ERS-1 Synthetic Aperture Radar Research Articles

Ocean Wave Integral Parameter Measurements Using Envisat ASAR Wave Mode Data

An empirical algorithm to retrieve integral ocean wave parameters such as significant wave height (SWH), mean wave period, and wave height of waves with period larger than 12 s <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$({H}_{12})$ </tex></formula> from synthetic aperture radar (SAR) images over sea surface is presented. The algorithm is an extension to the Envisat Advanced SAR (ASAR) wave mode data based on the CWAVE approach developed for ERS-2 SAR wave mode data and is thus called CWAVE_ENV (CWAVE for Envisat). Calibrated ASAR images are used as the only source of input without needing prior information from an ocean wave model (WAM) as the standard algorithms used in weather centers. This algorithm makes SAR an independent instrument measuring integrated wave parameters like SWH and mean wave period to altimeter quality. A global data set of 25 000 pairs of ASAR wave mode images and collocated reanalysis WAM results from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to tune CWAVE_ENV model coefficients. Validation conducted by comparing the retrieved SWH to in situ buoy measurements shows a scatter index of 0.24 and 0.16 when compared to the ECMWF reanalysis WAM. Two case studies are presented to evaluate the performance of the CWAVE_ENV algorithm for high sea state. A North Atlantic storm during which SWH is above 18 m as observed by SAR and Radar Altimeter simultaneously is analyzed. For an extreme swell case that occurred in the Indian Ocean, the potential of using SWH measurements from ASAR wave mode data derived by the CWAVE_ENV algorithm is demonstrated.

Underwater topography detection of Taiwan Shoal with SAR images

Under suitable conditions of tidal current and wind, underwater topography can be detected by synthetic aperture radar (SAR) indirectly. Underwater topography SAR imaging includes three physical processes: radar ocean surface backscattering, the modulation of sea surface short wave spectrum by the variations in sea surface currents, and the modulation of sea surface currents by the underwater topography. The first process is described usually by Bragg scattering theory because the incident angle of SAR is always between 20°–70°. The second process is described by the action balance equation. The third process is described by an ocean hydrodynamic model. Based on the SAR imaging mechanism for underwater topography, an underwater topography SAR detection model and a simplified method for its calculation are introduced. In the detection model, a two-dimensional hydrodynamic model — the shallow water model is used to describe the motion of tidal current. Due to the difficulty of determining the expression of SAR backscattering cross section in which some terms can not be determined, the backscattering cross section of SAR image used in the underwater topography SAR detection is pro-processed by the simulated SAR image of the coarse-grid water depth to simplify the calculation. Taiwan Shoal, located at the southwest outlet of Taiwan Strait, is selected as an evaluation area for this technique due to the occurrence of hundreds of sand waves. The underwater topography of Taiwan Shoal was detected by two scenes of ERS-2 SAR images which were acquired on 9 January 2000 and 6 June 2004. The detection results are compared with in situ measured water depths for three profiles. The average absolute and relative errors of the best detection result are 2.23 m and 7.5 %, respectively. These show that the detection model and the simplified method introduced in the paper is feasible.

A Level Set Filter for Speckle Reduction in SAR Images

Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

On the variations of InSAR-ICA altitudes in a mountain area of the Sele Valley (South Italy)

The ERS-1/ERS-2 Synthetic Aperture Radar (SAR) data are processed by InSAR-ICA technique and the altitude variations are calculated for the period June-December 1995. For the same period and the same ERS- 1/ERS-2 SAR data, the nominal surface deformations are calculated by the standard DInSAR (Differential Interferometric SAR) method, considered without any atmospheric correction. The results of the two different processing techniques are qualitatively compared with the previous geological and hydrological observations of the area under study. It is shown how the InSAR-ICA altitude variations are in better agreement with the expected characterization of this region. Although these variations cannot be considered quantitative precise surface deformations at present, this finding is interpreted in terms of usefulness and reliability of InSAR-ICA altitude estimations.

