A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy.

Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: a case study

Flood extents caused by fluvial floods in urban and rural areas may be predicted by hydraulic models. Assimilation may be used to correct the model state and improve the estimates of the model parameters or external forcing. One common observation assimilated is the water level at various points along the modelled reach. Distributed water levels may be estimated indirectly along the flood extents in Synthetic Aperture Radar (SAR) images by intersecting the extents with the floodplain topography. It is necessary to select a subset of levels for assimilation because adjacent levels along the flood extent will be strongly correlated. A method for selecting such a subset automatically and in near real-time is described, which would allow the SAR water levels to be used in a forecasting model. The method first selects candidate waterline points in flooded rural areas having low slope. The waterline levels and positions are corrected for the effects of double reflections between the water surface and emergent vegetation at the flood edge. Waterline points are also selected in flooded urban areas away from radar shadow and layover caused by buildings, with levels similar to those in adjacent rural areas. The resulting points are thinned to reduce spatial autocorrelation using a top-down clustering approach. The method was developed using a TerraSAR-X image from a particular case study involving urban and rural flooding. The waterline points extracted proved to be spatially uncorrelated, with levels reasonably similar to those determined manually from aerial photographs, and in good agreement with those of nearby gauges.

Detection of flooded urban areas in high resolution Synthetic Aperture Radar images using double scattering

Flooding is a particular hazard in urban areas worldwide due to the increased risks to life and property in these regions. Synthetic Aperture Radar (SAR) sensors are often used to image flooding because of their all-weather day-night capability, and now possess sufficient resolution to image urban flooding. The flood extents extracted from the images may be used for flood relief management and improved urban flood inundation modelling. A difficulty with using SAR for urban flood detection is that, due to its side-looking nature, substantial areas of urban ground surface may not be visible to the SAR due to radar layover and shadow caused by buildings and taller vegetation. This paper investigates whether urban flooding can be detected in layover regions (where flooding may not normally be apparent) using double scattering between the (possibly flooded) ground surface and the walls of adjacent buildings. The method estimates double scattering strengths using a SAR image in conjunction with a high resolution LiDAR (Light Detection and Ranging) height map of the urban area. A SAR simulator is applied to the LiDAR data to generate maps of layover and shadow, and estimate the positions of double scattering curves in the SAR image. Observations of double scattering strengths were compared to the predictions from an electromagnetic scattering model, for both the case of a single image containing flooding, and a change detection case in which the flooded image was compared to an un-flooded image of the same area acquired with the same radar parameters. The method proved successful in detecting double scattering due to flooding in the single-image case, for which flooded double scattering curves were detected with 100% classification accuracy (albeit using a small sample set) and un-flooded curves with 91% classification accuracy. The same measures of success were achieved using change detection between flooded and un-flooded images. Depending on the particular flooding situation, the method could lead to improved detection of flooding in urban areas.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images

The topography of many floodplains in the developed world has now been surveyed with high resolution sensors such as airborne LiDAR (Light Detection and Ranging), giving accurate Digital Elevation Models (DEMs) that facilitate accurate flood inundation modelling. This is not always the case for remote rivers in developing countries. However, the accuracy of DEMs produced for modelling studies on such rivers should be enhanced in the near future by the high resolution TanDEM-X WorldDEM. In a parallel development, increasing use is now being made of flood extents derived from high resolution Synthetic Aperture Radar (SAR) images for calibrating, validating and assimilating observations into flood inundation models in order to improve these. This paper discusses an additional use of SAR flood extents, namely to improve the accuracy of the TanDEM-X DEM in the floodplain covered by the flood extents, thereby permanently improving this DEM for future flood modelling and other studies. The method is based on the fact that for larger rivers the water elevation generally changes only slowly along a reach, so that the boundary of the flood extent (the waterline) can be regarded locally as a quasi-contour. As a result, heights of adjacent pixels along a small section of waterline can be regarded as samples with a common population mean. The height of the central pixel in the section can be replaced with the average of these heights, leading to a more accurate estimate. While this will result in a reduction in the height errors along a waterline, the waterline is a linear feature in a two-dimensional space. However, improvements to the DEM heights between adjacent pairs of waterlines can also be made, because DEM heights enclosed by the higher waterline of a pair must be at least no higher than the corrected heights along the higher waterline, whereas DEM heights not enclosed by the lower waterline must in general be no lower than the corrected heights along the lower waterline. In addition, DEM heights between the higher and lower waterlines can also be assigned smaller errors because of the reduced errors on the corrected waterline heights. The method was tested on a section of the TanDEM-X Intermediate DEM (IDEM) covering an 11km reach of the Warwickshire Avon, England. Flood extents from four COSMO-SKyMed images were available at various stages of a flood in November 2012, and a LiDAR DEM was available for validation. In the area covered by the flood extents, the original IDEM heights had a mean difference from the corresponding LiDAR heights of 0.5 m with a standard deviation of 2.0 m, while the corrected heights had a mean difference of 0.3 m with standard deviation 1.2 m. These figures show that significant reductions in IDEM height bias and error can be made using the method, with the corrected error being only 60% of the original. Even if only a single SAR image obtained near the peak of the flood was used, the corrected error was only 66% of the original. The method should also be capable of improving the final TanDEM-X DEM and other DEMs, and may also be of use with data from the SWOT (Surface Water and Ocean Topography) satellite.

