Generative Street Addresses from Satellite Imagery
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MIT Media Lab, 75 Amherst St, Cambridge, MA 02139, USA
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ISPRS Int. J. Geo-Inf. 2018, 7(3), 84; https://doi.org/10.3390/ijgi7030084
Received: 9 January 2018
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Revised: 13 February 2018
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Accepted: 17 February 2018
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Published: 8 March 2018
(This article belongs to the Special Issue Machine Learning for Geospatial Data Analysis)
We describe our automatic generative algorithm to create street addresses from satellite images by learning and labeling roads, regions, and address cells. Currently, 75% of the world’s roads lack adequate street addressing systems. Recent geocoding initiatives tend to convert pure latitude and longitude information into a memorable form for unknown areas. However, settlements are identified by streets, and such addressing schemes are not coherent with the road topology. Instead, we propose a generative address design that maps the globe in accordance with streets. Our algorithm starts with extracting roads from satellite imagery by utilizing deep learning. Then, it uniquely labels the regions, roads, and structures using some graph- and proximity-based algorithms. We also extend our addressing scheme to (i) cover inaccessible areas following similar design principles; (ii) be inclusive and flexible for changes on the ground; and (iii) lead as a pioneer for a unified street-based global geodatabase. We present our results on an example of a developed city and multiple undeveloped cities. We also compare productivity on the basis of current ad hoc and new complete addresses. We conclude by contrasting our generative addresses to current industrial and open solutions.
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Keywords:
road extraction; remote sensing; satellite imagery; machine learning; supervised learning; generative schemes; automatic geocoding
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MDPI and ACS Style
Demir, İ.; Hughes, F.; Raj, A.; Dhruv, K.; Muddala, S.M.; Garg, S.; Doo, B.; Raskar, R. Generative Street Addresses from Satellite Imagery. ISPRS Int. J. Geo-Inf. 2018, 7, 84. https://doi.org/10.3390/ijgi7030084
AMA Style
Demir İ, Hughes F, Raj A, Dhruv K, Muddala SM, Garg S, Doo B, Raskar R. Generative Street Addresses from Satellite Imagery. ISPRS International Journal of Geo-Information. 2018; 7(3):84. https://doi.org/10.3390/ijgi7030084
Chicago/Turabian StyleDemir, İlke, Forest Hughes, Aman Raj, Kaunil Dhruv, Suryanarayana M. Muddala, Sanyam Garg, Barrett Doo, and Ramesh Raskar. 2018. "Generative Street Addresses from Satellite Imagery" ISPRS International Journal of Geo-Information 7, no. 3: 84. https://doi.org/10.3390/ijgi7030084
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