The seasonal snow cover is an important resource in mountain regions such as the Alps, the monitoring of which is crucial for hydrology and water management. We present a portfolio of homogenized products of physical snow properties including snow extent, melt extent and state, and snow mass. The algorithm for monitoring snow extent exploits the available spectral bands of optical sensors and accounts for variations of illumination in mountains. It generates consistent snow products from different optical sensors supporting the combined use of the products. SAR data are used for monitoring the melt extent and state of the snowpack. We intercompared three algorithms in Alpine areas that are based on change detection and assessed the performance. For retrieving snow accumulation SAR interferometry is a promising tool. The procedure has been tested in the Alps using C- and L-Band SAR airborne and satellite data. Performance and critical issues have been checked in the context of field campaigns. These activities support preparations for snow mass monitoring by means of future interferometric missions.

The time-varying areal extent and duration of surface melt on ice sheets are important parameters for climate and cryosphere research and key indicators of climate change in polar regions. To evaluate snowmelt dynamics and melting/refreezing processes in Greenland and Antarctica, we developed and implemented an algorithm for generating time-series of surface melt extent and melt phases (dry, wet refreezing) based on the analysis of continuous time series of C-band active microwave satellite data. Our results, based on METOP ASCAT scatterometer and Sentinel-1 SAR data, demonstrate the excellent capability of these missions for operational monitoring of snowmelt areas, providing a consistent climate data record on the presence of liquid water in snow and firn areas of Greenland and Antarctica for studying surface melt processes and ice sheet mass loss.

Comprehensive Ice velocity observations are essential for estimating ice sheet discharge and mass balance and are key input for modelling ice dynamic processes in response to climate warming. Based on Sentinel-1 SAR imagery we generate high-resolution ice velocity maps at 50 m posting over the ice sheets by combining SAR interferometry (InSAR) and offset-tracking (OT). The InSAR method provides improved accuracy particularly in the slow-moving interior of the ice sheets at higher resolution but requires crossing satellite acquisitions as well as image pairs with adequate coherence. On zones without crossing orbits our processing line uses the velocity vector derived from INSAR and flow direction from OT to optimally fill in gaps. Fast moving areas where coherence is not preserved are filled with OT velocity observations. The added value of the new ice velocity maps is assessed by intercomparison with operational ice velocity products and in-situ GPS data. Significant improvement compared to current products are achieved in interior parts of the ice sheets, for example helping to better constrain boundaries between ice drainage basins.

In March 2021 a field campaign was conducted in the Austrian Alps exploring the application potential and performance of snow mass (snow water equivalent, SWE) retrievals by means of repeat-pass radar interferometry (RP-InSAR). Multiple repeat-pass acquisitions were obtained with an airborne polarimetric C-band and L-band SAR, covering days without snowfall, as well as two snowfall events of different intensity. SWE maps, deduced from the observed change of the RP-InSAR phase delay in the snowpack, show good agreement with field measurements. Whereas L-band data are well applicable for SWE mapping of both snowfall events, the 2 π phase ambiguity and low coherence prevent the use of C-band data for the snowfall event of high intensity. The analysis of the campaign data is going on, addressing among other topics the application of RP-InSAR for SWE monitoring within the planned L-band SAR mission ROSE-L of the European Copernicus program and by means of geostationary C-band SAR as proposed for the Hydroterra mission.

Within the framework of European Space Agency (ESA) activities, several campaigns were carried out in the last decade with the purpose of exploiting the capabilities of multifrequency synthetic aperture radar (SAR) data to retrieve snow information. This article presents the results obtained from the ESA SnowSAR airborne campaigns, carried out between 2011 and 2013 on boreal forest, tundra and alpine environments, selected as representative of different snow regimes. The aim of this study was to assess the capability of X- and Ku-bands SAR in retrieving the snow parameters, namely snow depth (SD) and snow water equivalent (SWE). The retrieval was based on machine learning (ML) techniques and, in particular, of artificial neural networks (ANNs). ANNs have been selected among other ML approaches since they are capable to offer a good compromise between retrieval accuracy and computational cost. Two approaches were evaluated, the first based on the experimental data (data driven) and the second based on data simulated by the dense medium radiative transfer (DMRT). The data driven algorithm was trained on half of the SnowSAR dataset and validated on the remaining half. The validation resulted in a correlation coefficient$R \simeq 0.77$between estimated and target SD, a root-mean-square error (RMSE)$\simeq 13$cm, and bias = 0.03 cm. ANN algorithms specific for each test site were also implemented, obtaining more accurate results, and the robustness of the data driven approach was evaluated over time and space. The algorithm trained with DMRT simulations and tested on the experimental dataset was able to estimate the target parameter (SWE in this case) with$R =0.74$, RMSE = 34.8 mm, and bias = 1.8 mm. The model driven approach had the twofold advantage of reducing the amount ofin situdata required for training the algorithm and of extending the algorithm exportability to other test sites.

