ERS-1 Images Research Articles

Calving cycle of Ninnis Glacier over the last 60 years

Iceberg calving is one of the contributing ways for the mass loss from ice shelves in Antarctica; the calving cycles of most ice shelves are quite long. The mechanism of iceberg calving has not been well investigated because of the limited temporal coverage of satellite observations. The Ninnis Glacier (NG) has experienced three calving events in the past 60 years (1980–1982, 1998, and 2018), which provides an opportunity to capture the long-term pattern of calving for the first time. In our study, ARGON, Landsat, and ERS-2 images were combined with field measurements to characterize the evolution of the Ninnis Glacier, especially for the last calving event, which can be studied using high-quality observations. The time span was over 23 years for the 1st calving cycle and the average time span was ∼18.5 years for each of the last two cycles. Supported by satellite-derived strain rates and ocean currents obtained from a numerical ocean model, we conclude that the calving of the Ninnis Glacier Tongue (NGT) was driven by the continuous impact of ocean current on the advected glacier tongue. According to a comparison among the three calving events, the calving area of the last calving event was ∼750 km2, only half of the 1st calving event, with breaking locations closer to the grounding line. We attribute these changes to the reduction of fast ice in this region, which can be related to the local oceanographic conditions.

The pattern of surface deformations in the Dąbrowa Basin (Poland) based on PSInSAR analysis

Slow, long-term ground deformations in the Dąbrowa Basin (southern Poland) were identified based on ERS-1 , ERS-2 and ENVISAT Synthetic Aperture Radar (SAR) images that were processed by means of Permanent Scatterer SAR Interferometry (PSInSAR). The Dąbrowa Basin is a region where two major factors can affect surface stability: intensive coal exploitation and neotectonic processes. In this study, in order to clarify the origin of surface deformations, the authors propose applying a newly developed algorithm of spatio-temporal PSInSAR data analysis. This analysis revealed that subsidence is a characteristic feature of the Dąbrowa Basin. A significant correlation exists between slow, long-term ground deformations and the location of the main tectonic structure of this region. The proposed spatiotemporal analysis of the PSInSAR data additionally showed some degree of correlation between mining activity and the studied deformations. This interconnection is a significant achievement of this study since the deformation values determined by means of PSInSAR were identified in earlier works solely on the basis of Dąbrowa Basin neotectonics. Normal 0 21 false false false PL X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:Standardowy; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;}

Least-Square-Based Joint Coregistration Method for SAR Image Series and Its Application for PS-InSAR Processing

Joint coregistration (JC) approach, based on least square (LS) method, is proposed to improve the synthetic aperture radar (SAR) images' coregistration precision and persistent scatterer interferometric synthetic aperture radar (PS-InSAR) performance. Firstly, the image pairs with small spatial and temporal baselines are used to estimate image shifts to reduce the decorrelation effects. The SAR images are all positioned in spatial-temporal baseline plane and connected with the Delaunay triangulation method. Those arcs with long spatial and/or temporal baselines are deleted with an experienced threshold. Secondly, the shifts are estimated with arc-linked images by conventional coregistration approaches. However, the shifts of arc-unlinked images are still unknown even the arc-linked images are accurately coregistered. For this problem, we estimate the shifts of all the slave images with respect to the reference image from the shifts estimated by the short spatial and temporal baselines. LS method is used to tackle the problem of shifts' error propagation. Finally, all the slave images are resampled according to the estimated LS-method-based images' shifts. 44 ERS-2 images are used to test the performance of JC approach for PS-InSAR processing. The validity is illustrated by the amplitude and phase stability of PS candidates, as well as the deformation performance of PS-InSAR.

Permafrost Deformation Monitoring Along the Qinghai-Tibet Plateau Engineering Corridor Using InSAR Observations with Multi-Sensor SAR Datasets from 1997-2018.

As the highest elevation permafrost region in the world, the Qinghai-Tibet Plateau (QTP) permafrost is quickly degrading due to global warming, climate change and human activities. The Qinghai-Tibet Engineering Corridor (QTEC), located in the QTP tundra, is of growing interest due to the increased infrastructure development in the remote QTP area. The ground, including the embankment of permafrost engineering, is prone to instability, primarily due to the seasonal freezing and thawing cycles and increase in human activities. In this study, we used ERS-1 (1997–1999), ENVISAT (2004–2010) and Sentinel-1A (2015–2018) images to assess the ground deformation along QTEC using time-series InSAR. We present a piecewise deformation model including periodic deformation related to seasonal components and interannual linear subsidence trends was presented. Analysis of the ERS-1 result show ground deformation along QTEC ranged from −5 to +5 mm/year during the 1997–1999 observation period. For the ENVISAT and Sentinel-1A results, the estimated deformation rate ranged from −20 to +10 mm/year. Throughout the whole observation period, most of the QTEC appeared to be stable. Significant ground deformation was detected in three sections of the corridor in the Sentinel-1A results. An analysis of the distribution of the thaw slumping region in the Tuotuohe area reveals that ground deformation was associated with the development of thaw slumps in one of the three sections. This research indicates that the InSAR technique could be crucial for monitoring the ground deformation along QTEC.