InSAR analyses of terrain deformation near the Wieliczka Salt Mine, Poland

European Remote Sensing satellites ERS-1 and ERS-2 synthetic aperture radar (SAR) data are used to analyze terrain deformation in the area of Wieliczka, Poland using interferometric techniques. Terrain deformations in Wieliczka are due to (i) salt mining, (ii) catastrophic suffusion caused by water inflows to the mine and (iii) landslides in the southern part of the region. To discriminate between different deformation regimes differential SAR Interferometry (D-InSAR) and persistent scatterers interferometry (PSI) are used. A comparison with published information based on leveling data is performed. It can be concluded that rapid subsidence caused by catastrophic water inflow cannot be identified with InSAR techniques. However, both D-InSAR and PSI retrieve information about slow subsidence due to mine convergence. These data match with subsidence maps constructed from leveling data. A limited amount of coherent scatterers were identified on landslides. Some scatterers can be related to buildings with clear damage caused by landslide movement.

Calibration of uncertain flood inundation models using remotely sensed water levels

Summary A traditional method of validating the performance of a flood model when remotely sensed data of the flood extent are available is to compare the predicted flood extent to that observed. The performance measure employed often uses areal pattern-matching to assess the degree to which the two extents overlap. Recently, remote sensing of flood extents using synthetic aperture radar (SAR) and airborne scanning laser altimetry (LiDAR) has made more straightforward the synoptic measurement of water surface elevations along flood boundaries (waterlines), and this has emphasised the possibility of using alternative performance measures based on height. This paper considers the advantages that can accrue from using a performance measure based on waterline elevations rather than one based on areal patterns of wet and dry pixels. The two measures were compared for their ability to estimate flood inundation uncertainty maps from a set of LISFLOOD-FP model runs carried out to span the acceptable model parameter range. A 1-in-5-year flood on the Thames in 1992, observed in an ERS-1 SAR image, was used as a test event. Waterlines were delineated in fused SAR and LiDAR data using an active contour model (snake). The performance measure based on height differences of corresponding points along the observed and modelled waterlines was found to be significantly more sensitive to the channel friction parameter than the measure based on areal patterns of flood extent. A result of this was that there was less uncertainty in the final flood hazard map. The height-based measure was found to be more sensitive when increased heighting accuracy was achieved by requiring that observed waterline heights varied slowly along the reach. The technique was shown to allow the decomposition of the reach into sections, with different effective channel friction parameters used in different sections. However, an evaluation of the modelled inundation uncertainty using the calibration event showed significant differences between the uncertainty map and the observed flood extent, especially for the height-based measure. This was probably due to the conceptually simple flood inundation model and the coarse application resolution employed in this case. The increased sensitivity of the height-based measure may lead to an increased onus being placed on the model developer in the production of a valid model.

A Fast Level Set Method for Synthetic Aperture Radar Ocean Image Segmentation

Segmentation of high noise imagery like Synthetic Aperture Radar (SAR) images is still one of the most challenging tasks in image processing. While level set, a novel approach based on the analysis of the motion of an interface, can be used to address this challenge, the cell-based iterations may make the process of image segmentation remarkably slow, especially for large-size images. For this reason fast level set algorithms such as narrow band and fast marching have been attempted. Built upon these, this paper presents an improved fast level set method for SAR ocean image segmentation. This competent method is dependent on both the intensity driven speed and curvature flow that result in a stable and smooth boundary. Notably, it is optimized to track moving interfaces for keeping up with the point-wise boundary propagation using a single list and a method of fast up-wind scheme iteration. The list facilitates efficient insertion and deletion of pixels on the propagation front. Meanwhile, the local up-wind scheme is used to update the motion of the curvature front instead of solving partial differential equations. Experiments have been carried out on extraction of surface slick features from ERS-2 SAR images to substantiate the efficacy of the proposed fast level set method.