The Sentinel-1 acquisition planning for polar regions provides almost uninterrupted observations of the Greenland Ice Sheet margin, key regions in Antarctica and other polar ice masses. The satellite constellation has thereby changed the landscape for satellite Earth observation (EO) in the polar regions, providing excellent opportunities for operational monitoring of key climate variables including ice velocity and glacier discharge. Based on Sentinel-1 SAR imagery, an archive of ice velocity maps covering the polar regions has been generated, encompassing the entire mission duration. The ice velocity maps, complemented with ice thickness and other EO datasets, form the basis for deriving ice flow, discharge fluctuations and trends at sub-monthly to multi-annual time scales, providing key input for ice dynamic and climate modelling. Our results underscore the value of long-term comprehensive monitoring of the polar ice masses, which is vital to gain insight for predicting their response to ongoing climate and ocean warming.

This paper provides a compact overview of Harmony, an Earth Explorer 10 mission candidate dedicated to the observation of dynamic deformations of ice, solid earth and ocean surfaces. Harmony consists of two receive-only small Synthetic Aperture Radar (SAR) satellites using Sentinel-1D as illuminator, which will alternate close formation phases, dedicated to single-pass cross-track interferometry, with StereoSAR phases dedicated to the study of ocean surface motion and 3-D land surface deformations.

The Sentinel satellite missions of the European Copernicus programme provide comprehensive data for long-term routine observations of the global environment. A key parameter for climate monitoring, hydrology and water management is the seasonal snow cover. We developed, implemented and tested a novel approach for monitoring snow extent and snowmelt area, exploiting the synergy of imaging radar of the Sentinel-1 mission and multispectral optical imagery of the SLSTR sensor on Sentinel-3. We describe the processing steps and algorithms for generating the synergistic snow cover product and show examples for snow cover maps over Europe based on single mission data as well as the final synergistic product.

Recent glacier surface elevation changes are obtained with unprecedented coverage and accuracy using multitemporal bistatic InSAR DEMs acquired by the TanDEM-X mission launched in 2010 and still ongoing. The geodetic method is used to compute the mass balance and the corresponding contribution to sea level rise. The investigated glaciers are located in the Northern and Southern Patagonian Icefields (NPI, SPI), which are extremely dynamic and underwent strong downwasting in the last decades. The uncertainty of the results is assessed, also by considering critical aspects such as radar signal penetration in snow and ice.

There is a long-stranding need of reliable space-borne observations on snow mass. Current satellite sensors and data products are largely unable to meet requirements presented in particular by numerical prediction and watershed management. Consequently, several concept studies have been initiated to address these specific needs, outlining possibilities for future space sensors focusing on retrieval of snow mass and other characteristics of the terrestrial cryosphere. The results of these of-going mission concept studies are presented and discussed. Several possible sensor options are presented, which would address diverse needs on either hemispheric or regional scales.

This paper provides a compact overview of SESAME, a mission concept in which two receive-only small Synthetic Aperture Radar (SAR) satellites flying in close formation would allow single-pass interferometric observations using Sentinel-1 as transmitter.

SESAME (SEntinel-1 SAR companion Multistatic Explorer) is a passive SAR satellite mission proposed for the ESA Earth Explorer Program. SESAME comprises two receive-only C-band SAR satellites flying in close formation to build a single-pass SAR interferometer (SP-InSAR) using the active signal of the European Sentinel-1 satellite. The SESAME mission addresses applications in geoscience and climate research that require repeat measurements of high precision elevation data over land surfaces including ice covered areas and forests, exploiting the SP-InSAR and multistatic observation geometry of the satellite formation. The objectives, the measurement approach and geo-biophysical products of the mission are described.

We compare ice elevation from TanDEM-X Raw DEMs of summer 2014 and from the SRTM C-band DEM of summer 2000 over the Northern Patagonian Icefield (NPI) in order to obtain a detailed map of ice elevation change rates over the last 14 years. The geodetic method is used to compute the mass balance for this region and for the nearby Southern Patagonian Icefield (SPI). The method is outlined along with the error budget estimation. The backscattering coefficient of the data is analyzed in order to exclude elevation biases due to signal penetration in snow and firn.

In this paper, we report results from the analysis of 3-D L-band airborne synthetic aperture radar (SAR) acquisitions acquired in March 2014 over the Mittelbergferner glacier, Austrian Alps, during the European Space Agency (ESA) campaign AlpTomoSAR. The campaign included coincident in situ measurements of snow and ice properties and ground-penetrating radar (GPR) data acquired at 600 and 200 MHz over a total length of 18 km. Radar data were acquired by repeatedly flying an L-band SAR along an oval racetrack at an altitude of about 1300 m over the glacier, such that two data stacks from opposite views are obtained. Data from all passes were coherently combined to achieve 3-D resolution capabilities, resulting in the generation of 3-D tomographic SAR (TomoSAR) cubes, where each voxel represents L-band radar reflectivity from a particular location in the 3-D space at a spatial resolution on the order of meters. TomoSAR cubes were finally corrected to account for wave propagation velocity into the ice, which was a necessary step to associate the observed features with their geometrical location, hence enabling a direct comparison to GPR data. The TomoSAR cubes show the complexity of the glacier subsurface scattering. Most areas are characterized by surface scattering in proximity of the ice surface, plus a complex pattern of in-depth volumetric scattering beneath and scattering at the ice/bedrock interface. Various subsurface features observed in GPR transects at 200 MHz clearly showed up in TomoSAR sections as well, particularly firn bodies, crevasses, layer transitions, and bedrock reflection down to 50 m below the ice surface.

