Flood Damage Modeling on the Basis of Urban Structure Mapping Using High-Resolution Remote Sensing Data

Abstract

Abstract:The modeling of flood damage is an important component for risk analyses, which are the basis for risk-oriented flood management, risk mapping, and financial appraisals. An automatic urban structure type mapping approach was applied on a land use/land cover classification generated from multispectral Ikonos data and LiDAR (Light Detection And Ranging) data in order to provide spatially detailed information about the building stock of the case study area of Dresden, Germany. The multi-parameter damage models FLEMOps (Flood Loss Estimation Model for the private sector) and regression-tree models have been adapted to the information derived from remote sensing data and were applied on the basis of the urban structure map. To evaluate this approach, which is suitable for risk analyses, as well as for post-disaster event analyses, an estimation of the flood losses caused by the Elbe flood in 2002 was undertaken. The urban structure mapping approach delivered a map with a good accuracy of 74% and on this basis modeled flood losses for the Elbe flood in 2002 in Dresden were in the same order of magnitude as official damage data. It has been shown that single-family houses suffered significantly higher damages than other urban structure types. Consequently, information on their specific location might significantly improve damage modeling, which indicates a high potential of remote sensing methods to further improve risk assessments. OPEN ACCESSWater 2014, 6 2368

Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier—A Case of Yuyao, China

“…In general, remote sensing data used for flood mapping consists of space-borne and airborne imageries. As for the former, optical and radar data have been widely adopted to extract inundation areas with high accuracy [5][6][7][8][9][10][11][12][13]. The advantage of optical satellite remote sensing [5,6] is that it provides true color images through which visual interpretation and automatic classification can be done to provide first-hand information of flooded areas.…”

“…Remote sensing has been recognized as a powerful tool to provide inundation maps in near real time according to a great deal of researches [1,[3][4][5][6][7][8][9][10][11][12][13]. Compared with in situ measurement, remote sensing can provide synoptic and continuous coverage of flood events, which aids flood monitoring and damage assessment [5][6][7][8][9].…”

“…Commonly used methods [1,[3][4][5][6][7][8][9][10][11][12][13] to extract flooded areas include thresholding, maximum likelihood, decision trees, etc. In this paper, we adopted a relatively novel classifier, Random Forest (RF) [18], for urban flood mapping.…”

Advances in Remote Sensing of Flooding

“…Although remotely sensed data have been used to assess the damage from local to regional extents (e.g., [2,14,15,[17][18][19]), estimates of possible structure damage and monetary loss, which are two key components in the flood risk analysis, are still a challenge. Using high resolution optical satellite data and airborne LiDAR data, Gerl et al [20] derived a land cover classification and map of urban structure types, and then input them into their multi-parameter flood damage models including regression tree models. The damage models were for the pre-hazard modeling and estimation of flood losses in flood risk mitigation, management, mapping, and financial appraisals.…”

Multi-Variate Analyses of Flood Loss in Can Tho City, Mekong Delta

“…This finding is different from the result of Penning-Rowsell [35] that the water depth is considered as a primary variable of flood losses to a building. Traditionally, depth-damage functions are used for flood loss estimation all over the world [9,20,36,37]. According to USACE (U.S Army Corps Engineers) [38], velocity is a major variable in damaging structures and contents.…”