Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 545325
Title Land-use characterisation using Google Street View pictures and OpenStreetMap
Author(s) Srivastava, S.; Lobry, Sylvain; Tuia, D.; Vargas Munoz, John
Event 21st AGILE Conference on Geographic Information Science (2018), Lund, 2018-06-12/2018-06-15
Department(s) Laboratory of Geo-information Science and Remote Sensing
PE&RC
Publication type Contribution in proceedings
Publication year 2018
Abstract This paper presents a study on the use of freely available, geo-referenced pictures from Google Street View to model and predict land-use at the urban-objects scale. This task is traditionally done manually and via photointerpretation, which is very time consuming. We propose to use a machine learning approach based on deep learning and to model land-use directly from both the pictures available from Google Street View and OpenStreetMap annotations. Because of the large availability of these two data sources, the proposed approach is scalable to cities around the globe and presents the possibility of frequent updates of the map. As base information, we use features extracted from single pictures around the object of interest; these features are issued from pre-trained convolutional neural networks. Then, we train various classifiers (Linear and RBF support vector machines, multi layer perceptron) and compare their performances. We report on a study over the city of Paris,France, where we observed that pictures coming from both inside and outside the urban-objects capture distinct, but complementary features.
Comments
There are no comments yet. You can post the first one!
Post a comment
 
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.