Recent studies, which were carried out within the framework of ESA's CoReH2O Phase-A mission, demonstrated that multi-frequency SAR data are able to quantify the amount of snow mass on land or glaciers (SWE). On the other hand the presence of forest has a significant impact on the propagation of the radar signal, depending on its structure, biomass, water content and cover fraction. In particular for dense forest, scattering of vegetation strongly hides the signal from snow and, consequently, compromises the sensitivity to snow parameters. A method for the compensation of the vegetation effect for the SWE retrieval in boreal forests is presented in this research. The procedure is based on the possibility to separate the scattering contribution from soil and vegetation from the data itself using ancillary information. The compensation follow through the estimation of the direct scattering from vegetation by using a minimization technique. Moreover, using a time series of backscatter images, this method is able to monitor the evolution of soil and vegetation status changes along the season, and improve the quality of the SWE retrieval algorithm.

The TanDEM-X/TerraSAR-X satellite formation, applying bistatic radar interferometry, delivers precise, spatially detailed topographic data, an excellent basis for mapping glacier volume change. Repeat pass data of these satellites are used for mapping glacier motion, key information for investigating the dynamic response of glaciers to changing boundary conditions. The synergistic analysis of these data sets provides main glacier parameters: the total net mass balance at annual and multi-annual intervals, the surface mass balance providing the link to atmospheric forcing, and ice export due to calving which is sensitive to changes in ice dynamics and ocean properties. The methods and capabilities of the TanDEM-X mission for delivering these parameters are described. The application is demonstrated for outlet glaciers of the Antarctic Peninsula that have been subject to major dynamic instability in recent years after collapse of buttressing ice shelves.

In this paper we present results from the tomographic analysis of L-Band SAR data acquired in February/March 2014 over the Mittelbergferner glacier, Austrian Alps, during the ESA campaign AlpTomoSAR. The campaign includes coincident in-situ measurements of snow and ice properties, as well as high-frequency Ground Penetrating Radar (GPR) data acquired over a total length of 18 km. The analyses of three-dimensional TomoSAR data cubes shows the complexity of the glacier sub-surface scattering. Most areas are characterized by surface scattering in proximity of the Lidar surface, plus a complex pattern of in-depth volumetric scattering beneath. Various subsurface features observed in GPR transects at 600 MHz and 200 MHz clearly showed up in TomoSAR sections as well. In particular: firn bodies, crevasses, and even the bedrock down to 50 m below the ice surface.

We compare ice elevation from a TanDEM-X DEM of September 2013 and the SRTM DEM of 2000 over the main glaciers of the Northern Patagonia Icefield (NPI) in order to quantify ice change rates over the last 13 years. The applied procedure and the obtained results are discussed. In order to have a more comprehensive picture of ice dynamics for this region, ice flow velocity maps for the S. Quintin and S. Rafael glaciers are obtained from feature tracking applied to TerraSAR-X high resolution repeat pass images.

Spatial and temporal characteristics of Ku- and X-band backscatter signatures of Alpine snow are discussed and related to in situ snow observations. The radar data have been acquired with the airborne SnowSAR sensor over three test sites in the Austrian Alps during the AlpSAR campaign in winter 2012/13. An example for inversion of backscatter images in terms of snow water equivalent (SWE) is presented. The backscatter signatures of three test sites in different elevation zones show significant differences in terms of mean values and temporal trends during the winter season. These variations can be attributed to snow structure and to properties of the medium below the snow pack.

We compare ice elevation from TanDEM-X DEMs of 2011/2012 and SRTM DEM of 2000 over the Southern Patagonia Icefield (SPI) in order to quantify the volume loss of the icefield over the last decade. The map of elevation change rate is discussed. Detailed results are shown for two glaciers: Jorge Montt and Pio XI, exhibiting opposite trends in elevation and front position.

The CoReH2O mission design is mature; there are two viable technical configurations, and the breadboards of key hardware components, such as the dual-polarized antenna array feeds and high power amplifiers have been built and tested. The baseline retrieval algorithm has been intensively tested using simulated and experimental data. The tests confirm that the threshold performance for SWE products can be met under a wide range of snow conditions. Data from further field campaigns by the airborne SnowSAR acquired Austria, Canada, and Alaska from November 2012 through April 2013 are being analysed to investigate retrieval performance over alpine, glacier and tundra terrains.