SHORT PERIOD CHANGE DETECTION OF SPERCHIOS LOWER DELTA AREA USING SPACE RADAR IMAGES

Being highly dynamic by nature, due to their changing hydrological regime and to the encroachment of urbanization, industrialization and changing patterns in agriculture, reliable and timely information of coastal areas is a prerequisite for their effective management. The aim of this paper is to assess the use of ERS-2 SAR satellite data to detect short period changes in the case of the R. Sperchios coastal area that is located at the eastern part of the Maliakos Gulf (near the middle of the east coast of the Greek mainland). A Landsat 7 (ΕΤΜ+) image served as a reference for the interpretation of the ERS images. In order to highlight and detect the changes occurred in the study area two methods were applied. The first method is based on the creation of a Temporal Differentiate Image, consisted of the three ERS-2 images (Figure 1). The second method concerns the implementation of Principal Component Transform (PCT) on the three multitemporal scenes. The final images derived from the two different methods were compared and evaluated. Both methods didn't show any significant change along the coastline. PCT method illustrates more clearly the seasonal changes of crops in the lower delta area. Eventually, radar technology gave the opportunity to discriminate shallow areas, which does not appear in satellite optical data. Concurrently, the effect of wind direction was investigated.

Interferometric Stacking toward Geohazard Identification and Geotechnical Asset Monitoring

Geotechnical assets are those found along transportation environments and are made up of or supported by earth materials. A geotechnical asset management program aims to achieve life-cycle performance goals by maintaining the geotechnical assets in a safe, cost-effective, and timely manner. Interferometric synthetic aperture radar, a remote sensing technique that derives ground deformation information from satellite-based radar data, is proposed as a monitoring method in the context of geotechnical asset management. A total of 90 ERS-1, ERS-2, and ENVISAT radar images, acquired from 1992 through 2010, are processed using two interferometric stacking techniques to measure ground deformation along a railroad corridor. A local-scale study was first conducted over a known slide (S-1) where total displacements up to 6 cm were measured. Then a regional-scale study was performed to locate hazard zones. Six potential geo-hazard zones were identified along the railroad corridor based on five criteria: slope distance, slope height, slope angle, average downslope velocity, and total downslope displacement. Interferometric stacking is shown to be quite useful for geotechnical asset management, as this remote sensing technique allows for an indirect method of quantifying asset condition and allows for the long-term monitoring of geotechnical assets that a management program aims to achieve.

Adaptive Weibull Multiplicative Model and Multilayer Perceptron neural networks for dark-spot detection from SAR imagery.

Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies.

Fully Automatic Dark-Spot Detection From SAR Imagery With the Combination of Nonadaptive Weibull Multiplicative Model and Pulse-Coupled Neural Networks

Dark-spot detection is a critical step in oil-spill detection. In this paper, a novel approach for automated dark-spot detection using synthetic aperture radar imagery is presented. A new approach from the combination of Weibull multiplicative model (WMM) and pulse-coupled neural network (PCNN) techniques is proposed to differentiate between the dark spots and the background. First, the filter created based on WMM is applied to each subimage. Second, the subimage is segmented by PCNN techniques. As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approach was tested on 60 Envisat and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall data set, an average accuracy of 93.66% was obtained. The average computational time for dark-spot detection with a 512 × 512 image is about 7 s using IDL software, which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust, and effective. The proposed approach can be applied on any kind of synthetic aperture radar imagery.