Sea Ice Deformation State From Synthetic Aperture Radar Imagery—Part II: Effects of Spatial Resolution and Noise Level

C- and L-band airborne synthetic aperture radar (SAR) imagery acquired at like- and cross-polarizations over sea ice under winter conditions is examined with the objective to study the discrimination between level ice and ice deformation features. High-resolution low-noise data were analyzed in the first paper. In this second paper, the main topics are the effects of spatial resolution and signal-to-noise ratio. Airborne high-resolution SAR scenes are used to generate a sequence of images with increasingly coarser spatial resolution from 5 to 25 m, keeping the number of looks constant. The signal-to-noise ratio is varied between typical noise levels for airborne imagery and satellite data. Areal fraction of deformed ice and average deformation distance are determined for each image product. At L-band, the retrieved values of the areal fraction get larger as the image resolution is degraded. The areal fraction at C-band remains constant. The retrieved average distance between deformation features increases both at C- and L-bands as the image resolution gets coarser. The influence of noise becomes noticeable if its level is equal or larger than the average intensity backscattered from the level ice. The retrieval of deformation parameters using simulated images that resemble ERS-2 SAR, Envisat ASAR, and ALOS PALSAR data products is discussed. Basic differences between real and simulated ERS-2 SAR images are analyzed.

Synthetic aperture radar interferometry observations of theM= 6.0 Orta earthquake of 6 June 2000 (NW Turkey): Reactivation of a listric fault

We study the coseismic surface displacement field due to the Orta earthquake of 6 June 2000, a moderate‐sized (Mw6.0) oblique‐slip event that took place on a previously unknown fault located about 70 km north of the capital, Ankara (Turkey), and about 35 km south of the North Anatolian Fault. We use European Space Agency ERS synthetic aperture radar (SAR) data to generate high‐resolution maps of the surface displacements by a two‐pass differential SAR interferometry method. The surface displacement field reaching up to 15 cm line of sight subsidence is captured in several coseismic interferograms from descending orbits and is inverted to determine the source parameters of the earthquake using elastic dislocations on rectangular fault surfaces with a nonlinear minimization procedure based on simulating annealing algorithm. Modeling of the coseismic interferograms indicates that the earthquake was associated with a shallow (&lt;6 km) left‐lateral oblique normal displacement that occurred on a north‐south striking, eastward dipping, listric fault trending at a high angle to the plate boundary, right‐lateral strike‐slip North Anatolian fault. Careful analyses of multiple interferograms together with the field observations allow us to infer the rupture geometry in fine detail. Modeling shows that coseismic slip occurs nearly only on the lower portion of the listric fault at a centroid depth of about 5 km but partially reaches to the surface along the surface trace of the Dodurga fault, in agreement with the field observations. We show that in the absence of field observations, additional measurements, or multiple interferograms that capture the surface deformation from different look angles, SAR interferometry alone may not be sufficient to constrain earthquake rupture geometry if there is no clear surface faulting. The results suggest that the Dodurga fault developed most probably as a result of a restraining bend along the North Anatolian fault and its left‐lateral kinematics is consistent with the stress regime that favors the right‐lateral North Anatolian fault.

Monitoring Urban Land Cover in Rome, Italy, and Its Changes by Single-Polarization Multitemporal SAR Images

This study contributes an assessment of the potential of single-polarization decametric synthetic aperture radar (SAR) images in classifying land cover within and around large urban areas and in monitoring their changes. The decision task is performed on a pixel basis and is carried out by supervised neural network algorithms fed by radar image features including backscattering intensity, coherence and textural parameters. Two configurations are considered: a short-term classification and change detection scheme intended for providing information in near-real time and a long-term scheme aimed at observing the urban changes at year time scales. We use a pair of interferometric images for the short-term case, while the long-term exercise utilizes two interferometric pairs and a fifth single acquisition. The images are acquired by the ERS SAR in late winter, spring and early summer over 836 square kilometers including Rome, Italy, and its surroundings. The accuracy of the short-term algorithm in discriminating seven types of surface is higher than 86%, while the accuracy of the long-term algorithm is beyond 88%. The many changes undergone by Rome from 1994 to 1999 have been identified by the postclassification comparison change detection procedure. The pixel-by-pixel analysis of the results has been carried out for a 160 square kilometers test area, obtaining a correct detection above 82% (less than 18% missed alarms and 0.3% false alarms).

