Google Street View: Capturing the World at Street Level

Computer ◽  
2010 ◽  
Vol 43 (6) ◽  
pp. 32-38 ◽  
Author(s):  
Dragomir Anguelov ◽  
Carole Dulong ◽  
Daniel Filip ◽  
Christian Frueh ◽  
Stéphane Lafon ◽  
...  
Keyword(s):  
Google Street View ◽  
Street Level ◽  
Street View ◽  
The World

scholarly journals Estimation of Mean Radiant Temperature in Urban Canyons Using Google Street View: A Case Study on Seoul

2022 ◽  
Vol 14 (2) ◽  
pp. 260
Author(s):  
Eun-Sub Kim ◽  
Seok-Hwan Yun ◽  
Chae-Yeon Park ◽  
Han-Kyul Heo ◽  
Dong-Kun Lee
Keyword(s):  
Heat Stress ◽  
Spatial Patterns ◽  
High Density ◽  
View Factor ◽  
Mean Radiant Temperature ◽  
Street Canyons ◽  
Google Street View ◽  
Street Level ◽  
Street View ◽  
Radiant Temperature

Extreme heat exposure has severe negative impacts on humans, and the issue is exacerbated by climate change. Estimating spatial heat stress such as mean radiant temperature (MRT) is currently difficult to apply at city scale. This study constructed a method for estimating the MRT of street canyons using Google Street View (GSV) images and investigated its large-scale spatial patterns at street level. We used image segmentation using deep learning to calculate the view factor (VF) and project panorama into fisheye images. We calculated sun paths to estimate MRT using panorama images from Google Street View. This paper shows that regression analysis can be used to validate between estimated short-wave, long-wave radiation and the measurement data at seven field measurements in the clear-sky (0.97 and 0.77, respectively). Additionally, we compared the calculated MRT and land surface temperature (LST) from Landsat 8 on a city scale. As a result of investigating spatial patterns of MRT in Seoul, South Korea, we found that a high MRT of street canyons (>59.4 °C) is mainly distributed in open space areas and compact low-rise density buildings where the sky view factor is 0.6–1.0 and the building view factor (BVF) is 0.35–0.5, or west-east oriented street canyons with an SVF of 0.3–0.55. However, high-density buildings (BVF: 0.4–0.6) or high-density tree areas (Tree View Factor, TVF: 0.6–0.99) showed low MRT (<47.6). The mapped MRT results had a similar spatial distribution to the LST; however, the MRT was lower than the LST in low tree density or low-rise high-density building areas. The method proposed in this study is suitable for a complex urban environment consisting of buildings, trees, and streets. This will help decision makers understand spatial patterns of heat stress at the street level.

scholarly journals Utilizing and Evaluating of Virtual Tours in Art Exhibition Amidst Global Pandemic

2021 ◽  
Vol 5 (2) ◽  
pp. 69-78
Author(s):  
Nur Muhammad Amin Hashim Amir ◽  
◽  
Aznan Omar ◽  
Hilal Mazlan ◽  
◽  
...  
Keyword(s):  
Art Exhibitions ◽  
Art Exhibition ◽  
Google Street View ◽  
Virtual Spaces ◽  
Advantages And Disadvantages ◽  
Street View ◽  
Global Pandemic ◽  
The World ◽  
Panoramic Images ◽  
Total Participation

Covid-19 has sojourned the world as we know then into a cessation. It affects various disciplinary fields to a standstill which includes art and tourism. In Malaysia, to adapt to the global pandemic; new opportunities have emerged and dealt with it no longer becomes optional but rather a solution. Therefore, this research is mainly focused on implementing virtual tours to cope with the new norms; and evaluates its implication specifically in showcasing art exhibitions. The researcher uses the concept of Google Street View to capture virtual spaces; combining with Pano2Vr software as constructing tools; for audiences to interact and discusses its usefulness based on their ease of accessibility. Through the usage of this software, the researcher was able to reconstruct the actual gallery into series of interconnected images that trajectories within a web hosting server which are accessible over various platforms. The researcher purposely uses 360 panoramic images to maintain the ingenuity and actuality of the exhibition surroundings; due to most audiences are more complacent to the practicality compared to 3D digital replication. The advantages and disadvantages of this particular application of Virtual Tours (VTs) are then assessed through data collected based on the accessed devices, accessed locations, and total participation to see whether this concept can be used as a new alternative tool in showcasing art exhibitions in the effort of avoiding the pandemic widespread while still keeping the art activity at a sensible pace.

Street-level: Google Street View’s abstraction by datafication

2017 ◽  
Vol 20 (3) ◽  
pp. 1201-1219 ◽  
Author(s):  
Aaron Shapiro
Keyword(s):  
Media Studies ◽  
Final Section ◽  
Algorithm Design ◽  
Google Street View ◽  
Street Level ◽  
Street View ◽  
Big Data Applications ◽  
Critical Media ◽  
Criminological Theories ◽  
Urban Places

While aerial photography is associated with vertical objectivity and spatial abstractions, street-level imagery appears less political in its orientation to the particularities of place. I contest this assumption, showing how the aggregation of street-level imagery into “big datasets” allows for the algorithmic sorting of places by their street-level visual qualities. This occurs through an abstraction by “datafication,” inscribing new power geometries onto urban places through algorithmic linkages between visual environmental qualities, geographic information, and valuations of social worth and risk. Though largely missing from media studies of Google Street View, similar issues have been raised in critiques of criminological theories that use place as a proxy for risk. Comparing the Broken Windows theory of criminogenesis with big data applications of street-level imagery informs a critical media studies approach to Google Street View. The final section of this article suggests alternative theoretical orientations for algorithm design that avoid the pitfalls of essentialist equations of place with social character.

Assessing street-level urban greenery using Google Street View and a modified green view index

2015 ◽  
Vol 14 (3) ◽  
pp. 675-685 ◽  
Author(s):  
Xiaojiang Li ◽  
Chuanrong Zhang ◽  
Weidong Li ◽  
Robert Ricard ◽  
Qingyan Meng ◽  
...  
Keyword(s):  
Google Street View ◽  
Street Level ◽  
Urban Greenery ◽  
Street View
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