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Covid-19 and Mobility

Mapping the Mobility Change during Covid-19

In respond to COVID-19, Google has recently published a Community Mobility Report based on collected annonimized and aggregated mobility data from Google Maps users. Based on analyzing how people visits and length of stay at different places, Google reported the mobility change compared to a baseline in the last month. That report provides insights into what has changed in response to social distancing and other policies aimed at combating COVID-19. This visualization tries to geovisualize the most recent reports that describe movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential at county and state levels across the United States.

Sky View

Using Google Street View to map the openness of street canyons of Boston (Sky View Factor)

City streets are a focal point of human activity in urban centers. Citizens interact with the urban environment through its streetscape and it is imperative to, not only map city streetscapes, but quantify those interactions in terms of human well-being. Researchers now have access to fully digitized representation of streetscapes through Google Street View (GSV), which captures the profile view of streetscapes and, thus, shares equivalent viewing angles with those of the citizen. Here I present how to use Google Street View to quantify and map the openness of street canyons.

Mapping sun glare

Mapping sun glare (dazzling sun while driving) using Google Street View

Just to think about that every time you drive from West to East at the sunrise time or drive from East to West during sunset time, do you feel the dazzling sun blind your eyes and make driving super difficult? I guess many people want to know when and where the dazzling sun occurs. I got the idea to predict the occurrence of sun glare when I was in a meeting with Liberty Mutual in Boston. I then think about how to predict it. I have been using Google Street View images in urban applications for many years, my previous project is Treepedia is a good one. I then to realize Google Street View may be a perfect dataset for predicting and mapping the sun glare occurrence because the Google Street View images have similar view angles with drivers and those images are actually collected by cars. Here is the tutorial to show you how to predict and map the sun glare using Google Street View and deep learning.


Shade provision of Trees

Quantifying the shade provision of street trees using Google Street View and Building Height Model

It is important to assess the shading service provided by street trees. Traditionally, remote sensing data have been widely used to evaluate the amount of urban greenery. However, the two-dimensional cover information cannot fully reflect the shading service of street trees, because the top-down view satellite imagery cannot reflect how the solar radiation reaching the street canyons. Recently, I have developed a method based on Google Street View panorama and building height model to quantify the exact shade provision of street trees in Boston.

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