Characterisation of flood inundated areas and delineation of poor drainage soil using ERS-1 SAR imagery

Recent years have been marked by a continuous availability of spatial SAR data since the launch of the European remote sensing satellite (ERS-1) in 1991. Consequently, remote sensing techniques now offer an opportunity to map flood inundation fields caused by river overflow or waterlogging in environments characterized by frequent cloud cover. Indeed, inundation fields can clearly be seen on ERS-1 SAR images taken during flooding periods. However, such an identification can be constrained by the similarity in behaviour between water surfaces and other features of the landscape such as extended asphalt areas, permanent water bodies and less illuminated slopes. For consistent flood inundation extent mapping a more robust approach is required. This is provided by a conceptual flood inundation index that is physically sound in relation to radar imaging. Moreover, this index has proved to be useful for highlighting soils located within inundation fields and having significantly different internal drainage. The results achieved in the framework of the research must be seen in the context of intensive use of remote sensing data to support decision methods for sustainable management of land and water resources. Such decision support methods could be provided by river hydraulic models aimed at assessing environmental effects of inundation floods and at early flood warning systems. © 1997 John Wiley & Sons, Ltd.     

Hydrological runoff modelling by the use of remote sensing data with reference to the 1993–1994 and 1995 floods in the river Rhine catchment

In hydrological modelling of runoff processes, including water balance, various input data and parameters can be acquired or estimated by the use of remote sensing (RS) techniques.The acquisition and use of synoptic RS areal information rather than traditional point information is an important issue in hydrology. Hydrological models allow runoff/water balance in catchments to be calculated and flow routing within flow channels to be done. For runoff and water balance computations land use, soil moisture, detection of snow and ice, digital terrain models (DTM), as well as hydrometeorological information and discharge are important. For flow routing, water level information, geometric–topographic information such as cross-sections for normal and flood conditions, coefficient of roughness and velocity of flow and its cross-sectional distribution are required. In addition, water level information (lower and upper level) is needed for shipping and for design purposes. In the German part of the River Rhine catchment, several focus areas in the December 1993–January 1994 and January 1995 floods were covered with RS data [ERS-1 and airborne SAR, both C-band VV, passive microwave (18·7, 36·5, 89 GHz), TIR, UV, aerial photographs (b/w PAN, b/w NIR)], giving a good opportunity for a comparison of methods. Evaluation is still continuing. The importance of soil saturation for flood generation and, therefore, for flood monitoring, was shown on this occasion. The use of ERS SAR data for soil moisture estimation is currently being investigated by the Federal Institute of Hydrology. Also, the need for emergency schemes for data acquisition and easy, quick and affordable RS data dissemination was demonstrated. The assimilation of RS data with GIS information such as DTMs, including relevant topographic features like dams, which is omitted in currently available raster digital elevation models, is promising. RS altimetry techniques can be a step towards high resolution DTMs for hydrological purposes. Ground truth reference data are still needed. © 1997 John Wiley & Sons, Ltd.     

Use of ERS-1 data for the extraction of flooded areas

The aim of this study, undertaken by Geoimage, was the setting up of a fast and precise location method of flooded areas over two sites in southern France. The use of satellite imagery seemed to be the appropriate tool for this study. Two types of flood had to be distinguished: (i) an oceanic flood, of long duration characteristic, and of low intensity on the Rhône Valley, (ii) a torrential flood, of short duration characteristic, but of high intensity, on the Var Valley. As we distributed of ERS-1 images over both sites, during the floods, we could test our methodology. A multitemporal approach using ERS-1 images in PRI mode, acquired before, during and after the flood, was set up. In the case of oceanic flood, the radar images characteristic answers, enabled us to extract and identify areas under water at each date of acquisition of the images. Therefore, if we distribute images at each step of the flood, its evolution can be precisely reconstituted (in terms of time and surface). In the case of torrential flood, it is more difficult to localize the flood with precision. This can be explained by the change of water surface, which has a large swell in this case. Radars are sensitive to these changes in the turbidity, an interaction occurs and thus the results were ‘turned off’. Nevertheless, simulation studies from other satellite data make possible the location of more or less strong hydrological risk accident areas. © 1997 John Wiley & Sons, Ltd.     

