Flood detection in urban areas using TerraSAR-X

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X Synthetic Aperture Radar (SAR) data to detect flooded regions in urban areas is described. The study uses a TerraSAR-X image of a 1 in 150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SAR End-To-End simulator (SETES) was used in conjunction with airborne scanning laser altimetry (LiDAR) data to estimate regions of the image in which water would not be visible due to shadow or layover caused by buildings and taller vegetation. A semi-automatic algorithm for the detection of floodwater in urban areas is described, together with its validation using the aerial photographs. 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. The algorithm is aimed at producing urban flood extents with which to calibrate and validate urban flood inundation models, and these findings indicate that TerraSAR-X is capable of providing useful data for this purpose.

Improving flood inundation models using remotely sensed data

The paper discusses the wide variety of ways in which remotely sensed data are being utilized in river flood inundation modeling. Model parameterization is being aided using airborne LiDAR data to provide topography of the floodplain for use as model bathymetry, and vegetation heights in the floodplain for use in estimating floodplain friction factors. Model calibration and validation are being aided by comparing the flood extent observed in SAR images with the extent predicted by the model. The recent extension of this to the observation of urban flooding using high resolution TerraSAR-X data is described. Possible future research directions are considered.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

Sensitivity of radar backscatter to desert surface roughness

Synthetic aperture radar (SAR) data have proved useful in remote sensing studies of deserts, enabling different surfaces to be discriminated by differences in roughness properties. Roughness is characterized in SAR backscatter models using the standard deviation of surface heights (sigma), correlation length (L) and autocorrelation function (rho(xi)). Previous research has suggested that these parameters are of limited use for characterizing surface roughness, and are often unreliable due to the collection of too few roughness profiles, or under-sampling in terms of resolution or profile length (L-p). This paper reports on work aimed at establishing the effects of L-p and sampling resolution on SAR backscatter estimations and site discrimination. Results indicate significant relationships between the average roughness parameters and L-p, but large variability in roughness parameters prevents any clear understanding of these relationships. Integral equation model simulations demonstrate limited change with L-p and under-estimate backscatter relative to SAR observations. However, modelled and observed backscatter conform in pattern and magnitude for C-band systems but not for L-band data. Variation in surface roughness alone does not explain variability in site discrimination. Other factors (possibly sub-surface scattering) appear to play a significant role in controlling backscatter characteristics at lower frequencies.

Remote sensing of intertidal morphological change in Morecambe Bay, U.K., between 1991 and 2007

Tidal Flats are important examples of extensive areas of natural environment that remain relatively unaffected by man. Monitoring of tidal flats is required for a variety of purposes. Remote sensing has become an established technique for the measurement of topography over tidal flats. A further requirement is to measure topographic changes in order to measure sediment budgets. To date there have been few attempts to make quantitative estimates of morphological change over tidal flat areas. This paper illustrates the use of remote sensing to measure quantitative and qualitative changes in the tidal flats of Morecambe Bay during the relatively long period 1991–2007. An understanding of the patterns of sediment transport within the Bay is of considerable interest for coastal management and defence purposes. Tidal asymmetry is considered to be the dominant cause of morphological change in the Bay, with the higher currents associated with the flood tide being the main agency moulding the channel system. Quantitative changes were measured by comparing a Digital Elevation Model (DEM) of the intertidal zone formed using the waterline technique applied to satellite Synthetic Aperture Radar (SAR) images from 1991–1994, to a second DEM constructed from airborne laser altimetry data acquired in 2005. Qualitative changes were studied using additional SAR images acquired since 2003. A significant movement of sediment from below Mean Sea Level (MSL) to above MSL was detected by comparing the two Digital Elevation Models, though the proportion of this change that could be ascribed to seasonal effects was not clear. Between 1991 and 2004 there was a migration of the Ulverston channel of the river Leven north-east by about 5 km, followed by the development of a straighter channel to the west, leaving the previous channel decoupled from the river. This is thought to be due to independent tidal and fluvial forcing mechanisms acting on the channel. The results demonstrate the effectiveness of remote sensing for measurement of long-term morphological change in tidal flat areas. An alternative use of waterlines as partial bathymetry for assimilation into a morphodynamic model of the coastal zone is also discussed.

