Name
Abstract | ||
|---|---|---|
This work shows that earthquake damages in urban areas can be determined with an acceptable accuracy through the exploitation
of multitemporal SAR data and ancillary information defining urban blocks. In this article, two different methodologies are
presented: an unsupervised statistical analysis of the parameters of the models representing backscatterer intensity or coherence
values for each block of the urban area under analysis, and a supervised approach which involves a multi-band/multi-temporal
classification, performed using a Markov Random Field (MRF) classifier or a spatial Fuzzy ARTMAP (FA) classifier. The two
procedures are compared by using ERS images acquired before and after the earthquake of Turkey in 1999. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s11554-008-0108-7 | J. Real-Time Image Processing |
Keywords | Field | DocType |
urban remote sensingrapid mapping,statistical analysis | Data mining,Computer science,Markov random field,Fuzzy logic,Coherence (physics),Classifier (linguistics),Urban area,Statistical analysis | Journal |
Volume | Issue | ISSN |
4 | 3 | 1861-8219 |
Citations | PageRank | References |
5 | 0.52 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giovanna Trianni | 1 | 90 | 10.92 |
| Paolo Gamba | 2 | 682 | 92.97 |