A synergetic use of satellite imagery from SAR and optical sensors to improve coastal flood mapping in the Gulf of Mexico

This work proposes a method for detecting inundation between semi‐diurnal low and high water conditions in the northern Gulf of Mexico using high‐resolution satellite imagery. Radarsat 1, Landsat imagery and aerial photography from the Apalachicola region in Florida were used to demonstrate and validate the algorithm. A change detection approach was implemented through the analysis of red, green and blue (RGB) false colour composites image to emphasise differences in high and low tide inundation patterns. To alleviate the effect of inherent speckle in the SAR images, we also applied ancillary optical data. The flood‐prone area for the site was delineated a priori through the determination of lower and higher water contour lines with Landsat images combined with a high‐resolution digital elevation model. This masking technique improved the performance of the proposed algorithm with respect to detection techniques using the entire Radarsat scene. The resulting inundation maps agreed well with historical aerial photography as the probability of detection reached 83%. The combination of SAR data and optical images, when coupled with a high‐resolution digital elevation model, was shown to be useful for inundation mapping and have a great potential for evaluating wetting/drying algorithms of inland and coastal hydrodynamic models. Copyright © 2011 John Wiley & Sons, Ltd.     

A probabilistic model for real‐time flood warning based on deterministic flood inundation mapping

Deterministic flood inundation mapping is valuable for the investigation of detailed flood depth and extent. However, when these data are used for real‐time flood warning, uncertainty arises while encountering the difficulties of timely response, message interpretation and performance evaluation that makes statistical analysis necessary. By incorporating deterministic flood inundation map outputs statistically by means of logistic regression, this paper presents a probabilistic real‐time flood warning model determining region‐based flood probability directly from rainfall, being efficient in computation, clear in message, and valid in physical meaning. The calibration and validation of the probabilistic model show a satisfactory overall correctness rate, with the hit rate far surpassing the false alarm rate in issuing flood warning for historical events. Further analyses show that the probabilistic model is effective in evaluating the level of uncertainty lying within flood warning which can be reduced by several techniques proposed in order to improve warning performance. Copyright © 2011 John Wiley & Sons, Ltd.     

Floodnet: a telenetwork for acquisition,processing and dissemination of earth observation data for monitoring and emergency management of floods

The aim of FLOODNET is to provide a communications and data distribution facility specifically designed to meet the demanding temporal requirements of flood monitoring within the European Union (EU). Currently, remotely sensed data are not fully utilized for flood applications because potential users are not familiar with the procedure for acquiring the data and do not have a defined route for obtaining help in processing and interpreting the data. FLOODNET will identify the potential user groups within the EU and will, by demonstration, education and the use of telematics, increase the awareness of users to the capabilities of earth observation (EO) and the means by which they can acquire EO data. FLOODNET will act as a filter between users and satellite operation planners to help assign priorities for data acquisition against previously agreed criteria. The network will encourage a user community and will facilitate cross-sector information transfer, particularly between ‘flood experts’ and administrative decision makers. The requirement for two levels of flood mapping is identified: (1) a rapid, ‘broad-brush’ approach to assess the general flood situation and identify areas at greatest risk and in need of immediate assistance; (2) a detailed mapping approach, less critical in time, suitable for input to hydrological models or for flood risk evaluation. A likely networking technology is outlined, the basic functionality of a FLOODNET demonstrator is described and some of the economic benefits of the network are identified. © 1997 John Wiley & Sons, Ltd.     

