attributes of the streetscapes in four segments of the old city district were identified and presented to 400 participants.The participants were then asked to rate the perception and preference of each attribute.Results of the attribute values were illustrated in a Cartesian diagram.Findings indicate notable discrepancies between the perceptions and preferences of the respondents.Thus,these attributes were inconsistent with their expectations.Moreover,the results showed that each segment should have different priorities for specific attributes to improve the performance of the streetscapes.Overall,such data can be used by stakeholders,such as tourism developers and government policymakers,to make appropriate and informed decisions that will improve the attractiveness of this tourism destination and increase the number of visitors.

Dense 3D surface reconstruction of large-scale streetscape from vehicle-borne imagery and LiDAR

Accurate and efficient three-dimensional(3D)streetscape reconstruction is the fundamental ability for an exploration vehicle to navigate safely and perform high-level tasks.Recently,remarkable progress has been made in streetscape reconstruction with visual images and light detection and ranging(LiDAR),but they have difficulties either in scaling and reconstructing large-scale outdoors or in efficient processing.To address these issues,this paper proposed an automatic method for incremental dense reconstruction of large-scale 3D streetscapes from coarse to fine at near real time.Firstly,the pose of vehicle is estimated by visual and laser odometry(VLO)and the state-of-the-art pyramid stereo matching network(PSMNet)is introduced to estimate depth information.Then,incremental dense 3D streetscape reconstruction is conducted by key-frame selection and coarse registration with local optimization.Finally,redundant and noise points are removed through multiple filtering,resulting good quality of dense reconstruction.Comprehensive experiments were undertaken to check the visual effect,trajectory pose error and multi-scale model to model cloud comparison(M3C2)based on reference trajectories and reconstructions provided by the state-of-the-art method,showing the precision,recall and F-score of sampling core points(SCPs)are over 80.42%,71.68%and 77.19%,respectively,which verified the proposed method.