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

Abstract

Earth Observation is a powerful tool for the detection of floods. Microwave sensors are typically favored as they deliver data enabling water detection independent of solar illumination or cloud cover conditions. However, scale issues play an important role in radar based flood mapping. Depending on the flood related phenomenon under investigation, some sensors might be more suitable than others. In this study, we elucidate flood mapping at different spatial scale investigating the capability of Envisat ASAR Wide Swath Mode data at 150 m spatial resolution, as well as TerraSAR-X Scansar and Stripmap data at 8.25 m and 2.5 m resolution to especially assess urban flooding. For this purpose, we evaluate the results of automated multi-temporal water extraction from data sources of different scale against other parameters, such as settlement density, also taking a highly accurate building layer digitized from Quickbird data into consideration. Results reveal that while Envisat ASAR WSM derived flood maps are suitable to support the understanding of general flood patterns in a larger region, high resolution data of sensors OPEN ACCESSRemote Sens. 2013, 5 5123 such as TerraSAR-X is needed to truly assess urban flooding. However, even radar data of high spatial resolution still shows limitations; mainly in regions with a dense accumulation of corner reflectors leading to effects of layover, foreshortening, and shadowing, and hence the "over radiation" of flood affected areas.

A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains

“…Recently several automatic image processing algorithms to derive flooding from SAR data have been proposed [2,5,6,8,36]. Even if the crisis information can be extracted automatically, a certain amount of user interaction is needed for data pre-processing, the collection and adaptation of auxiliary data useful for classification refinement as well as the preparation and dissemination of the crisis information to end users.…”

Image Fusion-Based Change Detection for Flood Extent Extraction Using Bi-Temporal Very High-Resolution Satellite Images

“…As an advantage of rapid revisit time and of widely available spectral wavelengths, multi-temporal images acquired from sensors having low spatial resolution but high spectral resolution, such as Landsat and MODIS sensors, have been generally used for flood monitoring [4][5][6][7]. SAR images have also been employed due to their strength that can acquire the data regardless of the weather condition [8][9][10]. In spite of the advantages of those sensors, exploiting very high-resolution (VHR) multi-temporal images is still attractive to detect flood extent for more detail analysis with precise performance [11].…”

Flood Mapping Based on Multiple Endmember Spectral Mixture Analysis and Random Forest Classifier—The Case of Yuyao, China

“…Flooding is among one of the most destructive disasters which results in tremendous economic and human losses worldwide [1][2][3][4]. It is of great significance to map accurately the extent of inundated areas and the land cover types under water [4,5], which can assist in flood monitoring, relief works planning and damage assessment.…”

“…Due to its synoptic view and continuous coverage of flooding events, remote sensing has been recognized as a powerful and effective tool to provide inundation maps in near real time according to many researches [1][2][3][4][5][6][7][8][9][10][11]. Generally, remotely sensed data used for flood monitoring are mainly collected from radar and optical satellites.…”

“…The advantage of radar remote sensing is that it enables data acquisition regardless of weather conditions and time of day [7]. Space-borne sensors such as Synthetic Aperture Radar (SAR) [8] are capable of penetrating the cloud, and can provide views of the extent of inundation even when thick clouds exist above the disaster-stricken areas [1,2,[6][7][8].…”