Modeling of atmospheric effects on InSAR measurements by incorporating terrain elevation information

We propose an elevation-dependent calibratory method to correct for the water vapour-induced delays over Mt. Etna that affect the interferometric syntheric aperture radar (InSAR) results. Water vapour delay fields are modelled from individual zenith delay estimates on a network of continuous GPS receivers. These are interpolated using simple kriging with varying local means over two domains, above and below 2 km in altitude. Test results with data from a meteorological station and 14 continuous GPS stations over Mt. Etna show that a reduction of the mean phase delay field of about 27% is achieved after the model is applied to a 35-day interferogram. (C) 2006 Elsevier Ltd. All rights reserved.

Using remotely sensed data to support flood modelling

Recent severe flooding in the UK has highlighted the need for better information on flood risk, increasing the pressure on engineers to enhance the capabilities of computer models for flood prediction. This paper evaluates the benefits to be gained from the use of remotely sensed data to support flood modelling. The remotely sensed data available can be used either to produce high-resolution digital terrain models (DTMs) (light detection and ranging (Lidar) data), or to generate accurate inundation mapping of past flood events (airborne synthetic aperture radar (SAR) data and aerial photography). The paper reports on the modelling of real flood events that occurred at two UK sites on the rivers Severn and Ouse. At these sites a combination of remotely sensed data and recorded hydrographs was available. It is concluded first that light detection and ranging Lidar generated DTMs support the generation of considerably better models and enhance the visualisation of model results and second that flood outlines obtained from airborne SAR or aerial images help develop an appreciation of the hydraulic behaviour of important model components, and facilitate model validation. The need for further research is highlighted by a number of limitations, namely: the difficulties in obtaining an adequate representation of hydraulically important features such as embankment crests and walls; uncertainties in the validation data; and difficulties in extracting flood outlines from airborne SAR images in urban areas.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

Progress on “Changing coastlines: data assimilation for morphodynamic prediction and predictability”

The task of assessing the likelihood and extent of coastal flooding is hampered by the lack of detailed information on near-shore bathymetry. This is required as an input for coastal inundation models, and in some cases the variability in the bathymetry can impact the prediction of those areas likely to be affected by flooding in a storm. The constant monitoring and data collection that would be required to characterise the near-shore bathymetry over large coastal areas is impractical, leaving the option of running morphodynamic models to predict the likely bathymetry at any given time. However, if the models are inaccurate the errors may be significant if incorrect bathymetry is used to predict possible flood risks. This project is assessing the use of data assimilation techniques to improve the predictions from a simple model, by rigorously incorporating observations of the bathymetry into the model, to bring the model closer to the actual situation. Currently we are concentrating on Morecambe Bay as a primary study site, as it has a highly dynamic inter-tidal zone, with changes in the course of channels in this zone impacting the likely locations of flooding from storms. We are working with SAR images, LiDAR, and swath bathymetry to give us the observations over a 2.5 year period running from May 2003 – November 2005. We have a LiDAR image of the entire inter-tidal zone for November 2005 to use as validation data. We have implemented a 3D-Var data assimilation scheme, to investigate the improvements in performance of the data assimilation compared to the previous scheme which was based on the optimal interpolation method. We are currently evaluating these different data assimilation techniques, using 22 SAR data observations. We will also include the LiDAR data and swath bathymetry to improve the observational coverage, and investigate the impact of different types of observation on the predictive ability of the model. We are also assessing the ability of the data assimilation scheme to recover the correct bathymetry after storm events, which can dramatically change the bathymetry in a short period of time.

AT(1) receptor ligands: virtual-screening-based design with TOPP descriptors, synthesis, and biological evaluation of pyrrolidine derivatives

As a continuing effort to establish the structure-activity relationships (SARs) within the series of the angiotensin II antagonists (sartans), a pharmacophoric model was built by using novel TOPP 3D descriptors. Statistical values were satisfactory (PC4: r(2)=0.96, q(2) ((5) (random) (groups))=0.84; SDEP=0.26) and encouraged the synthesis and consequent biological evaluation of a series of new pyrrolidine derivatives. SAR together with a combined 3D quantitative SAR and high-throughput virtual screening showed that the newly synthesized 1-acyl-N-(biphenyl-4-ylmethyl)pyrrolidine-2-carboxamides may represent an interesting starting point for the design of new antihypertensive agents. In particular, biological tests performed on CHO-hAT(1) cells stably expressing the human AT(1) receptor showed that the length of the acyl chain is crucial for the receptor interaction and that the valeric chain is the optimal one.

