scholarly journals High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data

2017 ◽  
Vol 51 (12) ◽  
pp. 6999-7008 ◽  
Author(s):  
Joshua S. Apte ◽  
Kyle P. Messier ◽  
Shahzad Gani ◽  
Michael Brauer ◽  
Thomas W. Kirchstetter ◽  
...  
Keyword(s):  
Air Pollution ◽  
Big Data ◽  
High Resolution ◽  
Google Street View ◽  
Street View

scholarly journals Mapping Air Pollution with Google Street View Cars: Efficient Approaches with Mobile Monitoring and Land Use Regression

2018 ◽  
Vol 52 (21) ◽  
pp. 12563-12572 ◽  
Author(s):  
Kyle P. Messier ◽  
Sarah E. Chambliss ◽  
Shahzad Gani ◽  
Ramon Alvarez ◽  
Michael Brauer ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Mobile Monitoring ◽  
Land Use Regression ◽  
Google Street View ◽  
Street View

scholarly journals Fine-Scale Spatiotemporal Air Pollution Analysis Using Mobile Monitors on Google Street View Vehicles

2019 ◽  
Vol 115 (531) ◽  
pp. 1111-1124 ◽  
Author(s):  
Yawen Guan ◽  
Margaret C. Johnson ◽  
Matthias Katzfuss ◽  
Elizabeth Mannshardt ◽  
Kyle P. Messier ◽  
...  
Keyword(s):  
Air Pollution ◽  
Fine Scale ◽  
Google Street View ◽  
Street View

‘Big data’ for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts

2015 ◽  
Vol 63 ◽  
pp. 337-345 ◽  
Author(s):  
Li Yin ◽  
Qimin Cheng ◽  
Zhenxin Wang ◽  
Zhenfeng Shao
Keyword(s):  
Big Data ◽  
Google Street View ◽  
Street View

scholarly journals Parcel-based urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View

2017 ◽  
Vol 64 ◽  
pp. 215-228 ◽  
Author(s):  
Weixing Zhang ◽  
Weidong Li ◽  
Chuanrong Zhang ◽  
Dean M. Hanink ◽  
Xiaojiang Li ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Urban Land ◽  
Urban Land Use ◽  
Airborne Lidar ◽  
Land Use Classification ◽  
Google Street View ◽  
Street View

scholarly journals Proposal of System for Calculating Sky View Factor Using Google Street View

2021 ◽  
pp. 313-324
Author(s):  
Shoko Nishio ◽  
Fumiko Ito
Keyword(s):  
Big Data ◽  
View Factor ◽  
Panoramic Image ◽  
Original Image ◽  
Google Street View ◽  
Sky View Factor ◽  
Street View ◽  
Current Point ◽  
Extended Area ◽  
The Web

AbstractIn recent years, big data entered use in various fields. Google Street View (hereinafter called “GSV”) can be regarded as open big data, and its images can be obtained using API. The streets can be viewed 360° horizontally and 290° vertically from each point on the web. In addition to those, zooming up is available, and the viewpoint can be moved approximately 10 m forward or backward to/from the current point. The original image to provide the view is the panoramic image associated with the latitude and longitude information on the street consecutively at intervals of 10 m, and they exist as massive data on the web. We determine the area of the sky using these images from GSV. In this research, we calculate the sky view factor (hereinafter called “SVF”) in an extended area by defining the area of the sky with the SVF and utilizing the computer.

‘Big Data’: Pedestrian Volume Using Google Street View Images

2016 ◽  
pp. 461-469 ◽  
Author(s):  
Li Yin ◽  
Qimin Cheng ◽  
Zhenfeng Shao ◽  
Zhenxin Wang ◽  
Laiyun Wu
Keyword(s):  
Big Data ◽  
Google Street View ◽  
Street View
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