ANN-Based Soil Moisture Retrieval over Bare and Vegetated Areas Using ERS-2 SAR Data

Active microwave remote sensing data (e.g., radar) can be used for estimation of soil moisture beneath the ground surfaces up to 0 to 5 cm depths. A number of analytical and empirical models are available that relate the synthetic aperture radar (SAR) data to the surface soil moisture. Each of these models has its own merits and demerits. In this paper, results obtained from a study on the application of artificial neural networks (ANN) for soil moisture retrieval from ERS-2 SAR data over bare and vegetated surfaces is presented. SAR images of three dates (i.e., July 28, 2003, March 29, 2004, and May 3, 2004) were acquired over a portion of the Solani river catchment in India. A feed forward back-propagation neural network was used for establishing the relationship between surface soil moisture and terrain as well as sensor variables. A maximum of seven input variables were considered for training the ANN. These are: Digital number (DN) or backscatter coefficient ( σ deg) (as the case may be) of each pixe...

Surface Wave Parameters Retrieval in Coastal Seas from Spaceborne SAR Image Mode Data

We have developed a retrieval scheme of surface wave parameters (wave height and wave propagation direction) from ERS Synthetic Aperture Radar (SAR) image mode data in coastal seas around Japan. In this study, we investigated the energy of simulated SAR spectrum at difierent wind speed using nonlinear wave-SAR imaging mechanism, derived the criteria to difierentiate swell from wind waves, and accordingly processed SAR images containing swell and wind waves in difierent way respectively. SAR spectra are converted to surface wave spectra of swell-dominated or wind-wave dominated cases. The SAR spectrum and SAR-derived wind speed are used for the derivation of surface wave spectrum. The wind-wave dominated case and swell- dominated case are difierentiated by the wind speed of 6m/s, and processed in difierent ways because of their difierent nonlinear degree. It is indicated that the cutofi wavelength for retrieval of the wind-wave dominated spectrum is proportional to the root of signiflcant wave height, which is consistent with the results of previous studies. We generated 66 match-ups coupling the SAR sub-images and the in-situ surface wave parameters, which were measured by the wave gauges installed in near-shore seas. Among them, the number of swell-dominated case is 57, and the number of wind-wave dominated case is 9. The SAR-derived and in-situ signiflcant wave heights agree well with the bias of 0.24m, the RMS error 0.92m and the correlation coe-cient of 0.66. The averaged absolute deviation of wave propagation directions is 18:4§, and the agreement tendency does not depend on the wave height. It is proven through the comprehensive validation that the developed SAR surface wave spectrum has high accuracy in the Japanese coastal seas.

Potential of Multitemporal ERS-2 SAR Imagery for Land Use Mapping in Coastal Zone of Shangyu City, China

Abstract Scarce land resources and growing population are compelling issues for intensively developing coastal zones in China. During the past 30 years, many coastal tidelands have been enclosed for cultivation and development. To plan and implement large-scale reclamation programs in coastal zones, timely and reliable information concerning the nature, extent and physicochemical characteristics of the coastal saline soils land is essential. Because extracting useful information from optical remote sensing imagery is often hampered by the presence of clouds and wet weather, in this study we used multitemporal European remote sensing satellite (ERS)–2 PRI synthetic aperture radar (SAR) images only for coastal land use mapping. The SAR multitemporal backscattering characteristics of main land use categories were first investigated after pseudocolor synthesizing of three temporal SAR images, extracting dikes and partitioning the study area into six subzones according to the reclamation years. Next, an iterat...

Spatial mapping of multi-year superimposed ice on the glacier Kongsvegen, Svalbard

AbstractGround-penetrating radar (GPR) and satellite ERS-2 synthetic aperture radar (SAR) are used to map the thickness and extent of the superimposed ice (SI) zone on the surge-type glacier Kongsvegen, Svalbard. GPR imagery shows sub-horizontal SI layers lying unconformably above a discrete boundary. Below this boundary, the ice has a GPR signature similar to that of ice further down-glacier in the ablation zone. This boundary is posited to represent the closing of crevasses that were created during the last surge of Kongsvegen in ∼1948. Open crevasses would have interrupted the formation of sheet layers of SI due to efficient vertical drainage of the snowpack. Aerial photographs suggest that the crevasses closed sometime in the period 1956–66. A classified SAR image from 2003 is used to delineate the extent of the SI zone. The SI extent in the SAR image agrees well with the SI zone mapped by GPR. Using the SI spatial depth distribution, we estimate the mean annual accumulation of superimposed ice to be 0.16 ± 0.06 m w.e. a−1 (locally up to 0.43 m a−1 w.e.). This corresponds to ∼15–33% of the local winter balance and ∼5–10% of the total winter balance measured since 1987.