Observations of ice flow velocity with TerraSAR-X were carried out over main outlet glaciers of the Southern Patagonia Icefield (SPI) since 2008 by means of amplitude correlation technique. Velocity data are required to estimate the ice export due to calving. Furthermore we compare ice elevation from a TanDEM-X DEM of 2011 and from an SRTM DEM of 2000 in order to quantify the volume loss of these glaciers over the last decade. Results are shown for three glaciers of the central section of SPI, exhibiting distinct differences in the observed trends for surface topography and ice velocity.

Observations of the 3D ice velocity field are important for studies of glacier hydraulics and for modeling the dynamic response of glaciers to changing boundary conditions. A method for 3D ice velocity retrieval from repeat pass SAR data of crossing orbits applying offset tracking in amplitude images is presented. In contrast to the conventional technique for ice motion mapping which assumes surface-parallel flow, this method delivers the true velocity vector. The procedure is validated using in-situ GPS data on an outlet glacier of the Vatnajökull ice cap in Iceland.

The COld REgions Hydrology High-resolution Observatory (CoReH2O) satellite mission was selected for detailed scientific and technical studies within the Earth Explorer Programme of ESA. The sensor is a dual frequency SAR, operating at 17.2 GHz and 9.6 GHz, VV and VH polarizations The mission will deliver spatially distributed snow and ice observations to improve the representation of the croysphere in hydrological and climate models. Primary parameters are the extent and water equivalent (SWE) of the snow pack and snow accumulation on glaciers. Scientific preparations of the mission include the development and testing of algorithms for retrieval of snow parameters, studies on synergy of CoReH2O-type snow products with passive microwave measurements, the assimilation of satellite snow data in process models, and field experiments. Performance of retrievals for snow extent and SWE was tested with simulated and experimental data, including Ku- and X-band SAR images of the airborne SnowSAR system.

Snow extent and water equivalent (SWE) on land and snow accumulation on glaciers are the main parameters to be delivered by the Cold Regions Hydrology High-resolution Observatory (CoReH2O) satellite. Detailed scientific and technical studies for the mission are going on within the Earth Explorer Programme of ESA. The CoReH2O sensor is a dual frequency SAR, operating at 17.2 and 9.6 GHz, VV and VH polarizations. A main task for mission preparation is the development and validation of algorithms for retrieval of snow parameters. A constrained minimization approach is proposed for SWE retrieval, matching backscatter computed with a radiative transfer model and measurements in the four SAR channels by iterating for SWE and snow grain size. The algorithm was validated with simulated and measured backscatter data. The tests confirm the feasibility of the retrieval approach and help to quantify the requirements for statistical background information which is needed for constraining the solution.

In this paper, how typical snowpack parameters with layering processes affect to the sensitivity of X- and Ku-band backscatter to the increase of SWE (Snow Water Equivalent) was analyzed. A particular motivation of this work was to contribute to the development of the geophysical algorithm of CoReH2O, a proposed ESA SAR mission currently in Phase A [1][2]. DSLDMRT forward backscatter model for microwave backscatter from snow covered terrain was used in analysis. The software is based on a second order radiative transfer model using the dense medium approach [3]. The analyses showed that the layering of snowpack changes the sensitivity of backscatter to SWE. A layer of refrozen at the bottom of snow pack (resulting from thaw-refreeze cycles at early winter) can cause a negative correlation of backscatter with the increase SWE for the beginning of the dry snow accumulation period. The positive correlation between snow grain size and SWE, typical for the temporal metamorphosis, increases the correlation between SWE and backscattering coefficient.

We report on results from spaceborne velocity and topography measurements of the Drygalski glacier, Antarctic Peninsula. For our analysis we use a time series of TerraSAR-X data acquired between 2007 and 2010 which enables us to perform an error analysis and to determine higher order velocity parameters such as acceleration. Our estimated accuracy for velocity estimation is on the order of 2 cm/day and we find a weak slow down at the terminus of the glacier. Very first TanDEM-X single pass interferometric data sets acquired in 2010 allow us to reconstruct the 3D-glacier topography with unprecedented accuracy, delivering both, surface topography and roughness.

The acquisition of Snow Water Equivalent (SWE) at spatial resolutions higher than those of the present methods relying on inversion of coarse-scale passive microwave observations is a possible application for space-borne SAR imagery. The presented experimental campaign NoSREx (Nordic Snow Radar Experiment) was initiated to contribute to the knowledge of snowpack backscattering and emission properties, in particular, to help develop methods to retrieve SWE from high-resolution two-frequency SAR observations (at X and Ku band). Another objective was to provide data for studies exploring the synergistic use of active and passive microwave observations for monitoring of snow properties. The NoSREx campaign began in November 2009, and has recently concluded a second winter period of observations.

