- Aach T. and Kaup A., “Bayesian algorithms for adaptive change detection in image sequences using Markov random fields”, Image Commun., vol. 7, no. 2, pp. 147–160, 1995.
https://doi.org/10.1016/0923-5965%2895%2900003-F
- Aherne F. J., Thacker N. A., and Rockett P. I., “The Bhattacharyya metric as an absolute similarity measure for frequency coded data”, Kybernetika, vol. 34, pp. 363–368, Jun. 1998.
http://www.kybernetika.cz/content/1998/4/363/paper.pdf
- Ali, I., Cao, S., Naeimi, V., Paulik, C., & Wagner, W. (2018). Methods to remove the border noise from Sentinel-1 synthetic aperture radar data: implications and importance for time-series analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(3), 777-786.
https://doi-org.proxy.bnl.lu/10.1109/JSTARS.2017.2787650
- Ashman K. M., Bird C. M. and Zepf S. E., “Detecting bimodality in astronomical datasets”, Astron. J., vol. 108, pp. 2348–2361, Aug. 1994.
https://doi.org/10.1086/117248
- Bauer-Marschallinger, B.; Cao, S.; Tupas, M.E.; Roth, F.; Navacchi, C.; Melzer, T.; Freeman, V.; Wagner, W. Satellite-Based Flood Mapping through Bayesian Inference from a Sentinel-1 SAR Datacube. Remote Sens. 2022, 14, 3673.
https://doi.org/10.3390/rs14153673
- Bazi Y., Bruzzone L. and Melgani F., “Image thresholding based on the EM algorithm and the generalized Gaussian distribution”, Pattern Recognit., vol. 40, no. 2, pp. 619–634, 2007.
https://doi.org/10.1016/j.patcog.2006.05.006
- Chow, C., Twele, A., Martinis, S. (2016). An assessment of the ‘Height Above Nearest Drainage’ terrain descriptor for the thematic enhancement of automatic SAR-based flood monitoring services. Proc. of SPIE, 9998, 1-11.
https://doi.org/10.1117/12.2240766
- European Commission. 2020. Technical Specifications for Call for tenders JRC/IPR/2020/OP/0551 - Provision of an Automated, Global, Satellite-based Flood Monitoring Product for the Copernicus Emergency Management Service.
https://etendering.ted.europa.eu/document/document-file-download.html?docFileId=77006
- Gong M., Li H. and Jiang X., “A multi-objective optimization framework for ill-posed inverse problems”, CAAI Trans. Intell. Technol., vol. 1, no. 3, pp. 225–240, 2016
https://doi.org/10.1016/J.TRIT.2016.10.007
- Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science, 342, 850–853.
https://doi.org/10.1126/science.1244693
- Kittler, J., & Illingworth, J. (1986). Minimum error thresholding. Pattern Recognit., 19, 41-47.
https://doi.org/10.1016/0031-3203%2886%2990030-0
- Laferte J. M., Perez P. and Heitz F., “Discrete Markov image modeling and inference on the quadtree”, IEEE Trans. Image Process., vol. 9, no. 3, pp. 390–404, Mar. 2000
https://doi.org/10.1109/83.826777
- Lehner, B., Verdin, K., & Jarvis, A. (2008). New global hydrography derived from spaceborne elevation data. Eos, Transactions American Geophysical Union, 89(10), 93-94.
https://doi.org/10.1029/2008EO100001
- Marquardt D. W., “An algorithm for least-squares estimation of nonlinear parameters”, J. Soc. Ind. Appl. Math., vol. 11, no. 2, pp. 431–441, 1963.
https://doi.org/10.1137/0111030
- Matgen, P., S. Martinis, W. Wagner, V. Freeman, P. Zeil, and N. McCormick. 2020. Feasibility assessment of an automated, global, satellite-based flood-monitoring product for the Copernicus Emergency Management Service. JRC Technical Report. EUR 30073 EN. Publications Office of the European Union, Luxembourg. ISBN 978-92-76-10254-0. 47p.