Study on Ocean Wind Vector Retrieval from ERS‐2 SAR Image

AbstractSAR (Synthetic Aperture Radar) wind retrieval is a hot research topic in current Remote Sensing field. In this paper the principle of space borne SAR ocean wind retrieval and three related retrieval algorithms are introduced firstly. Then, the flowchart of the retrieval procedures is provided. As an example, ERS‐2 SAR image covering Hong Kong region acquired on May 7, 2002 is used for wind vector retrieval. The classic SAR Wind Direction Algorithm ‐ spectral method is improved, and applied for the retrieval. The wind direction thus estimated is however with 180º ambiguity. Buoy data collected by the Hong Kong Observatory are then used to resolve the uncertainty. Finally, the GMF (Geophysical Model Function)‐CMOD4 is adopted to estimate the wind speed at the height of 10 m above sea level. Compared with the data recorded by Hong Kong Observatory, the error in the wind direction and average wind speed are very small. The results show that accurate ADC (Analog to Digital Converter) compensation and image calibration, together with improved SWDA and CMOD4 algorithms, could offer high quality wind vector.

Classification of sediments on exposed tidal flats in the German Bight using multi-frequency radar data

We present a new method for the extraction of roughness parameters of sand ripples on exposed tidal flats from multi-frequency synthetic aperture radar (SAR) data. The method is based on the Integral Equation Model (IEM) which predicts the normalized radar cross-section (NRCS) of randomly rough dielectric surfaces. The data used for this analysis were acquired in the German Bight of the North Sea by the Spaceborne Imaging Radar-C/X-Band SAR (SIR-C/X-SAR) in 1994. In-situ measurements of the root-mean-squared (rms) height and the correlation length of the sand ripples clearly demonstrate a relationship between these roughness parameters and the C-band NRCS determined from an ERS SAR image. Using the IEM we have calculated NRCS isolines for the three frequency bands deployed by SIR-C/X-SAR (L, C, and X band), as a function of the rms height and the correlation length of the sand ripples. For each SIR-C/X-SAR image pixel these two roughness parameters were determined from the intersections of the NRCS isolines at different radar bands, and they were used for a crude sediment classification for a small test area at the German North Sea coast. Comparing our results with available sediment maps, we conclude that the presented method is very promising for tidal flat classification by using data from presently existing airborne and future spaceborne multi-frequency SAR systems.

High resolution (400 m) motion characterization of sea ice using ERS-1 SAR imagery

Using Synthetic Aperture Radar (SAR) images from ERS-1, we render high resolution motion fields of sea ice using a multi-resolution processing system. The results are provided at a 400 m resolution, which is an order of magnitude greater than the standard SAR motion products (5–10 km). An error propagation experiment shows a standard deviation of 1.3% day − 1 for the noise in invariant shear resulting from position uncertainties and processing techniques. We use this noise level to determine a significant lower threshold when identifying shear zone discontinuities. As example, a 24-day sequence of images is processed using this system to examine the development and evolution of a shear zone. This evolution is in response to the topographic steering caused by ocean circulation and wind forcing along a continental shelf break. In addition, we adapt the Line Integral Convolution (LIC) to depict flow patterns present in the motion field. Collectively, these motion products provide valuable descriptions of the non-rigid dynamics taking place within the sea ice. Our goal is to complement the existing RADARSAT Geophysical Processing System (RGPS) motion products and aid in the validation and further development of the most progressive “lead-resolving” sea ice models currently available. This form of sea ice visualization is important for understanding air–ice–sea momentum transfer processes that transcend through small-scale to large-scale fracture events with application to ship navigation.