The COld REgions Hydrology High-resolution Observatory (CoReH2O) satellite mission has been selected for detailed scientific and technical studies within the ESA Living Planet Programme. The mission addresses the need for distributed snow and ice observations to improve the representation of the cryosphere in climate models and the prediction of the water cycle. The sensor is a dual frequency SAR, operating at 17.2 GHz and 9.6 GHz, VV and VH polarizations. This configuration enables the decomposition of the scattering signal for retrieving snow mass (SWE) and other physical properties of snow and ice. A major task for mission preparation is the development and testing of algorithms for SWE retrieval. The baseline algorithm applies a constrained minimization approach, matching forward computed and measured backscatter by iterating for SWE and effective grain size of the snow volume. Experimental campaigns on Kuand X-band backscatter of snow deliver important information for retrieval development and validation.

Ice velocities mapped by means of TerraSAR-X images in combination with surface elevation profiles measured by the altimeter system of ICESat are used to estimate glacier thinning and the increased calving flux after collapse of northern Larsen Ice Shelf on the Antarctic Peninsula in 1995 and 2002. InSAR analysis of one-day repeat pass SAR images from the ERS-l/ERS-2 tandem mission of 1995 and 1999 are these basis for retrieving the mass fluxes in the pre- collapse state. Applications of the various satellite data are shown for analysing the mass deficit and ice flow properties of Crane Glacier after disintegration of Larsen-B Ice Shelf. The ice flow acceleration shows a similar pattern for all calving glaciers on Larsen_B. The highest acceleration is observed at the front, decreasing upstream. Due to dynamic thinning at the frontal sections all main glaciers are now floating. This condition and the ongoing mass depletion will cause further frontal retreat in the coming years.

The main aim of this work is to adapt the ratio-technique for snow cover mapping developed for C-band to the X-band and high resolution COSMO-SkyMed images. This algorithm, aimed at detecting wet snow, is based on the difference in backscattering coefficients between snow- covered areas in winter images and snow-free summer images. For these purposes, a series of COSMO-SkyMed acquisitions (Stripmap PingPong mode, dual polarizations VV-VH) has been planned and acquired over the test site located in South Tyrol (Northern Italy) in correspondence of the melting and winter season. Contemporary to radar passes field campaigns have been performed. The objective is to test the sensitivity of X-band data to different snow conditions. An analysis has been carried out to find the most suitable filtering technique which allows a clearer distinction of distributions of backscattering coefficients of snow-covered and snow-free areas. Based on this analysis a first map of snow from the images acquired on 26-27 April 2010 (wet snow) was derived and compared with snow cover area derived from LANDSAT ETM+ of 20-04-2010 based on NDSI. Further statistical analysis will be carried out also considering the new acquisitions.

SIGNAL is an innovative earth exploration mission proposal with the main objective to estimate accurately and repeatedly topography and topographic changes associated with mass change or other dynamic effects on glaciers, ice caps and polar ice sheets. Elevation measurements are complemented with glacier velocity measurements, providing valuable additional information for a better understanding of the hydrology of glacierized basins and of the Arctic and Antarctic water cycle. SIGNAL is capable of monitoring all critical regions with a high spatial resolution and an adequate revisit time. This paper gives an overview about the actual mission design status and provides a brief description of the topography (DEM - digital elevation map) self-calibration strategy and the estimated global interferometric performance.

In preparation of the satellite mission CoReH2O, one of the three missions selected for scientific and technical feasibility studies within the Earth Explorer Programme of the European Space Agency, experimental and theoretical studies started in order to investigate backscatter properties of snow covered terrain and improve the methods for retrieval of snow physical properties from SAR data. The aim of this paper is to investigate the impact of vegetation in the retrieval of snow parameters from backscattering measurements. First a radiative transfer model, able to simulating scattering from a vegetated snow-covered terrain was developed and implemented. Lastly, a sensitivity analysis on snow and vegetation parameters was conducted for coniferous forest. Results confirm that with increasing biomass the sensitivity to SWE strongly decreases. Moreover when biomass is in the 0-150 m3/ha range a procedure to correct the vegetation effect in the SWE retrieval algorithm is suggested.

We present initial results from an experimental campaign aiming to acquire a comprehensive, full-snow season dataset of simultaneous backscatter and brightness temperature measurements of snow covered ground. The campaign is a part of Phase A activities in support of the proposed CoReH2O mission, aiming both to contribute to investigations on interpreting snow properties from active microwave observations, and to explore the possibilities for synergistic use of active measurements with existing passive microwave instruments. The campaign period covers the winter season of 2009-2010. Microwave observations are complemented by detailed in situ data of snow cover properties.

Snow is a critical component of the global water cycle and climate system, and a major source of water supply in many parts of the world. There is a lack of spatially distributed information on the accumulation of snow on land surfaces, glaciers, lake ice, and sea ice. Satellite missions for systematic and global snow observations will be essential to improve the representation of the cryosphere in climate models and to advance the knowledge and prediction of the water cycle variability and changes that depend on snow and ice resources. This paper describes the scientific drivers and technical approach of the proposed Cold Regions Hydrology High-Resolution Observatory (CoReH2O) satellite mission for snow and cold land processes. The sensor is a synthetic aperture radar operating at 17.2 and 9.6 GHz, VV and VH polarizations. The dual-frequency and dual-polarization design enables the decomposition of the scattering signal for retrieving snow mass and other physical properties of snow and ice.

