TY - JOUR
T1 - Flood mapping of danube river at romania using single and multi-date ERS2-SAR images
AU - Gan, T. Y.
AU - Zunic, F.
AU - Kuo, C. C.
AU - Strobl, T.
N1 - Funding Information:
The first author was jointly supported by the German Academic Exchange Service (DAAD) and the Technische Universität München, Germany during his sabbatical leave from the University of Alberta. The ERS2-SAR data was provided through a research proposal funded by the European Space Agency (ESA) under its Category 1 project program. Image analysis was done using the PCI software. The third author was partly funded by the Canadian Foundation for Climate and Atmospheric Science (CFCAS).
PY - 2012
Y1 - 2012
N2 - Several flood mapping classification techniques, applied to single-date and multi-date SAR images of ERS2, based on the Danube River flooding of 2006 in Romania are compared, as part of an effort to explore the feasibility of mapping flooded areas by SAR images acquired through radar sensors. Among 7 SAR images analyzed for the same study site located around Bistret of Romania, several represent "dry" and several "wet" conditions, where the latter represent the major Danube flooding event of 2006. The images were classified into (1) permanent water (Danube River and lakes), (2) flooded area, and (3) dry land, using single image, pixel-based classification, frequency-based contextual classification, and principal component analysis (PCA) combined with Isodata classification. The flooded areas delineated from the above procedures for the study site at Bistret are visually compared with that of Landsat-TM images and MODIS mosaic and digitally compared with referenced flooded area produced by the DEM data of SRTM. Apparently there is no one technique that is clearly better partly because of the nature of SAR data (radar echoes) and partly because of data noise even though the images were first subjected to speckle filtering and geometric corrections, and partly because SAR images could appear dark not only because of flooding but also because of smooth surfaces, target sizes, etc. However, if multi-date SAR images of both DRY and WET (flooding) conditions are available, it seems that PCA combined with the Isodata classifier would give better defined flooded areas of the Danube River than the simple single image, pixel-based classification or the contextual classification.
AB - Several flood mapping classification techniques, applied to single-date and multi-date SAR images of ERS2, based on the Danube River flooding of 2006 in Romania are compared, as part of an effort to explore the feasibility of mapping flooded areas by SAR images acquired through radar sensors. Among 7 SAR images analyzed for the same study site located around Bistret of Romania, several represent "dry" and several "wet" conditions, where the latter represent the major Danube flooding event of 2006. The images were classified into (1) permanent water (Danube River and lakes), (2) flooded area, and (3) dry land, using single image, pixel-based classification, frequency-based contextual classification, and principal component analysis (PCA) combined with Isodata classification. The flooded areas delineated from the above procedures for the study site at Bistret are visually compared with that of Landsat-TM images and MODIS mosaic and digitally compared with referenced flooded area produced by the DEM data of SRTM. Apparently there is no one technique that is clearly better partly because of the nature of SAR data (radar echoes) and partly because of data noise even though the images were first subjected to speckle filtering and geometric corrections, and partly because SAR images could appear dark not only because of flooding but also because of smooth surfaces, target sizes, etc. However, if multi-date SAR images of both DRY and WET (flooding) conditions are available, it seems that PCA combined with the Isodata classifier would give better defined flooded areas of the Danube River than the simple single image, pixel-based classification or the contextual classification.
KW - Dry land
KW - ERS2-SAR images
KW - Flooded area
KW - Flooding of Danube River
KW - PCA and Isodata classifications
KW - Permanent water
KW - Single-image un-supervised, contextual
UR - http://www.scopus.com/inward/record.url?scp=84864517206&partnerID=8YFLogxK
U2 - 10.1016/j.jag.2012.01.012
DO - 10.1016/j.jag.2012.01.012
M3 - Article
AN - SCOPUS:84864517206
SN - 1569-8432
VL - 18
SP - 69
EP - 81
JO - International Journal of Applied Earth Observation and Geoinformation
JF - International Journal of Applied Earth Observation and Geoinformation
IS - 1
ER -