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.

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.

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.

Estimating discharge from inundation imagery

Remote sensing from space-borne platforms is often seen as an appealing method of monitoring components of the hydrological cycle, including river discharge, due to its spatial coverage. However, data from these platforms is often less than ideal because the geophysical properties of interest are rarely measured directly and the measurements that are taken can be subject to significant errors. This study assimilated water levels derived from a TerraSAR-X synthetic aperture radar image and digital aerial photography with simulations from a two dimensional hydraulic model to estimate discharge, inundation extent, depths and velocities at the confluence of the rivers Severn and Avon, UK. An ensemble Kalman filter was used to assimilate spot heights water levels derived by intersecting shorelines from the imagery with a digital elevation model. Discharge was estimated from the ensemble of simulations using state augmentation and then compared with gauge data. Assimilating the real data reduced the error between analyzed mean water levels and levels from three gauging stations to less than 0.3 m, which is less than typically found in post event water marks data from the field at these scales. Measurement bias was evident, but the method still provided a means of improving estimates of discharge for high flows where gauge data are unavailable or of poor quality. Posterior estimates of discharge had standard deviations between 63.3 m3s-1 and 52.7 m3s-1, which were below 15% of the gauged flows along the reach. Therefore, assuming a roughness uncertainty of 0.03-0.05 and no model structural errors discharge could be estimated by the EnKF with accuracy similar to that arguably expected from gauging stations during flood events. Quality control prior to assimilation, where measurements were rejected for being in areas of high topographic slope or close to tall vegetation and trees, was found to be essential. The study demonstrates the potential, but also the significant limitations of currently available imagery to reduce discharge uncertainty in un-gauged or poorly gauged basins when combined with model simulations in a data assimilation framework.

Robust classification of SAR imagery

In this work the G(A)(0) distribution is assumed as the universal model for amplitude Synthetic Aperture (SAR) imagery data under the Multiplicative Model. The observed data, therefore, is assumed to obey a G(A)(0) (alpha; gamma, n) law, where the parameter n is related to the speckle noise, and (alpha, gamma) are related to the ground truth, giving information about the background. Therefore, maps generated by the estimation of (alpha, gamma) in each coordinate can be used as the input for classification methods. Maximum likelihood estimators are derived and used to form estimated parameter maps. This estimation can be hampered by the presence of corner reflectors, man-made objects used to calibrate SAR images that produce large return values. In order to alleviate this contamination, robust (M) estimators are also derived for the universal model. Gaussian Maximum Likelihood classification is used to obtain maps using hard-to-deal-with simulated data, and the superiority of robust estimation is quantitatively assessed.

A change detection approach to flood mapping in urban areas using TerraSAR-X

Very high-resolution Synthetic Aperture Radar sensors represent an alternative to aerial photography for delineating floods in built-up environments where flood risk is highest. However, even with currently available SAR image resolutions of 3 m and higher, signal returns from man-made structures hamper the accurate mapping of flooded areas. Enhanced image processing algorithms and a better exploitation of image archives are required to facilitate the use of microwave remote sensing data for monitoring flood dynamics in urban areas. In this study a hybrid methodology combining radiometric thresholding, region growing and change detection is introduced as an approach enabling the automated, objective and reliable flood extent extraction from very high-resolution urban SAR images. The method is based on the calibration of a statistical distribution of “open water” backscatter values inferred from SAR images of floods. SAR images acquired during dry conditions enable the identification of areas i) that are not “visible” to the sensor (i.e. regions affected by ‘layover’ and ‘shadow’) and ii) that systematically behave as specular reflectors (e.g. smooth tarmac, permanent water bodies). Change detection with respect to a pre- or post flood reference image thereby reduces over-detection of inundated areas. A case study of the July 2007 Severn River flood (UK) observed by the very high-resolution SAR sensor on board TerraSAR-X as well as airborne photography highlights advantages and limitations of the proposed method. We conclude that even though the fully automated SAR-based flood mapping technique overcomes some limitations of previous methods, further technological and methodological improvements are necessary for SAR-based flood detection in urban areas to match the flood mapping capability of high quality aerial photography.