An incoherent amplitude correlation approach is used to derive ice motion fields of three major outlet glaciers of the Patagonia Icefields. High resolution repeat pass TerraSAR-X data of 2008 and 2009 were analyzed. The strong gradients in ice velocity of the terminus of San Rafael glacier, ranging from 2 to 16 m d-1, were captured well. Significant acceleration of the ice flow and losses in mass were observed for Upsala glacier.

Techniques for the retrieval of snow properties from Ku- and X-band radar backscatter measurements were investigated. The work contributes to feasibility studies for the CoReH2O satellite mission of ESA for which a dual frequency SAR, operating at Ku-band (17.2 GHz) and X-band (9.6 GHz), VV and VH polarizations, is proposed. A main parameter to be measured is the snow water equivalent (SWE). For the retrieval of SWE it is necessary to separate the backscatter contributions of the snow volume and the background target and to account for effects of snow grain size. The current version of the SWE retrieval algorithm applies the maximum likelihood approach matching radiative transfer forward computations with measured backscatter data. An application example for SWE retrieval is shown for the Cold Land Processes Experiment (CLPX-II) in Alaska, using Ku-band data of the NASA-JPL PolScat and X-band data of the TerraSAR-X satellite as input.

The Aerosol Land Mission (AERL) has been investigated within a study on concepts for advanced techniques that are compatible with implementation on a small satellite in the 150–200 kg range of total mass. AERL addresses the need for improved observations of atmospheric aerosol over land surfaces for air pollution control and climate research. The mission employs two instruments for multidirectional and multispectral measurements of reflected solar radiance. For measuring the columnar aerosol optical depth and properties a triple-view spectral imager with narrow band-pass filters in the 420 nm–910 nm spectral range is applied. Information on vertical layering of aerosol is obtained by dual view measurements of a grating spectrometer in the 757 nm–775 nm spectral range (oxygen A band).

The capabilities of TerraSAR-X data for feature tracking by amplitude correlation over glacier surfaces are investigated. Methodical aspects of the amplitude correlation approach are described. The TerraSAR-X based velocity fields are compared with former InSAR derived velocities and field measurements on three outlet glaciers on the South Patagonia ice field.

In preparation of the satellite mission CoReH2O, one of the six missions which has been selected for scientific and technical feasibility studies within the Earth Explorer Programme of the European Space Agency, experimental and theoretical studies started in order to investigate backscatter properties and improve the methods for retrieval of snow physical properties from SAR data. The aim of this paper is to investigate the impact of vegetation in the retrieval of snow parameters from backscattering measurements at the X- and Ku-bands. First the key vegetation types found in snow covered regions where identified on the basis of available global scale data base. A model able to simulating scattering from a vegetated snow-covered terrain was then developed and implemented. Lastly, a sensitivity analysis to vegetation parameters was conducted on sparse vegetation and coniferous forest.

The COld REgions Hydrology High-resolution Observatory (CoRe-H2O) satellite mission has been selected for scientific and technical studies within the ESA Earth Explorer Programme. The mission addresses the need for spatially detailed snow and ice observations in order to improve the representation of the cryosphere in climate models and to improve the knowledge and prediction of water cycle variability and changes. CoRe-H2O will observe the extent, water equivalent and melting state of the snow cover, accumulation and diagenetic facies of glaciers, and properties of sea ice and lake ice. The sensor is a dual frequency SAR, operating at 17 GHz and 9.6 GHz, VV and VH polarizations. This configuration enables the decomposition of the scattering signal for retrieving physical properties of snow and ice. Scientific preparation activities include experimental field campaigns, improvement of radar backscatter models, and the development of inversion algorithms.

The retrieval of snow parameters, and snow water equivalent in particular, are key parameters in hydrology and climate research. Theory, ground-based signature research and analysis of spaceborne scatterometry suggests that the high- frequency combination of Ku- and X-band active microwave sensors is an excellent tool for the retrieval of snow physical properties. In order to validate this, a snow measurement campaign was carried out with the University of Cranfield's portable Ground-Based Synthetic Aperture Radar (GB-SAR) System during the winter of 2006/7 at two test-sites in the Austrian Alps close to Innsbruck. Fully polarimetric X-and Ku-band backscatter signatures were acquired over a range of incidence angles (~20deg-70deg), with the active sensor operating predominately in SAR mode, but occasionally also in InSAR mode. Microwave signatures and snow properties were measured on seven different dates. Detailed complementary meteorological and snow metamorphic conditions were also recorded.