Snow Cover Area Estimation Using Radar and Optical Satellite Information

Obtaining the seasonal variation of snow cover in areas of the Argentinian Andes is important for hydrological studies and can facilitate proper planning of water resources, with regard to irrigation, supply, flood attenuation and hydroelectricity. Remote sensors that work in the visible and infrared wavelength range are operational tools for monitoring the snow in clear skies. However, microwave satellites are able to obtain data regardless of atmospheric conditions. The advantage of using radar images is that they are very useful to obtain highly accurate parameters such as snow moisture depth, density and water equivalent resulting in improved forecasting models. In this paper, we analyze an ERS-2 image of the Andes mountain range in the northern region of the Neuquen province, Patagonia, Argentina. The objective was to obtain the spatial distribution of wet and dry snow and to compare these results with data from optical sensors (LANDSAT) in order to understand the topographic variables that influence the spatial distribution of wet snow. Optical information from sensors like LANDSAT TM 5 was analyzed to obtain fractional and binary snow indexes during a passage simultaneously with radar data. Surface temperature is used to study the association between the different types of snow altitudinal ranges and surface temperature. In this paper, we selected a scene on October 8th 2005. The entire methodology was systematized in a code implemented in IDL language.

WEIBULL MULTIPLICATIVE MODEL AND MACHINE LEARNING MODELS FOR FULL-AUTOMATIC DARK-SPOT DETECTION FROM SAR IMAGES

Abstract. As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

Mapping lakes for winter liquid water availability using SAR on the North Slope of Alaska

Synthetic aperture radar (SAR) satellite data were used to map late winter liquid water presence below ice for lakes within a 168,000km2 study area on the North Slope coastal plain of Alaska. Automated digital processing techniques were used to preprocess and classify 36 ERS-2 images acquired during April 2009. Lakes within the study area were extracted from the imagery and classified to produce frozen (no liquid water present) and unfrozen (liquid water present under ice) classes. Bathymetric data from 105 lakes were compiled from existing sources and were used as validation for the classification results based on an expected maximum ice depth of 1.6m. Lake locations with a depth of less than 1.6m were considered to be frozen while those greater than 1.6m were considered unfrozen. Bathymetric locations that were classified as frozen were found to be less than 1.6m in depth at 94% of the sample locations. Classification error within the unfrozen class was typically greatest within 50m of the frozen/unfrozen class boundary. Bathymetric locations that were greater than 1.6m in depth and which were more than 50m from the frozen/unfrozen class boundary were correctly identified as unfrozen at 98% of the verification locations. Shallow areas less 1.6m in depth were sometimes misclassified as unfrozen areas resulting in an overall classification accuracy of 89%. Three sources of classification error were considered; spatial mis-registration, ice depth variation, and talik presence. Mapping winter liquid water content within lakes on the North Slope coastal plain provides a useful tool for the evaluation of individual lakes during development planning and also provides a broad regional description of lake morphology that is relevant to landscape level physical and ecological interpretation.

Monitoring an earthfill dam using differential SAR interferometry: La Pedrera dam, Alicante, Spain

Surface displacement at the dykes of La Pedrera reservoir (SE Spain) has been measured by satellite differential Synthetic Aperture Radar (SAR) interferometry. At the main dyke, a displacement of about 13cm along the satellite line of sight has been estimated between August 1995 and May 2010, from a dataset composed by ERS-1, ERS-2 and Envisat-ASAR images. Two independent short-term processing tasks were also carried out with ERS-2/Envisat-ASAR (from June 2008 to May 2010) and TerraSAR-X (from August 2008 to June 2010) images which have shown similar spatial and temporal displacement patterns. The joint analysis of historical instrument surveys and DInSAR-derived data has allowed the identification of a long-term deformation process which is reflected at the dam's surface and is also clearly recognizable in the inspection gallery. The plausible causes of the displacements measured by DInSAR are also discussed in the paper. Finally, DInSAR data have been used to compute the long-term settlement of La Pedrera dam, showing a good agreement with external studies. Consequently, this work demonstrates the integration of DInSAR with in-situ techniques which helps provide a complete spatial vision of the displacements in the dam thereby helping to differentiate the causal mechanisms.

On the application of DInSAR to deformation monitoring in desert areas

The DInSAR technique is used for monitoring the desert height changes to study sandstorms. Hunshandake Sandy Land, as the test area, is one of the main sources of sandstorms in Beijing. In order to study the sandstorm source and its impact, a pair of EnviSat ASAR images of Oct. 11, 2005, and Oct. 26, 2004, is processed on the basis of analysis of six ERS-2 and EnviSat radar images. After the image configuration, flat earth effect correction, data filtering, phase unwrapping, and geo-coding, a deformation model over Hunshandake desert is built. According to the results, the height decreased in most areas and increased in a few areas, which basically coincides with the strong sandstorm appearing in Beijing in the Spring of 2005. The results show DInSAR has an important role in monitoring of desert surface deformation.

