Multi-sensoral and automated derivation of inundated areas using TerraSAR-X and ENVISAT ASAR data

Varying Scale and Capability of Envisat ASAR-WSM, TerraSAR-X Scansar and TerraSAR-X Stripmap Data to Assess Urban Flood Situations: A Case Study of the Mekong Delta in Can Tho Province

“…Detailed knowledge of the region is therefore available [31,34]. We also contributed to the validation of the flood mask derivation algorithm presented by Gstaiger et al [7]. Numerous interviews with locals-including scientists and farmers-were led over the course of this five year time span.…”

“…Verbeiren et al [23] developed a method to assess urbanization growth and the related impact on flood prediction around Dublin City, Ireland. Flood monitoring in densely settled urban areas based on SAR data has been undertaken by Henry et al [7], and Mason et al [24,25]. Henry et al [7] compared the flood boundary delineation capability of multi-polarized Envisat ASAR data with ERS-2 data during the 2002 Elbe river flood in Dresden City and Mason et al [24] investigated the century flood in Tewkesbury, UK in 2007.…”

“…Flood monitoring in densely settled urban areas based on SAR data has been undertaken by Henry et al [7], and Mason et al [24,25]. Henry et al [7] compared the flood boundary delineation capability of multi-polarized Envisat ASAR data with ERS-2 data during the 2002 Elbe river flood in Dresden City and Mason et al [24] investigated the century flood in Tewkesbury, UK in 2007. Mason et al [26] developed a LiDAR post-processor based on the fusion of airborne scanning laser altimetry and digital map data for urban flood modeling.…”

“…Floods lead to the hindrance of transportation, bring with them pollution and disease, lead to the destruction of infrastructure, and more people lose their lives due to floods than due to any other natural hazard [1][2][3]. It is widely accepted that synthetic aperture radar (SAR) data is a suitable choice for the mapping and monitoring of flooded areas [4][5][6][7][8] as it allows for observations even during heavy cloud cover (typical during rainy seasons). Leinenkugel et al.…”

“…Numerous authors assess flood situations based on a single radar data set, simply depicting the uni-temporal flood water extent and discuss flood water impact on other land cover classes, such as urban areas or infrastructure. Advanced studies rely on multitemporal data to analyze flood progression [6,7,[11][12][13][14][15][16][17][18][19].…”