Riccio, D.[Daniele],
Ruello, G.[Giuseppe],
Synthesis of Fractal Surfaces for Remote-Sensing Applications,
GeoRS(53), No. 7, July 2015, pp. 3803-3814.
IEEE DOI
1503
Fractals
BibRef
Riccio, D.[Daniele],
di Martino, G.[Gerardo],
Iodice, A.[Antonio],
Ruello, G.[Giuseppe],
Zinno, I.[Ivana],
Fractal dimension images from SAR images,
ICIP14(106-110)
IEEE DOI
1502
Estimation
BibRef
Schmitt, A.[Andreas],
Wessel, B.[Birgit],
Roth, A.[Achim],
Curvelet-based Change Detection on SAR Images for Natural Disaster
Mapping,
PFG(2010), No. 6, 2010, pp. 463-474.
WWW Link.
1211
BibRef
Earlier:
Curvelet Approach for SAR Image Denoising, Structure Enhancement, and
Change Detection,
CMRT09(151-156).
PDF File.
0909
BibRef
Schmitt, A.[Andreas],
Wessel, B.[Birgit],
Roth, A.[Achim],
An Innovative Curvelet-only-Based Approach for Automated Change
Detection in Multi-Temporal SAR Imagery,
RS(6), No. 3, 2014, pp. 2435-2462.
DOI Link
1404
BibRef
Broussolle, J.[Joan],
Kyovtorov, V.[Vladimir],
Basso, M.[Marco],
di Silvi e Castiglione, G.F.[Guido Ferraro],
Morgado, J.F.[Jorge Figueiredo],
Giuliani, R.[Raimondo],
Oliveri, F.[Franco],
Sammartino, P.F.[Pier Francesco],
Tarchi, D.[Dario],
MELISSA, a new class of ground based InSAR system. An example of
application in support to the Costa Concordia emergency,
PandRS(91), No. 1, 2014, pp. 50-58.
Elsevier DOI
1404
MIMO
BibRef
Singh, G.,
Yamaguchi, Y.,
Boerner, W.M.,
Park, S.E.[Sang-Eun],
Monitoring of the March 11, 2011, Off-Tohoku 9.0 Earthquake With
Super-Tsunami Disaster by Implementing Fully Polarimetric
High-Resolution POLSAR Techniques,
PIEEE(100), No. 3, March 2013, pp. 831-846.
IEEE DOI
1303
BibRef
Koyama, C.N.[Christian N.],
Gokon, H.[Hideomi],
Jimbo, M.[Masaru],
Koshimura, S.[Shunichi],
Sato, M.[Motoyuki],
Disaster debris estimation using high-resolution polarimetric
stereo-SAR,
PandRS(120), No. 1, 2016, pp. 84-98.
Elsevier DOI
1610
Debris
BibRef
Havivi, S.[Shiran],
Schvartzman, I.[Ilan],
Maman, S.[Shimrit],
Rotman, S.R.[Stanley R.],
Blumberg, D.G.[Dan G.],
Combining TerraSAR-X and Landsat Images for Emergency Response in
Urban Environments,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link
1806
BibRef
And:
Erratum:
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Havivi, S.[Shiran],
Schvartzman, I.[Ilan],
Maman, S.[Shimrit],
Marinoni, A.,
Gamba, P.,
Rotman, S.R.[Stanley R.],
Blumberg, D.G.[Dan G.],
Utilizing SAR and Multispectral Integrated Data For Emergency Response,
ISPRS16(B7: 493-496).
DOI Link
1610
BibRef
Kelevitz, K.[Krisztina],
Tiampo, K.F.[Kristy F.],
Corsa, B.D.[Brianna D.],
Improved Real-Time Natural Hazard Monitoring Using Automated DInSAR
Time Series,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Alonso-Díaz, A.[Alex],
Fontes, M.[Miguel],
Teixeira, A.C.[Ana Cláudia],
Wdowinski, S.[Shimon],
Sousa, J.J.[Joaquim J.],
Multi-Temporal InSAR and Machine Learning for Geohazard Monitoring: A
Systematic Review with Emphasis on Noise Mitigation and Model
Transferability,
RS(18), No. 9, 2026, pp. 1356.
DOI Link
2605
BibRef
Yang, C.H.,
Soergel, U.,
Rapid Disaster Analysis Based on SAR Techniques,
PIA15(281-288).
DOI Link
1504
BibRef
Meroni, A.,
Bahr, T.,
Operational SAR Data Processing in GIS Environments for Rapid Disaster
Mapping,
Hannover13(245-246).
DOI Link
1308
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Evacuation Management .