Large area forest stem volume mapping in the boreal zone using synergy of ERS-1/2 tandem coherence and MODIS vegetation continuous fields

ERS-1/2 tandem coherence was reported to have high potential for the mapping of boreal forest stem volume (e.g. Santoro et al., 2002, 2007a; Wagner et al., 2003; Askne & Santoro, 2005). Large-scale application of the data for forest stem volume mapping, however, is hindered by the variability of coherence with meteorological and environmental acquisition conditions. The traditional way of stem volume retrieval is based on the training of models, relating coherence to stem volume, with the aid of forest inventory data which is generally available for a few small test sites but not for large areas. In this paper a new approach is presented that allows model training using the MODIS Vegetation Continuous Fields canopy cover product (Hansen et al., 2003) without further need for ground data. A comparison of the new approach with the traditional regression-based and ground-data dependent model training is presented in this paper for a multi-seasonal ERS-1/2 tandem dataset covering several well known Central Siberian forest sites. As a test scenario for large-area application, the approach was applied to a multi-seasonal ERS-1/2 tandem dataset of 223 ERS-1 and ERS-2 image pairs covering Northeast China (~ 1.5 million km 2) to map four stem volume classes (0–20, 20–50, 50–80, and > 80 m 3/ha).

Assessing image processing techniques for geological mapping: a case study in Eljufra, Libya

Various image processing techniques were experimented with in this study to evaluate their efficiency for geological mapping in the Eljufra area of northwest Libya. Remote sensing data including multi-spectral optical Landsat Enhanced Thematic Mapper (ETM+), Synthetic Aperture Radar (ERS-2 SAR) and Digital Elevation Models (DEMs) extracted from the Shuttle Radar Topography Mission (SRTM) data were used to trace different lithological units as well as extracting geological lineaments in the study area. The study area is located in an arid environment mostly devoid of any vegetation. Most lithological and structural units are distinguishable based on their topographic form and spectral properties. Fusion of ETM+ and ERS-2 images was experimented with to further identify lithological units. Shaded relief techniques were implemented to enhance terrain perspective views and to extract geological lineaments. The results discriminated different rock units and modified formation boundaries and revealed new geological lineaments. Nine rock units were identified and plotted in the new geological map defined by the new boundaries. The dominant lineaments tend to run in the NNW-SSE and NNE-SSW directions. Analysis and interpretation of the lineaments provided information about the tectonic evolution of the study area.

First delimitation of areas affected by ground deformations in the Guadalfeo River Valley and Granada metropolitan area (Spain) using the DInSAR technique

A Differential Interferometric SAR (DInSAR) analysis of terrain displacements in the province of Granada (southern Spain) is presented here for two different study zones. The first zone concerns the Guadalfeo River Basin, where abundant landslides and unstable slopes were previously identified and inventoried on a GIS application. However, no instrumental quantification of landslide activity was available. Considering morphological criteria and field observations, these deep-seated landslides were considered to be “dormant” or moving extremely slowly. The second study zone corresponds to the Granada metropolitan area, where no previous information was available on any vertical movement. The analysis was based on ERS1 and ERS2 images, covering the period from 1993 to 2000. By using DInSAR, we made an initial qualitative assessment of movements on landsliding slopes in the Guadalfeo River Basin and also vertical land movements in the alluvial Quaternary sediments to the west and south of the Granada metropolitan area. The terrain instability assessment resulting from this research shows maximum annual velocities along the SAR line of sight (LOS) of 6 mm/yr for the Tablones landslide, and up to 13 mm/yr for the Albuñuelas village; where progressive differential settlement processes were established as the origin of the movement. In the case of the Granada metropolitan area, two sites were detected with subsidence affecting two villages: Santa Fe, located in the western part of the area, with an estimated average velocity of 8 mm/yr and Otura in the south of the area, with maximum velocities of 12 mm/yr. A description of geological features of the different sites, showing LOS ground displacement, is presented with a discussion of the application of the rates to landslide-activity assessment found, local ground conditions, or exploitation of subterranean water in urban areas.