Taking into account the needs for improved, spatially detailed observations of snow and ice in climate research, hydrology, and glaciology, the satellite mission COld REgions Hydrology High-resolution Observatory, CoRe-H2O, was proposed to ESA. As payload a co- and cross-polarized Ku-band (17.2 GHz) and X-band (9.6 GHz) SAR was selected, because of its sensitivity to dry snow, thin sea ice, and the metamorphic state of snow, firn and ice on glaciers and ice caps. A cost-effective ScanSAR scheme with parabolic reflectors (each with multiple beams) is proposed fulfilling the requirements for swath width, spatial resolution and radiometry. The mission has been selected by ESA for further scientific and technical studies in the frame of the Earth Explorer Satellite Programme.

Time series of satellite radar image data of Envisat ASAR were used to study the retreat of ice shelves and glaciers at northern Larsen Ice Shelf,Antarctic Peninsula, up to March 2007. After the disintegration event in March 2002, the small remaining ice shelf section of Larsen B decreased further in area. The retreat of grounded glacier ice continued also. The glacier velocities above previous Larsen B increased further since 2004, but the acceleration has been smaller than in the first two years after the collapse in 2002. Ice export increased rapidly after the glaciers started to calve directly into the ocean. The sea level contribution due to discharge of grounded ice above the disintegrated ice shelf sections amounts to about 6% of the present glacier and ice sheet contribution to sea level rise.

Capabilities of the MEdium Resolution Imaging Spectrometer (MERIS) for monitoring water quality parameters of oligo- and mesotrophic lakes are investigated. Relations between optically active substances and spectral reflectance were studied, based on limnological field data and spectral reflectivity measured in situ, in an airborne survey, and from first MERIS data. An atmospheric radiative transfer model is applied to derive the at-surface reflectance. An empirical algorithm was developed for mapping the concentration of chlorophyll-a based on reflectance ratios.

Algorithms for snow mapping in Alpine areas are developed for the medium resolution imaging spectrometers MODIS and MERIS. A snow classification algorithm, discriminating snow cover in forested areas and open terrain, is presented. Examples of snow cover products are shown for MODIS data. The need for improvement, mainly related to snow/cloud discrimination, is addressed. In addition, the albedo of snow surfaces was derived from at-satellite radiances, applying a model for atmospheric radiative transfer. Capabilities and weaknesses of the model are discussed.

Based on requirements for improved observations of snow and ice in climate research and hydrology, SNOWSAT, a satellite mission for observation of the cryosphere from regional to global scales, was elaborated. As payload a co- and cross- polarized Ku-band (17 GHz) SAR was selected, because of its sensitivity to dry snow, thin sea ice, and the metamorphic state of snow, firn and ice on glaciers and ice caps. A ScanSAR scheme with a linear array of 3 parabolic reflectors, each with multiple beams, was chosen to fulfil the requirements for swath width and spatial resolution and to avoid antenna deployment. SNOWSAT, operating in two different modes for climate applications and hydrology, represents an innovative, cost-effective solution for monitoring a wide range of snow and ice parameters.

Methods and applications of differential SAR interferometry (DINSAR) for detecting and monitoring slow movements of mountain slopes on the order of centimeters per year were investigated in the Austrian and Swiss Alps, using SAR images from the European ERS-1 and ERS-2 satellites. The DINSAR analysis methods and criteria for selecting SAR image pairs suitable for landslide monitoring are briefly described. Most of the detected landslides are above the tree line, because on surfaces with sparse vegetation and bare soil or rock the coherence is preserved over long periods. The investigations confirm the operational potential of DINSAR for detecting and monitoring mass movements in high Alpine areas.

Signatures of glaciated and ice free areas were analyzed from polarimetric SAR data at C-, L-, and P-band and single polarization X-band data. The data base includes an AIRSAR scene from June 25, 1991, and SIR-C/X-SAR images from April and October 1994 (SRL-1 and SRL-2), acquired over the high Alpine test site O/spl uml/tztal in Austria. The environmental conditions were different at the time of the three experiments. Ground measurements, meteorological observations, and backscattering modeling are the basis for interpreting the backscattering signatures. Seasonal differences are due mainly to the presence or absence of snow and due to changes of its properties. Short term variations of snow conditions can be monitored at C- and X-band. For unglaciated areas, the surface roughness has a dominant influence on backscattering in all seasons. The dependence of the mean backscattering and correlation coefficients on the incidence angle was analyzed. Spectral and depolarization ratios and the magnitude of the HHVV correlation coefficient were selected as components of the multidimensional feature vector for studying the target separability. Good separability was found between the accumulation and ablation areas on the glaciers, whereas on ice-free areas, the dominance of surface roughness limits the discrimination of different surface types. Short-term variations of backscattering have significant impact for the classification of accumulation and ablation areas on glaciers, as verified by comparisons with field data.

