(You technically could download the historical data if you know the pano id for the image. Unfortunately the automatic API only returns the most recent image – there is no way to return older imagery nor know the date-stamp of the current image. In my tests my IP got banned after around 100 images, but you can get a verified google account which allows 25,000 image downloads per day. Here is the 457 West Robinwood Street picture: "14214 Arlington Street, Detroit, Michigan 48212"]ĭropbox has a nice mosaic view for a folder of pictures, you can view all seven photos here. "3317 Cody Street, Detroit, Michigan 48212", "15414 Wabash Street, Detroit, Michigan 48238", "1520 West Philadelphia, Detroit, Michigan 48206",
Tests = ["457 West Robinwood Street, Detroit, Michigan 48203", Urllib.urlretrieve(MyUrl, os.path.join(SaveLoc,fi)) MyUrl = base + urllib.quote_plus(Add) + key #added url encoding Key = "&key=" + "" #got banned after ~100 requests with no key Myloc = r"C:\Users\andrew.wheeler\Dropbox\Public\ExampleStreetView" #replace with your own location I defaulted for the image to be 1200×800 pixels. This function takes an address and a location to download the file, then saves the resulting jpeg to your folder of choice. This ends up being abit simpler than my prior examples (such as the street distance API or the places API) because it just returns the image blob, no need to parse JSON.īelow is a simple example in python, using a set of addresses in Detroit that are part of a land bank. Using the Google Street View image API you can submit either a set of coordinates or an address and have the latest street view image returned locally. See for example Phil Cohen’s Family Inequality post in which he shows examples of auctioned houses in Detroit over time. I think it is just a cool source of data though to be honest.
TINY PLANET GOOGLE STREETVIEW CODE
It has been used in criminal justice applications as a free source for second hand systematic social observation by having people code aspects of disorder from the imagery (instead of going in person) ( Quinn et al., 2014), as estimates of the ambient walking around population ( Yin et al., 2015), and examining criminogenic aspects of the built environment ( Vandeviver, 2014). For a few projects I was interested in downloading street view imagery data.
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