Water surface mapping from airborne laser scanning using signal intensity and elevation data

In recent years airborne laser scanning (ALS) evolved into a state‐of‐the‐art technology for topographic data acquisition. We present a novel, automatic method for water surface classification and delineation by combining the geometrical and signal intensity information provided by ALS. The reflection characteristics of water surfaces in the near‐infrared wavelength (1064 nm) of the ALS system along with the surface roughness information provide the basis for the differentiation between water and land areas. Water areas are characterized by a high number of laser shot dropouts and predominant low backscatter energy. In a preprocessing step, the recorded intensities are corrected for spherical loss and atmospheric attenuation, and the locations of laser shot dropouts are modeled. A seeded region growing segmentation, applied to the point cloud and the modeled dropouts, is used to detect potential water regions. Object‐based classification of the resulting segments determines the final separation of water and non‐water points. The water‐land‐boundary is defined by the central contour line of the transition zone between water and land points. We demonstrate that the proposed workflow succeeds for a regulated river (Inn, Austria) with smooth water surface as well as for a pro‐glacial braided river (Hintereisfernerbach, Austria). A multi‐temporal analysis over five years of the pro‐glacial river channel emphasizes the applicability of the developed method for different ALS systems and acquisition settings (e.g. point density). The validation, based on real time kinematic (RTK) global positioning system (GPS) field survey and a terrestrial orthophoto, indicate point cloud classification accuracy above 97% with 0·45 m planimetric accuracy (root mean square error) of the water–land boundary. This article shows the capability of ALS data for water surface mapping with a high degree of automation and accuracy. This provides valuable datasets for a number of applications in geomorphology, hydrology and hydraulics, such as monitoring of braided rivers, flood modeling and mapping. Copyright © 2009 John Wiley & Sons, Ltd.     

Satellite remote sensing of river inundation area,stage, and discharge: a review

The growing availability of multi-temporal satellite data has increased opportunities for monitoring large rivers from space. A variety of passive and active sensors operating in the visible and microwave range are currently operating, or planned, which can estimate inundation area and delineate flood boundaries. Radar altimeters show great promise for directly measuring stage variation in large rivers. It also appears to be possible to obtain estimates of river discharge from space, using ground measurements and satellite data to construct empirical curves that relate water surface area to discharge. Extrapolation of these curves to ungauged sites may be possible for the special case of braided rivers. Where clouds, trees and floating vegetation do not obscure the water surface, high-resolution visible/infrared sensors provide good delineation of inundated areas. Synthetic aperture radar (SAR) sensors can penetrate clouds and can also detect standing water through emergent aquatic plants and forest canopies. However, multiple frequencies and polarizations are required for optimal discrimination of various inundated vegetation cover types. Existing single-polarization, fixed-frequency SARs are not sufficient for mapping inundation area in all riverine environments. In the absence of a space-borne multi-parameter SAR, a synergistic approach using single-frequency, fixed-polarization SAR and visible/infrared data will provide the best results over densely vegetated river floodplains. © 1997 John Wiley & Sons, Ltd.     

Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS‐2

Active microwave remote sensing observations of backscattering, such as C‐band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS‐2) satellite, have the potential to measure moisture content in a near‐surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from single frequency and polarization SAR observations is difficult. In this paper, the potential for measuring near‐surface soil moisture with the ERS‐2 satellite is explored by comparing model estimates of backscattering with ERS‐2 SAR observations. This comparison was made for two ERS‐2 overpasses coincident with near‐surface soil moisture measurements in a 6 ha catchment using 15‐cm time domain reflectometry probes on a 20 m grid. In addition, 1‐cm soil moisture data were obtained from a calibrated soil moisture model. Using state‐of‐the‐art theoretical, semi‐empirical and empirical backscattering models, it was found that using measured soil moisture and roughness data there were root mean square (RMS) errors from 3·5 to 8·5 dB and r² values from 0·00 to 0·25, depending on the backscattering model and degree of filtering. Using model soil moisture in place of measured soil moisture reduced RMS errors slightly (0·5 to 2 dB) but did not improve r² values. Likewise, using the first day of ERS‐2 backscattering and soil moisture data to solve for RMS surface roughness reduced RMS errors in backscattering for the second day to between 0·9 and 2·8 dB, but did not improve r² values. Moreover, RMS differences were as large as 3·7 dB and r² values as low as 0·53 between the various backscattering models, even when using the same data as input. These results suggest that more research is required to improve the agreement between backscattering models, and that ERS‐2 SAR data may be useful for estimating fields‐scale average soil moisture but not variations at the hillslope scale. Copyright © 2004 John Wiley & Sons, Ltd.     

Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: application to hydrological and erosion modelling

Synthetic aperture radar (SAR) sensors are often used to characterize the surface of bare soils in agricultural environments. They enable the soil moisture and roughness to be estimated with constraints linked to the configurations of the sensors (polarization, incidence angle and radar wavelength). These key soil characteristics are necessary for different applications, such as hydrology and risk prediction. This article reviews the potential of currently operational SAR sensors and those planned for the near future to characterize soil surface as a function of users' needs. It details what it is possible to achieve in terms of mapping soil moisture and roughness by specifying optimal radar configurations and the precision associated with the estimation of soil surface characteristics. The summary carried out for the present article shows that mapping soil moisture is optimal with SAR sensors at low incidence angles (<35 ). This configuration, which enables an estimated moisture accuracy greater than 6% is possible several times a month taking into account all the current and future sensors. Concerning soil roughness, it is best mapped using three classes (smooth, moderately rough, and rough). Such mapping requires high‐incidence data, which is possible with certain current sensors (RADARSAT‐1 and ASAR both in band C). When L‐band sensors (ALOS) become available, this mapping accuracy should improve because the sensitivity of the radar signal to Soil Surface Characteristics (SSC) increases with wavelength. Finally, the polarimetric mode of certain imminent sensors (ALOS, RADARSAT‐2, TerraSAR‐X, etc.), and the possibility of acquiring data at very high spatial resolution (metre scale), offer great potential in terms of improving the quality of SSC mapping. Copyright © 2007 John Wiley & Sons, Ltd.     

Potential applications of ERS-1 SAR data in near real-time

Summary Some important principles of remote sensing using synthetic aperture radar data (SAR data) from the first European Remote Sensing Satellite ERS-1 are explained. Examples illustrate the potential applications of satellite radar information. The possibility of using near-on-line processed remote information for operational purposes is discussed in particular.The satellite information used was received, processed and presented to the visitors of the exhibition which took place as part of the 1992 International Space Year (ISY) at the Bonn offices of the EEC. The BSH and DLR co-operated with DARA and TELEKOM. The intention was to familiarize a broader public with the potential of remote sensing and to stress the necessity of using space technology in combatting environmental problems.

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Zum Nutzungspotential von ERS-1-AAR-Daten in naher Echtzeit

Zusammenfassung Im vorliegenden Beitrag werden einige wichtige Grundlagen der Fernerkundung mit SAR-Daten des Ersten Europäischen Fernerkundungssatelliten ERS-1 erläutert und anhand einiger ausgewählter Beispiele Möglichkeiten der Nutzanwendung von Radar-Daten aufgezeigt. Dabei werden besonders die Möglichkeiten eines Nahe-Echtzeit-Einsatzes unter operationellen Gesichtspunkten aufgegriffen und diskutiert.Die verwendeten Daten wurden während einer Präsentation in der Vertretung der Kommission der Europäischen Gemeinschaft in Bonn anläßlich einer Veranstaltung zum Internationalen Weltraumjahr 1992 (ISY) von der BDDN-Fast-Delivery-Station des Bundesamts für Seeschiffahrt und Hydrographie (BSH) in Zusammenarbeit mit der Deutschen Forschungsanstalt für Luft- und Raumfahrt (DLR) und der TELEKOM aufgezeichnet, digital verarbeitet und den Besuchern der Ausstellung vorgestellt. Im Vordergrund stand, das Potential der Fernerkundung einer breiteren Öffentlichkeit zugänglich zu machen und die Notwendigkeit der Raumfahrt zur Erkundung unserer Umwelt zu bekräftigen.