Atmospheric Fronts along the East Coast of Taiwan Studied by ERS Synthetic Aperture Radar Images

Abstract The existence of quasi-stationary alongshore atmospheric fronts typically located 30–70 km off the east coast of Taiwan is demonstrated by analyzing synthetic aperture radar (SAR) images of the sea surface acquired by the European Remote Sensing Satellites ERS-1 and ERS-2. For the data interpretation, cloud images from the Japanese Geostationary Meteorological Satellite GMS-4 and the American Terra satellite, rain-rate maps from ground-based weather radars, sea surface wind data from the scatterometer on board the Quick Scatterometer (QuikSCAT) satellite, and meteorological data from weather maps and radiosonde ascents have also been used. It is shown that these atmospheric fronts are generated by the collisions of the two airflows from opposing directions: one is associated with a weak easterly synoptic-scale wind blowing against the high coastal mountain range at the east coast of Taiwan and the other with a local offshore wind. At the convergence zone where both airflows collide, air is forced to move upward, which often gives rise to the formation of coast-parallel cloud bands. There are two hypotheses about the origin of the offshore wind. The first one is that it is a thermally driven land breeze/katabatic wind, and the second one is that it is wind resulting from recirculated airflow from the synoptic-scale onshore wind. Air blocked by the mountain range at low Froude numbers is recirculated and flows at low levels back offshore. Arguments in favor of and against the two hypotheses are presented. It is argued that both the recirculation of airflow and land breeze/katabatic wind contribute to the formation of the offshore atmospheric front but that land breeze/katabatic wind is probably the main cause.

AN EFFICIENT MODELING WITH GA APPROACH TO RETRIEVE SOIL TEXTURE, MOISTURE AND ROUGHNESS FROM ERS-2 SAR DATA

One of the most important functions of radar remote sensing is to retrieve the soil moisture and surface parameters where surface parameters generally includes soil surface roughness and texture of soil (i.e.,% of coarse sand,silt and clay). Variation of soil moisture and surface parameters changes the soil permittivity, and affects the observation of the radar wave scattering (σ 0 ). How to invert the moisture and surface parameters from radar data has been one of the most interesting problems to be resolved. Still,very few reported work is available to retrieve the soil textures with radar data. Therefore,in present paper an attempt has been made to retrieve the soil textures with soil moisture and surface roughness from Synthetic Aperture Radar (SAR) data. In this case number of variables are more and it is difficult to invert and retrieve the various parameters. To overcome this difficulty,an approach based on Genetic Algorithm (GA) with inclusion of empirical modeling has been proposed to retrieve the soil moisture,roughness and soil texture with ERS-2 (European Remote Sensing) SAR (Synthetic Aperture Radar) data of Haridwar region of India. The retrieved surface parameters and moisture content with proposed approach show quite good agreement with observed values of soil moisture and surface parameters. This study infers that modeling with GA has great potential to retrieve several variables simultaneously with good results.

Early recognition of glacial lake hazards in the Himalaya using remote sensing datasets

Glacier recession in high-Himalayan catchments leads to the formation of moraine-dammed lakes on many debris-covered glacier tongues. Such lakes are hazardous to communities and infrastructure downstream because of their potential to breach catastrophically, and their early recognition is required if remedial efforts are to be timely and cost-effective. Whilst the development of supraglacial lakes is known to begin as a series of ponds that subsequently coalesce into a larger lake, the relationship between glacier dynamics and lake formation is not well understood. Using ERS-1 and ERS-2 Synthetic Aperture Radar (SAR) data, SPOT-5 optical imagery and historical aerial photography, information is presented on the dynamics and structure of glaciers in Tibet (China) and Nepal that drain the southern side of the Himalaya. Glacier velocity data derived from interferometry show that where lakes are developing on debris-covered tongues the ice is virtually stagnant (displacements < 5 m a − 1 ). Furthermore, elevation data from Digital Elevation Models (DEMs) derived from aerial photography and SPOT-5 HRS data reveal that supraglacial lake formation is prevalent where glacier surface gradients are less than 2° from the glacier terminus, supporting empirical observations from previous work. The resolution offered by the DEMs and SAR data allows variations in transverse glacier elevations and velocities to be detected, such that the pattern of lake development on an individual glacier can be identified. Whilst the glacier surface gradient provides the boundary conditions favourable for lake formation, local variations in glacier velocity and surface morphology between flow units control the precise location of lake growth. Integrating the surface gradient and velocity information into a single analysis highlights those glaciers that are particularly vulnerable to lake development over an expected decadal timescale. The wider application of these techniques, based on remote sensing data, is particularly suitable for ‘first-pass’ hazard assessments and for regions where field access is difficult due to severe terrain, political sensitivity or financial constraints.