Scheduling satellite-based SAR acquisition for sequential assimilation of water level observations into flood modelling

Satellite-based Synthetic Aperture Radar (SAR) has proved useful for obtaining information on flood extent, which, when intersected with a Digital Elevation Model (DEM) of the floodplain, provides water level observations that can be assimilated into a hydrodynamic model to decrease forecast uncertainty. With an increasing number of operational satellites with SAR capability, information on the relationship between satellite first visit and revisit times and forecast performance is required to optimise the operational scheduling of satellite imagery. By using an Ensemble Transform Kalman Filter (ETKF) and a synthetic analysis with the 2D hydrodynamic model LISFLOOD-FP based on a real flooding case affecting an urban area (summer 2007,Tewkesbury, Southwest UK), we evaluate the sensitivity of the forecast performance to visit parameters. We emulate a generic hydrologic-hydrodynamic modelling cascade by imposing a bias and spatiotemporal correlations to the inflow error ensemble into the hydrodynamic domain. First, in agreement with previous research, estimation and correction for this bias leads to a clear improvement in keeping the forecast on track. Second, imagery obtained early in the flood is shown to have a large influence on forecast statistics. Revisit interval is most influential for early observations. The results are promising for the future of remote sensing-based water level observations for real-time flood forecasting in complex scenarios.

Co-eruptive and inter-eruptive surface deformation measured by satellite radar interferometry at Nyamuragira volcano, D.R. Congo, 1996 to 2010.

Interferometric Synthetic Aperture Radar (InSAR) measurements of surface deformation at Nyamuragira Volcano between 1996 and 2010 reveal a variety of co-eruptive and inter-eruptive signals. During 7 of the 8 eruptions in this period deformation was measured that is consistent with the emplacement of shallow near-vertical dykes feeding the eruptive fissures and associated with a NNW-trending fissure zone that traverses the summit caldera. Between eruptions the caldera and the summit part of this fissure zone subsided gradually (b3–5 cm/year). We also find evidence of post-eruption subsidence around the sites of the main vents of some flank eruptions (2002, 2004, 2006, and 2010). In the 6 months prior to the 2010 eruption a10-km wide zone centred on the caldera inflated by 1–2 cm. The low magnitude of this signal suggests that the presumed magma reservoir at 3–8 km depth contains highly compressible magma with little stored elastic strain energy. To the north of the caldera the fissure zone splits into WNW and NE branches around a zone that has a distinct InSAR signal. We interpret this zone to represent an elevated, 'stable' block of basement rocks buried by lavas within the Rift Zone.

Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data

The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

Observations of supercooling and frazil ice formation in the Laptev Sea coastal polynya

This paper examines a hydrographic response to the wind‐driven coastal polynya activity over the southeastern Laptev Sea shelf for April–May 2008, using a combination of Environmental Satellite (Envisat) advanced synthetic aperture radar (ASAR) and TerraSAR‐X satellite imagery, aerial photography, meteorological data, and SBE‐37 salinity‐temperature‐depth and acoustic Doppler current profiler land‐fast ice edgemoored instruments. When ASAR observed the strongest end‐of‐April polynya event with frazil ice formation, the moored instruments showed maximal acoustical scattering within the surface mixed layer, and the seawater temperatures were either at or 0.02°C below freezing. We also find evidence of the persistent horizontal temperature and salinity gradients across the fast ice edge to have the signature of geostrophic flow adjustment as predicted by polynya models.

Mapping Macrophyte Species in the Amazon Floodplain Wetlands Using Fully Polarimetric ALOS/PALSAR Data

The purpose of this paper was to evaluate attributes derived from fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain wetlands. Fieldwork was carried out almost simultaneously to the radar acquisition, and macrophyte biomass and morphological variables were measured in the field. Attributes were calculated from the covariance matrix [C] derived from the single-look complex data. Image attributes and macrophyte variables were compared and analyzed to investigate the sensitivity of the attributes for discriminating among species. Based on these analyses, a rule-based classification was applied to map macrophyte species. Other classification approaches were tested and compared to the rule-based method: a classification based on the Freeman-Durden and Cloude-Pottier decomposition models, a hybrid classification (Wishart classifier with the input classes based on the H/a plane), and a statistical-based classification (supervised classification using Wishart distance measures). The findings show that attributes derived from fully polarimetric L-band data have good potential for discriminating herbaceous plant species based on morphology and that estimation of plant biomass and productivity could be improved by using these polarimetric attributes.

