The URBIS project: Vacant urban area classification and detection of changes

作者: Gabriele Moser , Vladimir Krylov , Michaela De Martino , Sebastiano Serpico

DOI: 10.1109/JURSE.2015.7120532

关键词:

摘要: The Urban Land Recycling Information Services for Sustainable Cities (URBIS) project aims to identify and monitor the vacant abandoned zones in large urban (LUZ). High resolution remotely sensed multispectral images will be employed along with available situ data perform classification multi-temporal change detection on European LUZ order facilitate redevelopment monitoring. activity builds result of a previous Atlas that produced high-resolution land use maps 305 their surroundings (with population over 100.000 inhabitants). This paper focuses presentation URBIS objectives scope, methodology applied by research unit at University Genoa performed within this project.

参考文章(10)
Thomas Blaschke, Stefan Lang, Geoffrey Hay, None, Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications Springer. ,(2008)
G. Moser, S. B. Serpico, J. A. Benediktsson, Land-Cover Mapping by Markov Modeling of Spatial–Contextual Information in Very-High-Resolution Remote Sensing Images Proceedings of the IEEE. ,vol. 101, pp. 631- 651 ,(2013) , 10.1109/JPROC.2012.2211551
Xin Huang, Liangpei Zhang, Pingxiang Li, Classification and Extraction of Spatial Features in Urban Areas Using High-Resolution Multispectral Imagery IEEE Geoscience and Remote Sensing Letters. ,vol. 4, pp. 260- 264 ,(2007) , 10.1109/LGRS.2006.890540
Dengsheng Lu, Qihao Weng, Use of impervious surface in urban land-use classification Remote Sensing of Environment. ,vol. 102, pp. 146- 160 ,(2006) , 10.1016/J.RSE.2006.02.010
Gang Chen, Geoffrey J. Hay, Luis M. T. Carvalho, Michael A. Wulder, Object-based change detection International Journal of Remote Sensing. ,vol. 33, pp. 4434- 4457 ,(2012) , 10.1080/01431161.2011.648285
Gabriele Moser, Sebastiano B. Serpico, Combining Support Vector Machines and Markov Random Fields in an Integrated Framework for Contextual Image Classification IEEE Transactions on Geoscience and Remote Sensing. ,vol. 51, pp. 2734- 2752 ,(2013) , 10.1109/TGRS.2012.2211882
A.H.S. Solberg, T. Taxt, A.K. Jain, A Markov random field model for classification of multisource satellite imagery IEEE Transactions on Geoscience and Remote Sensing. ,vol. 34, pp. 100- 113 ,(1996) , 10.1109/36.481897
Mark Dougherty, Randel L. Dymond, Scott J. Goetz, Claire A. Jantz, Normand Goulet, Evaluation of Impervious Surface Estimates in a Rapidly Urbanizing Watershed Photogrammetric Engineering and Remote Sensing. ,vol. 70, pp. 1275- 1284 ,(2004) , 10.14358/PERS.70.11.1275
Y. Boykov, O. Veksler, R. Zabih, Fast approximate energy minimization via graph cuts IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 23, pp. 1222- 1239 ,(2001) , 10.1109/34.969114
Masroor Hussain, Dongmei Chen, Angela Cheng, Hui Wei, David Stanley, Change detection from remotely sensed images: From pixel-based to object-based approaches Isprs Journal of Photogrammetry and Remote Sensing. ,vol. 80, pp. 91- 106 ,(2013) , 10.1016/J.ISPRSJPRS.2013.03.006