Abstract
In this paper, efficient and economical methods for water area detection during flood event in mountainous area is proposed. To accomplish this, various case studies were preformed based on SAR image processing methods with the support of additional information such as Gray Level Co-occurrence Matrix (GLCM), Digital Elevation Model (DEM), and Digital Slope Model (DSM). As a result of various test2, the case when Synthetic Aperture Radar (SAR) image was classified with DSM applied by MIN filter gave the best performance, even in small streams of different elevation categories in mountainous terrain.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Birkett, C.M.: Synergistic Remote Sensing of Lake Chad: Variability of Basin Inundation. Remote Sensing of Environment 72(2), 218–236 (2000)
Costa, M.P.F.: Use of SAR Satellites for Mapping Zonation of Vegetation Communities in the Amazon Floodplain. International Journal of Remote Sensing 25(10), 1817–1835 (2004)
Giacomelli, A., Mancini, M.M., Rosso, R.: Assessment of Flooded Areas from ERS-1 PRI Data: An Applicaion to the 1994 Flood in Northern Italy. Phys. Chem. Earth 20(5-6), 469–474 (1995)
Giesen, N.V.D.: Characterization of west african shallow flood plains with L- and C-band radar. In: Remote sensing and Hydrology 2000 Proceedings of a symposium, vol. 267, pp. 365–367 (2000)
Goering, D.J., Chen, H., Hinzman, L.D., Kane, D.L.: Removal of terrain effects from SAR satellite imagery of Arctic tundra. IEEE Transaction on Geoscience and Remote Sensing 33(1), 185–194 (1995)
Goyal, S.K., Seyfreid, M.S., O’Neill, P.E.: Effect of digital elevation model resolution on topographic correction of airborne SAR. International Journal of Remote Sensing 19(3), 3076–3096 (1998)
Lee, J.S.: Speckle analysis and smoothing of synthetic aperture radar images. Computer Graphics and Image Processing 17, 24–32 (1981)
Liu, Z., Huang, F., Li, L., Wan, E.: Dynamic monitoring and damage evaluation of flood in north-west Jilin with remote sensing. International Journal of Remote Sensing 23(18), 3669–3679 (2002)
Mline, A.K., Horn, G., Finlayson, M.: Monitoring wetlands inundation patterns using RADARSAT multi-temporal data. Canadian Journal of Remote Sensing 26(2), 133–141 (2000)
Peng, X., Wang, J., Raed, M., Gari, J.: Land cover mapping from RADARSAT stereo images in a mountainous area of southern Argentina. Canadian Journal of Remote Sensing 29(1), 75–87 (2003)
Rio, J.N.R., Lozano-Carcia, D.F.: Spatial Filtering of Radar Data (RADARSAT) for Wetlands (Brackish Marshes) Classification. Remote Sensing of Environment 73(2), 143–151 (2000)
Shang, J.: Evaluation of multi-spectral scanner and radar satellite data for wetland detection and classification in the Great Lakes Basin, Masters Thesis, Department of Geography, University of Windsor, Windsor, Ont. (1996)
Sun, G., Ranson, K.J., Kharuk, V.I.: Radiometric slope correction for forest biomass estimation from SAR data in the Western Sayani Mountains, Siberia. Remote Sensing of Environment 79(2-3), 279–287 (2002)
Töyrä, J., Pietroniro, A., Maritz, L.W., Prowse, T.D.: A multi-sensor approach to wetland flood monitoring. Hydrological Process 16(8), 1569–1581 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sohn, HG., Song, YS., Kim, GH. (2005). Detecting Water Area During Flood Event from SAR Image. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424826_82
Download citation
DOI: https://doi.org/10.1007/11424826_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25861-2
Online ISBN: 978-3-540-32044-9
eBook Packages: Computer ScienceComputer Science (R0)