Aplicação do Sensoriamento Remoto e do Sistema de Informações Geográficas na Detecção de Manchas de Óleo na Região do Pólo de Exploração de Guamaré, R.N.

Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamaré, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamaré for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamaré. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier

ASTER: A Brazilian mission to an asteroid

The first Brazilian mission to an asteroid is being planned. The target is the asteroid 2001 SN263, which has a NEA orbit of class AMOR. Spectral analysis indicated that this is a C-type asteroid. This type of asteroids are dark and difficult to be studied from Earth. They hold clues of the initial stages of planetary formation and also the origin of water and life on Earth. In fact, radar data showed that 2001 SN263 is composed of three bodies with diameters of about 2.8 km, 1.1 km and 0.4 km. Therefore, the spacecraft will have the opportunity to explore three bodies on the same trip. The mission is scheduled to be launched in 2015, reaching the asteroid in 2018. It will be used a small spacecraft (150 kg) with 30 kg for the payload. The set of scientific instruments being considered to explore the target of this mission include an Imaging Camera, a Laser Rangefinder, an Infrared Spectrometer, a Synthetic Aperture Radar and a Mass Spectrometer. The main measurements to be made include the bulk properties (size, shape, mass, density, dynamics, spin state), the internal properties (structure, gravity field) and surface properties (mineralogy, morphology, elemental composition). The mission also opens an opportunity for some relevant experiments, not directly related to the target. Two such experiments will take benefit from being on board of the spacecraft along the journey to the asteroid system, which will take about three years. The first is an astrobiology experiment. The main goal of this experiment is to determine the viability of the microorganisms survival in extraterrestrial environments simulated in laboratory (chemical atmosphere, temperature, desiccation, vacuum, microgravity and radiation). The second experiment is a plasma package. The main objectives of this experiment are to study the structure and electrodynamics of plasma along the trajectory, the plasma instability processes and the density and temperature of plasma of solar wind origin along the trajectory and near the asteroids. This mission represents a great challenge for the Brazilian space program. It is being structured to allow the full engagement of the Brazilian universities and technological companies in all the necessary developments to be carried out. In this paper, we present some aspects of this mission and details of the payload that will be used and the scientific expectations. Copyright ©2010 by the International Astronautical Federation. All rights reserved.

Mapeamento de ambientes costeiros tropicais (Golfão Maranhense, Brasil) utilizando imagens de sensores remotos orbitais

Este trabalho apresenta os resultados do reconhecimento e mapeamento dos ambientes costeiros da região do Golfão Maranhense, Brasil, utilizando uma abordagem metodológica que incluiu: (a) análise integrada com base no processamento digital de imagens, ópticas Landsat-4 TM e SPOT-2 HRV, de imagens SAR (Synthetic Aperture Radar) do RADARSAT-1, e dados de elevação da SRTM (Shuttle Radar Topography Mission); (b) sistema de informações geográficas; e (c) levantamentos de campo relativos à geomorfologia, topografia e sedimentologia. Os ambientes costeiros, assim mapeados foram agrupados em quatro setores: Setor 1, com pântanos salinos, pântanos de água doce, lagos intermitentes e canal estuarino; Setor 2, abrangendo tabuleiro costeiro, planície de maré lamosa, planície fluvial, planície de maré arenosa, praias de macromaré, área construída e lagos artificiais; Setor 3, com manguezal, paleodunas e planície de maré mista; e Setor 4, constituído por dunas móveis. Além disso, foram também reconhecidos lagos perenes, deltas de maré vazante e planícies de supramaré arenosas. O processamento digital e a análise visual das imagens de sensores remotos orbitais, associados ao uso de sistemas de informações geográficas, mostraram-se eficazes no mapeamento de zonas costeiras tropicais, possibilitando a geração de produtos com boa acurácia e precisão cartográfica.