Crystal and molecular structure of the thioether-analogue of PEEK from X-ray powder data and diffraction-modelling

Analysis of X-ray powder data for the melt-crystallisable aromatic poly(thioether thioether ketone) [-S-Ar-S-Ar-CO-Ar](n), ('PTTK', Ar= 1,4-phenylene), reveals that it adopts a crystal structure very different from that established for its ether-analogue PEEK. Molecular modelling and diffraction-simulation studies of PTTK show that the structure of this polymer is analogous to that of melt-crystallised poly(thioetherketone) [-SAr-CO-Ar](n) in which the carbonyl linkages in symmetry-related chains are aligned anti-parallel to one another. and that these bridging units are crystallographically interchangeable. The final model for the crystal structure of PTTK is thus disordered, in the monoclinic space group 121a (two chains per unit cell), with cell dimensions a = 7.83, b = 6.06, c = 10.35 angstrom, beta = 93.47 degrees. (c) 2005 Elsevier Ltd. All rights reserved.

Correlation-type structure activity relationships for the kinetics of gas-phase RO2 self-reactions and reaction with HO2

Structure activity relationships (SARs) are presented for the gas-phase reactions of RO2 with HO2, and the self- and cross-reactions of RO2. For RO2+HO2 the SAR is based upon a correlation between the logarithm of the measured rate coefficient and a calculated ionisation potential for the molecule R-CH=CH2, R being the same group in both the radical and molecular analogue. The correlation observed is strong and only for one RO2 species does the measured rate coefficient deviate by more than a factor of two from the linear least-squares regression line. For the self- and cross-reactions of RO2 radicals, the SAR is based upon a correlation between the logarithm of the measured rate coefficient and the calculated electrostatic potential (ESP) at the equivalent carbon atom in the RH molecule to which oxygen is attached in RO2, again R being the same group in the molecule and the radical. For cases where R is a simple alkyl-group, a strong linear correlation observed. For RO2 radicals which contain lone pair-bearing substituents and for which the calculated ESP<-0.05 self-reaction rate coefficients appear to be insensitive to the value of the ESP. For RO2 of this type with ESP>-0.05 a linear relationship between log k and the ESP is again observed. Using the relationships, 84 out of the 85 rate coefficients used to develop the SARs are predicted to within a factor of three of their measured values. A relationship is also presented that allows the prediction of the Arrhenius parameters for the self-reactions of simple alkyl RO2 radicals. On the basis of the correlations, predictions of room-temperature rate coefficients are made for a number of atmospherically important peroxyl-peroxyl radical reactions. (C) 2003 Elsevier Ltd. All rights reserved.

Gas-phase rate coefficients for the reactions of NO3, OH and O-3 with alpha,beta-unsaturated esters and ketones: structure-activity relations (SARs)

Gas-phase rate coefficients for the atmospherically important reactions of NO3, OH and O-3 are predicted for 55 alpha,beta-unsaturated esters and ketones. The rate coefficients were calculated using a correlation described previously [Pfrang, C., King, M.D., C. E. Canosa-Mas, C.E., Wayne, R.P., 2006. Atmospheric Environment 40, 1170-1179]. These rate coefficients were used to extend structure-activity relations for predicting the rate coefficients for the reactions of NO3, OH or O-3 with alkenes to include alpha,beta-unsaturated esters and ketones. Conjugation of an alkene with an alpha,beta-keto or alpha,beta-ester group will reduce the value of a rate coefficient by a factor of similar to 110, similar to 2.5 and similar to 12 for reaction with NO3, OH or O-3, respectively. The actual identity of the alkyl group, R, in -C(O)R or -C(O)OR has only a small influence. An assessment of the reliability of the SAR is given that demonstrates that it is useful for reactions involving NO3 and OH, but less valuable for those of O-3 or peroxy nitrate esters. (c) 2006 Elsevier Ltd. All rights reserved.

Optical sensors for monitoring water uptake in plants

The monitoring of water uptake in plants is becoming increasingly important. Optical sensors offer considerable advantages over conventional methods and several sensors have been developed including an optical potometer that monitors water uptake from individual roots, the detection of xylem cavitation using audio acoustic emissions with an interferometric force feedback microphone, and an optical fiber displacement transducer that detects changes in leaf thickness in relation to leaf-water potential.

Near real-time 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. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm 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. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.