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Le potentiel d'application des données ERS-1 SAR en utilisation presqueimmédiate

Résumé Des propriétés importantes du radar d'ouverture synthétique du premier satellite européen ERS-1 d'observation de la Terre sont présentées. Des exemples choisis illustrent les possibilités d'utilisation appliquée de l'information radar. La possibilité d'une exploitation en temps très légèrement différé sous des aspects opérationnels est démontrée.L'information du satellite ERS-1 a été reçue, traitée et archivée lors d'une présentation à la Commission de la Communauté Européene à Bonn. À l'occasion de la manifestation de l'année internationale de l'espace 1992 (ISY), avec le concours de l'Agence Maritime et Hydrographique Fédérale (BSH), en coopération avec le Centre Allemand de Recherches Aérospatiales (DLR) et les TELEKOM. Le but était de présenter au public les possibilités de la télédétection et de montrer la nécessité de l'usage de la technologie pour aider à résoudre les problèmes de l'environment.

     

Flood management through LANDSAT TM and ERS SAR data: a case study

This paper deals with the experimental activity carried out in the field of flood monitoring at the Civil Engineering Department of Florence University (Italy) in cooperation with EOSAT (USA) and Eurimage (Italy). The aim of the study is to research the possibilities of satellite data utilization to aid in modelling of the hydrological behaviour of a river basin and monitoring flood emergencies. The area selected for the study is the Fucecchio Marsh (Tuscany, Italy), in which flooding events are very frequent. This paper describes the results of the study, with particular reference to the use of Landsat TM data to estimate soil water content, and the use of ERS SAR data to analyse flash flood events. © 1997 John Wiley & Sons, Ltd.     

Residual relief separation: digital elevation model enhancement for geomorphological mapping

Geomorphologically mapped data form a primary set of observations that can be used to infer former environmental conditions. Thus, objective and consistent mapping of landforms from remotely sensed data (e.g. satellite imagery, digital elevation models (DEMs)) is paramount for reconstructing palaeoenvironments. This paper proposes a technique, ‘residual relief separation’, to enhance landforms in DEMs prior to visualization and digital mapping. This is applied to a ～600 km² region surrounding Lough Gara, Ireland, where drumlins (～200 m wide) overlie a regional relief of hills (～10 km wide). Here, residual relief separation uses this difference in width‐scale. Regional relief is approximated by a 1 km wide median filter, then subtracted to leave the drumlins in a ‘residual’ topography. In a second step, the residual relief is normalized to allow for amplitude variations in the drumlins across the area (～5–40 m high). Finally, visualization uses a simple black‐to‐white colour scale for height. Although not numerically outperforming other visualization techniques, this method performs equally well, and as the data are not ‘illuminated’ there is no azimuthal bias. Additional benefits include the relatively simple calculation, intuitive visual comprehension, no emphasis of noise, and the possibility of using any desired visualization technique after the landscape has been topographically manipulated. Copyright © 2008 John Wiley & Sons, Ltd.     

Application of boat‐based laser scanning for river survey

The boat‐based, mobile mapping system (BoMMS) with a laser scanner allows the derivation of detailed riverine topographical data for fluvial applications. Combined with data acquisition from static terrestrial LiDAR (light detection and range) or mobile terrestrial LiDAR on the ground, boat‐based laser scanning enables a totally new field mapping approach for fluvial studies. The BoMMS approach is an extremely rapid methodology for surveying riverine topography, taking only 85 min to survey a reach approximately 6 km in length. The BoMMS approach also allowed an effective survey angle for deep river banks, which is difficult to achieve with aerial or static terrestrial LiDAR. Further, this paper demonstrates the three‐dimensional mapping of a point‐bar and its detailed morphology. Compared with the BoMMS surface, approximately, 80% and 96% of the terrestrial LiDAR points showed a height deviation of less than 2 cm and 5 cm, respectively, with an overall standard deviation of ± 2·7 cm. This level of accuracy and rapidity of data capture enables the mapping of post‐flood deposition directly after a flood event without an extensive time lag. Additionally, the improved object characterisation may allow for better 3D mapping of the point bar and other riverrine features. However, the shadow effect of the BoMMS survey in point bar mapping should be removed by additional LiDAR data to acquire entire riverine topography. The approach demonstrated allowed a large reach to be surveyed compared with static terrestrial LiDAR and increased the spatial limit of survey towards aerial LiDAR, but it maintains the same or even better temporal resolution as static terrestrial LiDAR. Copyright © 2009 John Wiley & Sons, Ltd.     