https://doi.org/10.2760/653891
- Otsu N., “A threshold selection method from gray-level histograms”, IEEE Trans. Syst., Man, Cybern., vol. SMC-9, no. 1, pp. 62–66, Jan. 1979.
https://doi.org/10.1109/TSMC.1979.4310076
- Pal S. K. and Rosenfeld A., "Image Enhancement and Thresholding by Optimization of Fuzzy Compactness", Patt. Recog. Lett., vol. 7, pp. 77-86, 1988.
https://doi.org/10.1016/0167-8655%2888%2990122-5
- Pekel J.F., Cottam A., Gorelick N., Belward A.S., "High-resolution mapping of global surface water and its long-term changes", Nature, vol. 540, pp. 418-422, 2016.
https://doi.org/10.1038/nature20584
- Quegan, S.; Le Toan T.; Yu J.J.; Ribbes F.; Floury N. 2000. Multitemporal ERS SAR Analysis Applied to Forest Mapping. IEEE Transactions on Geoscience and Remote Sensing 38 (2): 741–753.
https://doi.org/10.1109/36.842003
- Rennó, C.D., Nobre, A.D., Cuartas, L.A., Soares, J.V., Hodnett, M.G., Tomasella, J., Waterloo, M.J., 2008. HAND, a new terrain descriptor using SRTM-DEM: Mapping terrafirme rainforest environments in Amazonia. Remote Sensing of Environment, 112, 3469-3481.
https://doi.org/10.1016/j.rse.2008.03.018
- Rott H., Mätzler C. Possibilities and limits of synthetic aperture radar for snow and glacier surveying, Ann. Glaciol., 9, 195–199, 1987.
https://doi.org/10.1017/S0260305500000604
- Salamon, P., N. McCormick, C. Reimer, T. Clarke, B. Bauer-Marschallinger, W. Wagner, S. Martinis, C. Chow, C. Böhnke, P. Matgen, M. Chini, R. Hostache , L. Molini, E. Fiori, A. Walli. 2021. The new, systematic global flood monitoring product of the Copernicus Emergency Management Service. International Geoscience and Remote Sensing Symposium (IGARRS) 2021. Paper WE4.O-6.4.
https://igarss2021.com/view_paper.php?PaperNum=3884
- Sauer, S., Ferro-Famil, L., Reigber, A., Pottier, E., 2011. Three-dimensional imaging and scattering mechanism estimation over urban scenes using dual-baseline polarimetric InSAR observations at L-band. IEEE Transactions on Geoscience and Remote Sensing, 49(11), 4616-4629. https://doi.org/10.1109/TGRS.2011.2147321
- Schlaffer, S.; Matgen, P.; Hollaus, M.; Wagner, W. Flood detection from multi-temporal SAR data using harmonic analysis and change detection.International Journal of Applied Earth Observation and Geoinformation 2015,38, 15 – 24.
https://doi.org/10.1016/j.jag.2014.12.001
- Twele, A., Cao, W., Plank, S., Martinis, S., 2016. Sentinel-1 based flood mapping: a fully automated processing chain. International Journal of Remote Sensing, 37 (13), 2990-3004.
https://doi.org/10.1080/01431161.2016.1192304
- Ulaby F. and Dobson M. C., Handbook of Radar Scattering Statistics for Terrain. Norwood, MA, USA: Artech House, 1989
https://www.amazon.com/Handbook-Scattering-Statistics-Terrain-Sensing/dp/0890063362
- Wagner, W., V. Freeman, S. Cao, P. Matgen, M. Chini, P. Salamon, N. McCormick, S. Martinis, B. Bauer-Marschallinger, C. Navacchi, M. Schramm, C. Reimer, and C. Briese. 2020. Data processing architectures for monitoring floods using Sentinel-1. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-3-2020, 641–648.
https://doi.org/10.5194/isprs-annals-V-3-2020-641-2020
Main Menu