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(to be completed)

 


ThinkMind // GEOProcessing 2012, The Fourth International Conference on Advanced Geographic Information Systems, Applications, and Services // View article geoprocessing_2012_8_10_30040


Land-use Mapping of Valencia City Area from Aerial Images and LiDAR Data

Authors:
Txomin Hermosilla
Luis Angel Ruiz
Jorge Abel Recio
José Balsa-Barreiro

Keywords: Object-based classification; high spatial resolution imagery; LiDAR; urban areas; mapping

Abstract:
Land-use classification of urban environments is usually limited by the number and complexity of the considered classes and the capability of the selected methodology for the efficient discrimination of these classes. Thus, this paper analyses and assesses the performance of a contextual object-based classification methodology in urban environments considering a comprehensive land-use legend, including several complex urban land-uses –historical buildings, urban buildings, open urban buildings, semi-detached houses, detached houses, industrial/warehouse buildings, religious buildings, commercial buildings, public buildings, gardens and parks–, and agricultural classes –arable lands, citrus orchards, irrigated crops, carob-trees orchards, rice crops, forest, greenhouses–. Object-based approach was achieved by using cadastral plot limits for object definition. An exhaustive set of object-based descriptive features were computed informing about the spectral, texture, structural, geometrical, three-dimensional and contextual properties. Classification was performed by means of decision trees algorithm combined with boosting multi-classifier. The overall accuracy reached classifying the urban area of Valencia reached 84.8%, which is a significantly high value when considering a large number of complex urban classes.

Pages: 232 to 237

Copyright: Copyright (c) IARIA, 2012

Publication date: January 30, 2012

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-178-6

Location: Valencia, Spain

Dates: from January 30, 2012 to February 4, 2012

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