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Auteur Kaunil Dhruv |
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Generative street addresses from satellite imagery / İlke Demir in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)
[article]
Titre : Generative street addresses from satellite imagery Type de document : Article/Communication Auteurs : İlke Demir, Auteur ; Forest Hughes, Auteur ; Aman Raj, Auteur ; Kaunil Dhruv, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] adresse postale
[Termes IGN] apprentissage profond
[Termes IGN] extraction du réseau routier
[Termes IGN] graphe
[Termes IGN] image satellite
[Termes IGN] routeRésumé : (Auteur) 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. Numéro de notice : A2018-095 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030084 En ligne : https://doi.org/10.3390/ijgi7030084 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89507
in ISPRS International journal of geo-information > vol 7 n° 3 (March 2018)[article]