Sparse arrays and image compounding techniques for non-destructive testing using guided acoustic waves

Piezoelectric array transducers applications are becoming usual in the ultrasonic non-destructive testing area. However, the number of elements can increase the system complexity, due to the necessity of multichannel circuitry and to the large amount of data to be processed. Synthetic aperture techniques, where one or few transmission and reception channels are necessary, and the data are post-processed, can be used to reduce the system complexity. Another possibility is to use sparse arrays instead of a full-populated array. In sparse arrays, there is a smaller number of elements and the interelement spacing is larger than half wavelength. In this work, results of ultrasonic inspection of an aluminum plate with artificial defects using guided acoustic waves and sparse arrays are presented. Synthetic aperture techniques are used to obtain a set of images that are then processed with an image compounding technique, which was previously evaluated only with full-populated arrays, in order to increase the resolution and contrast of the images. The results with sparse arrays are equivalent to the ones obtained with full-populated arrays in terms of resolution. Although there is an 8 dB contrast reduction when using sparse arrays, defect detection is preserved and there is the advantage of a reduction in the number of transducer elements and data volume. © 2013 Brazilian Society for Automatics - SBA.

Use of synthetic aperture radar for recognition of Coastal Geomorphological Features, land-use assessment and shoreline changes in Bragança coast, Pará, Northern Brazil

Imagens de radar de abertura sintética (SAR) vem sendo bem mais utilizadas do que antes nas aplicações de geociências em regiões tropicais úmidas. Nesta investigação, uma imagem RADARSAT-1, na banda C, polarização HH adquirida em 1998 foi usada para o mapeamento costeiro e avaliação da cobertura da terra na área de Bragança, norte do Brasil. Imagem do radar aerotransportado GEMS-1000, na banda X, polarização HH, adquirida em 1972 durante o projeto RADAM foi também utilizada para avaliar as variações costeiras ocorridas nas últimas três décadas. A pesquisa tem confirmado a utilidade da imagem RADARSAT-1 para o mapeamento geomorfológico e avaliação da cobertura da terra, particularmente em costas de manguezal de macromaré. Além disso, um novo método para estimar as variações da linha de costa baseado na superposição de vetores extraídos de diferentes imagens SAR, com alta acurácia geométrica, tem mostrado que a planície costeira de Bragança tem estado sujeita a severa erosão responsável pelo recuo de aproximadamente 32 km² e acreção de 20 km², resultando em uma perda de área de manguezal de aproximadamente 12 km². Como perspectiva de aplicação, dados SAR orbitais e aerotransportados provaram ser uma importante fonte de informação tanto para o mapeamento geomorfológico, quando para o monitoramento de modificações costeiras em ambientes tropicais úmidos.

Dynamics of the Gulf of California (GC). A case study of the internal waves using synthetic aperture radar (SAR)

Calificación: Matrícula de Honor

Comparisons of observed ice properties and Envisat Advanced Synthetic Aperture Radar (ASAR) data during Nathanial B. Palmer cruise NBP09-01 and Oden cruise OSO08/09

Envisat Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) images are used to derive C-band HH-polarization normalized radar cross sections (NRCS). These are compared with ice-core analysis and visual ship-based observations of snow and ice properties observed according to the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol during two International Polar Year summer cruises (Oden 2008 and Palmer 2009) in West Antarctica. Thick first-year (TFY) and multi-year (MY) ice were the dominant ice types. The NRCS value ranges between -16.3 ± 1.1 and -7.6 ± 1.0 dB for TFY ice, and is -12.6 ± 1.3 dB for MY ice; for TFY ice, NRCS values increase from ~-15 dB to -9 dB from December/January to mid-February. In situ and ASPeCt observations are not, however, detailed enough to interpret the observed NRCS change over time. Co-located Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) vertically polarized 37 GHz brightness temperatures (TB37V), 7 day and 1 day averages as well as the TB37V difference between ascending and descending AMSR-E overpasses suggest the low NRCS values (-15 dB) are associated with snowmelt being still in progress, while the change towards higher NRCS values (-9dB) is caused by commencement of melt-refreeze cycles after about mid-January.

