Limits and Challenges of Optical Very-High-Spatial-Resolution Satellite Remote Sensing for Urban Applications-Reference-Cited by-同舟云学术

Limits and Challenges of Optical Very-High-Spatial-Resolution Satellite Remote Sensing for Urban Applications

Published:2011-04-13 Issue: Volume: Page:35-48
ISSN:
Container-title:Urban Remote Sensing
language:
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Author:

Gamba Paolo,Dell'Acqua Fabio,Stasolla Mattia,Trianni Giovanna,Lisini Gianni

Publisher

John Wiley & Sons, Ltd

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/9780470979563.ch3/fullpdf

Reference36 articles.

1. Baltsavias , E. 2005 Potential of optical satellite sensors for urban mapping SIFET and AIT workshop on Urban Remote Sensing

2. Blaschke , T. 2003 Object-based contextual image classification built on image segmentation IEEE Workshop on Advances in Technology and Analysis of Remote Sensed Data 113 119

3. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information;Benz;ISPRS Journal of Photogrammetry and Remote Sensing,2004

4. Bovolo , F. Bruzzone , L. Marchesi , S. 2008 A context-sensitive technique robust to registration noise for change detection in very high resolution multispectral images Proceedings of IEEE International Geoscience and Remote Sensing Symposium, IGARSS'08 150 153

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