An algorithm has been developed for mapping wet snow in mountainous terrain using repeat pass synthetic aperture radar (SAR) images. As a basis for algorithm development, backscattering properties of snow-free and snow-covered alpine surfaces were investigated using ERS SAR data and field measurements at test sites in the Austrian Alps. The incidence angle dependence of backscattering derived from SAR data is compared with simulations for snow-free surfaces and for surfaces covered by dry snow and wet snow. Significant seasonal changes of backscattering are observed, which are mainly caused by variations of the snow liquid water content and of the surface roughness. The importance of surface roughness for backscattering of wet snow is demonstrated by a surface roughness experiment. The algorithm for mapping wet snow applies change detection using ratios of wet snow versus snow-free or dry snow surfaces. The main steps include coregistration, speckle reduction, thresholding of ratio images, geocoding, and, optionally, combination of crossing passes to reduce the loss of information due to layover. A threshold of -3 dB was found to be appropriate for both Radarsat and ERS SAR to separate wet snow from other surfaces. Postprocessing steps, based on historic snow maps or topographic information, are used to correct for dry snow areas at high elevations. Effects of imaging geometry are investigated by comparing ERS SAR images with a look angle of 19/spl deg/ and Radarsat SAR Beam Mode S7 images with a look angle of 40/spl deg/. The comparison of snow maps from SAR and Landsat-5 Thematic Mapper images shows good agreement in areas of closed snow cover, whereas near the snow line/SAR tends to slightly underestimate the snow extent.

The scatterometer flown onboard the European remote-sensing satellites ERS-1 and ERS-2 is a vertically polarized radar operating at 5.3 GHz (C-band) and has a spatial resolution of 50 km. In a number of studies, the sensitivity of the ERS scatterometer to vegetation has been demonstrated, but it is not yet clear which vegetation parameters are of primary importance to explain the ERS scatterometer signal. In this paper, the effects of land cover and seasonal vegetation development are investigated by comparing ERS scatterometer data with land cover information, normalized difference vegetation index (NDVI) data sets, and meteorological observations. As a study area, the Iberian Peninsula was chosen. The Iberian Peninsula is characterized by the Mediterranean climate that has a wet winter and a dry summer. This allows the authors to better differentiate the effects of the annual vegetation and precipitation cycle on the temporal evolution of the backscattering coefficient /spl sigma//spl deg/. It is shown that the ERS scatterometer has only limited capabilities for monitoring the vegetation development within a given year because most of the temporal variability of /spl sigma//spl deg/ is due to soil moisture changes. On the other hand, it might be of merit for vegetation discrimination on large scales (regional to global) because the percentage area of forests, bushes, and shrubs within one ERS scatterometer pixel is found to explain a significant part of the spatial variability of the signal.

The capability of the scatterometers onboard the European Remote Sensing Satellites (ERS-1 and ERS-2) for soil moisture retrieval is investigated. The ERS scatterometer consists of three antennas that illuminate the Earth's surface from three different viewing directions. This allows the authors to study the dependence of the backscattering coefficient /spl sigma//sup 0/ on the azimuth and the incidence angle. An analysis of ERS scatterometer data over the Canadian Prairie region shows that land surfaces are slightly anisotropic with respect to the azimuth angle. It is proposed to consider the azimuthal anisotropy as an additional error source to /spl sigma//sup 0/. The variation of /spl sigma//sup 0/ with the incidence angle was found to be linked to vegetation, but independent of soil moisture. Based on these observations, a method for the normalization of the backscattering coefficient with respect to the incidence angle is proposed. The normalized backscattering coefficient at an incidence angle of 40/spl deg/, /spl sigma//sup 0/(40), is sensitive to vegetation and, in the case of moderate vegetation (grassland to sparsely forested areas), to the soil moisture content. Soil moisture maps derived from ERS-1 scatterometer measurements are compared to maps representing conditions on annually cropped land showing agreement. Results suggest that, over the Canadian Prairies, estimates of the total water content in the soil profile might be possible with an accuracy of about 10% of field capacity if little or no rainfall has occurred for three days before radar image acquisition.

Active microwave sensors can discriminate snow from other surfaces in all weather conditions, and their spatial resolution is compatible with the topographic variation in alpine regions. Using data acquired with the NASA AIRSAR in the Otztal Alps in 1989 and 1991, the authors examine the usage of synthetic aperture radar (SAR) to map snow- and glacier-covered areas. By comparing polarimetric SAR data to images from the Landsat Thematic Mapper obtained under clear conditions one week after the SAR flight, the authors found that SAR data at 5.3 GHz (C-band) can discriminate between areas covered by snow from those that are ice-free. However, they are less suited to discrimination of glacier ice from snow and rock. The overall pixel-by-pixel accuracies-74% from VV polarization alone with topographic information, 76% from polarimetric SAR without any topographic information, and 79% from polarimetric SAR with topographic information-are high enough to justify the use of SAR as the data source in areas that are too cloud-covered to obtain data from the Thematic Mapper. This is especially true for snow discrimination, where accuracies exceed 80%, because mapping of a transient snow cover during a cloudy melt season is often difficult with an optical sensor. The AIRSAR survey was carried out in summer during a heavy rainstorm, when the snow surfaces were unusually rough. Even better results for snow discrimination can be expected for mapping in the spring, when snow is usually smoother.>