Recent deformation at the junction between the North Luzon block and the Central Philippines from ERS-1 Images

The transfer of the major part of the motion between the Philippine Sea Plate and the Sunda block is accommodated along a north-west shear wide zone partly on the Philippine Fault and partly on the Sibuyan Verde Passage Fault (SVPF) as indicated by global positioning satellite and geological data. Given the limited motion along the SVPF and the important motion along the Philippine Fault, as well as the necessity of a connection between these faults and the southern Manila Trench, a transtensional motion along the northeast-southwest Macolod Corridor (MC) may be predicted. We used synthetic aperture radar European remote sensing (SAR ERS-1) images to analyze the volcano– tectonic features of this area, because these images are sensitive to minute textural or topographic contrasts resulting from small effects of recent deformation. In addition, they allow us to determine accurately the shape of the base of volcanic edifices and to detect linear clusters of very small adjacent cones. The results presented herein allow us to extend the features recognized earlier to a larger MC. Large faults actually connect the Philippine Fault to the Sibuyan Verde Passage Fault all across the Taal Volcanic Field. In addition to extension along north-east faults, we identify an important component of left-lateral strike–slip underlined by fault scarps, dykes, alignments of volcanoes and pull-apart basins, accompanied by extension along north-south faults. A relative chronology of the fractures and volcanic edifices is proposed. When compared to the existing ages of the volcanics, an evolution scheme of the area may be proposed, according to which extension shifted from a nearly north-south opening between 5 and 2 million years to a direction close to east-west at Present. The early north-south extension existed in the Marinduque Basin and may have migrated northward and rotated to the present MC.

Integrating Physical and Topographic Information Into a Fuzzy Scheme to Map Flooded Area by SAR.

A flood mapping procedure based on a fuzzy sets theory has been developed. The method is based on the integration of Synthetic Aperture Radar (SAR) measurements with additional data on the inundated area, such as a land cover map and a digital elevation model (DEM). The information on land cover has allowed us to account for both specular reflection, typical of open water, and double bounce backscattering, typical of forested and urban areas. DEM has been exploited to include simple hydraulic considerations on the dependence of inundation probability on surface characteristics. Contextual information has been taken into account too. The proposed algorithm has been tested on a flood occurred in Italy on November 1994. A pair of ERS-1 images, collected before and after (three days later) the flood, has been used. The results have been compared with the data provided by a ground survey carried out when the flood reached its maximum extension. Despite the temporal mismatch between the survey and the post-inundation SAR image, the comparison has yielded encouraging results, with the 87% of the pixels correctly classified as inundated.

Mine Subsidence Monitoring Using Multi-source Satellite SAR Images

Ground subsidence due to underground mining has posed a constant threat to the safety of surface infrastructure such as motorways, railways, power lines, and telecommunications cables. Traditional monitoring techniques like using levels, total stations and GPS can only measure on a point-by-point basis and hence are costly and time-consuming. Differential interferometric synthetic aperture radar (DINSAR) together with GPS and GIS have been studied as a complementary alternative by exploiting multi-source satellite SAR images over a mining site southwest of Sydney. Digital elevation models (DEMs) derived from ERS-1 and ERS-2 tandem images, photogrammetry, airborne laser scanning, and the Shuttle Radar Topography Mission were assessed based on ground survey data using levelling as well as GPS-RTK. The identified high quality DEM was then used in the DINSAR analysis. Repeat-pass acquisitions by the ERS-1, ERS-2, JERS-1, RADARSAT-1 and ENVISAT satellites were used to monitor mine subsidence in the region with seven active mine collieries. Sub-centimeter accuracy has been demonstrated by comparing DINSAR results against ground survey profiles. The ERS tandem DINSAR results revealed mm-level resolution.

A wavelet-based algorithm to estimate ocean wave group parameters from radar images

In recent years, new remote sensing techniques have been developed to measure two-dimensional (2-D) sea surface elevation fields. The availability of these data has led to the necessity to extend the classical analysis methods for one-dimensional (1-D) buoy time series to two dimensions. This paper is concerned with the derivation of group parameters from 2-D sea surface elevation fields using a wavelet-based technique. Wave grouping is known to be an important factor in ship and offshore safety, as it plays a role in dangerous resonance phenomenons and the generation of extreme waves. Synthetic aperture radar (SAR) data are used for the analysis. The wavelet technique is introduced using synthetic ocean surfaces and simulated SAR data. It is shown that the group structure of the ocean wave field can be recovered from the SAR image if the nonlinear imaging effects are moderate. The method is applied to a global dataset of European Remote Sensing satellite (ERS-2) wave mode data. Different group parameters including the area covered by the largest group and the number of groups in a given area are calculated for over 33 000 SAR images. Global maps of the parameters are presented. For comparison, classical 1-D grouping parameters are calculated from colocated wave model data showing good overall agreement with the wavelet-derived parameters. ERS-2 image mode data are used to study wave fields in coastal areas. Waves approaching the island of Sylt in the North Sea are investigated, showing the potential of the wavelet technique to analyze the spatial wave dynamics associated with the bottom topography. Observations concerning changes of wavelength and group parameters are compared to linear wave theory.