Near-coastal circum-Antarctic iceberg size distributions determined from Synthetic Aperture Radar images

The Radarsat-1 Antarctic Mapping Project (RAMP) compiled a mosaic of Antarctica and the adjacent ocean zone from more than 3000 high-resolution Synthetic Aperture Radar (SAR) images acquired in September and October 1997. The mosaic with a pixel size of 100 m was used to determine iceberg size distributions around Antarctica, combining an automated detection with a visual control of all icebergs larger than 5 km**2 and correction of recognized false detections. For icebergs below 5 km**2 in size, the numbers of false detections and accuracies of size retrievals were analyzed for three test sites. Nearly 7000 icebergs with horizontal areas between 0.3 and 4717.7 km**2 were identified in a near-coastal zone of varying width between 20 and 300 km. The spatial distributions of icebergs around Antarctica were calculated for zonal segments of 20° angular width and related to the types of the calving fronts in the respective section. Results reveal that regional variations of the size distributions cannot be neglected. The highest ice mass accumulations were found at positions of giant icebergs (> 18.5 km) but also in front of ice shelves from which larger numbers of smaller icebergs calve almost continuously. Although the coastal oceanic zone covered by RAMP is too narrow compared to the spatial coverage needed for oceanographic research, this study nevertheless demonstrates the usefulness of SAR images for iceberg research and the need for repeated data acquisitions extending ocean-wards over distances of 500 km and more from the coast to monitor iceberg melt and disintegration and the related freshwater input into the ocean.

Processing of ultra-wideband low-frequency signals, for application in Foliage Penetration (FOPEN) Synthetic Aperture Radar (SAR) systems

Foliage Penetration (FOPEN) radar systems were introduced in 1960, and have been constantly improved by several organizations since that time. The use of Synthetic Aperture Radar (SAR) approaches for this application has important advantages, due to the need for high resolution in two dimensions. The design of this type of systems, however, includes some complications that are not present in standard SAR systems. FOPEN SAR systems need to operate with a low central frequency (VHF or UHF bands) in order to be able to penetrate the foliage. High bandwidth is also required to obtain high resolution. Due to the low central frequency, large integration angles are required during SAR image formation, and therefore the Range Migration Algorithm (RMA) is used. This project thesis identifies the three main complications that arise due to these requirements. First, a high fractional bandwidth makes narrowband propagation models no longer valid. Second, the VHF and UHF bands are used by many communications systems. The transmitted signal spectrum needs to be notched to avoid interfering them. Third, those communications systems cause Radio Frequency Interference (RFI) on the received signal. The thesis carries out a thorough analysis of the three problems, their degrading effects and possible solutions to compensate them. The UWB model is applied to the SAR signal, and the degradation induced by it is derived. The result is tested through simulation of both a single pulse stretch processor and the complete RMA image formation. Both methods show that the degradation is negligible, and therefore the UWB propagation effect does not need compensation. A technique is derived to design a notched transmitted signal. Then, its effect on the SAR image formation is evaluated analytically. It is shown that the stretch processor introduces a processing gain that reduces the degrading effects of the notches. The remaining degrading effect after processing gain is assessed through simulation, and an experimental graph of degradation as a function of percentage of nulled frequencies is obtained. The RFI is characterized and its effect on the SAR processor is derived. Once again, a processing gain is found to be introduced by the receiver. As the RFI power can be much higher than that of the desired signal, an algorithm is proposed to remove the RFI from the received signal before RMA processing. This algorithm is a modification of the Chirp Least Squares Algorithm (CLSA) explained in [4], which adapts it to deramped signals. The algorithm is derived analytically and then its performance is evaluated through simulation, showing that it is effective in removing the RFI and reducing the degradation caused by both RFI and notching. Finally, conclusions are drawn as to the importance of each one of the problems in SAR system design.