A review of low‐cost space‐borne data for flood modelling: topography,flood extent and water level

During the last two decades, remote sensing data have led to tremendous progress in advancing flood inundation modelling. In particular, low‐cost space‐borne data can be invaluable for large‐scale flood studies in data‐scarce areas. Various satellite products yield valuable information such as land surface elevation, flood extent and water level, which could potentially contribute to various flood studies. An increasing number of research studies have been dedicated to exploring those low‐cost data towards building, calibration and evaluation, and remote‐sensed information assimilation into hydraulic models. This paper aims at reviewing these recent scientific efforts on the integration of low‐cost space‐borne remote sensing data with flood modelling. Potentials and limitations of those data in flood modelling are discussed. This paper also introduces the future satellite missions and anticipates their likely impacts in flood modelling. Copyright © 2015 John Wiley & Sons, Ltd.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Global mapping of artificial surfaces at 30-m resolution

Urbanization is expected to accelerate with population growth and economic development at the global scale. The artificial surface is the main land cover form of urbanization. On the one hand, urbanization provides spaces for industry, economic activities and residence. On the other hand, artificial surfaces change the earth surface to a large extent, thus significantly affecting natural processes such as the heat exchange, hydrological processes and ecological balance. Therefore, the global mapping of artificial surfaces is valuable for both natural science and social science. This study produced the global artificial surface maps at 30-m resolution for two base-years using the satellite images acquired around 2000 and 2010. First, we proposed a new definition of “artificial surface” based on patch level with consideration of its geographic meaning and image features at 30-m resolution. Second, pixel-based and object-based image processing techniques were combined for the extraction of artificial surface patches. Finally, human editing and a quality control system were employed to guarantee the quality of global mapping. Independent accuracy assessments show that the user’s accuracy of this product is higher than 80%. It can be concluded that the product is the most reliable one among all the available global datasets of artificial surfaces (or related types). The data can significantly contribute to various research fields, such as urbanization and ecosystem assessment.     

Spatial heterogeneity in estuarine mud dynamics

The fate of mud in an estuary over an entire year was unravelled using complementary, independent, spatially explicit techniques. Sequential ERS-2 SAR and Envisat MERIS-FR data were used to derive synoptic changes in intertidal bottom mud and suspended particulate matter (SPM) in the top of the water column, respectively. These satellite data were combined with in situ measurements and with a high resolution three-dimensional cohesive sediment model, simulating mud transport, resuspension, settling and deposition under the influence of tides, wind, waves and freshwater discharge. The spatial distribution of both bottom mud and SPM as observed by in situ and satellite techniques was largely explained by modelled estuarine circulation, tidal and wind-induced variations in vertical mixing and horizontal advection. The three data sources also showed similar spring-neap and seasonal variations in SPM (all factor 1.5 to 2), but semi-diurnal tidal variations were underestimated by the model. Satellite data revealed that changes in intertidal bottom mud were spatially heterogeneous, but on average mud content doubled during summer, which was confirmed by in situ data. The model did not show such seasonal variation in bed sediment, suggesting that seasonal dynamics are not well explained by the physical factors presently implemented in the model, but may be largely attributed to other (internal) factors, including increased floc size in summer, temporal stabilisation of the sediment by microphytobenthos and a substantially lower roughness of the intertidal bed in summer as observed by the satellite. The effects of such factors on estuarine mud dynamics were evaluated.