Mountain Cryosphere

A polarimetric two-scale scattering model employed to retrieve the surface parameters of bare soils from polarimetric SAR data is presented. The scattering surface is here considered as composed of randomly tilted rough facets, for which the SPM or the PO hold. The facet random tilt causes a random variation of the local incidence angle, and a random rotation of the local incidence plane around the line-of-sight, which in turn causes a random rotation of the facet scattering matrix. Unlike other similar already existing approaches, our method considers both these effects. The proposed scattering model is then used to retrieve bare soil moisture and large-scale roughness from the co-polarized and cross-polarized ratios.

The crucial role of cryosphere for understanding the global climate change has been widely recognized in recent decades . Glaciers and ice sheets are the main components of the cryosphere and constitute the basic reservoir of fresh water for high-latitudes and many densely populated areas at mid and low latitudes. The need of information on large scale and the inaccessibility of polar regions qualify synthetic aperture radar (SAR) sensors for glaciological applications. At long wavelengths (e.g. P-and L-band), SAR systems are capable to penetrate several tens of meters deep into the ice body. Consequently, they are sensitive to the glacier surface as well as to sub-surface ice structures. However, the complexity of the scattering mechanisms, occurring within the glacier ice volume, turns the interpretation of SAR scattering signatures into a challenge and large uncertainties remain in estimating reliably glacier accumulation rates, ice thickness, subsurface structures and discharge rates. In literature great attention has been given to model-based decomposition techniques of polarimetric SAR (PolSAR) data. The first model-based decomposition for glacier ice was proposed in [2] as an adaptation and extension of the well-known Freeman-Durden model . Despite this approach was able to interpret many effects in the experimental data, it could not explain, for instance, co-polarization phase differences. The objective of this study is to develop a novel polarimetric model that attempts to explain PolSAR signatures of glacier ice. A new volume scattering component from a cloud of oriented particles will be presented. In particular, air and atmospheric gases inclusions, typically present in ice volumes , are modeled as oblate spheroidal particles, mainly horizontally oriented and embedded in a glacier ice background. Since the model has to account for an oriented ice volume, the anisotropic nature of the ice medium has to be incorporated. This phenomenon, neglected in [2], leads to different refraction indices, i.e. differential propagation velocities (phase differences) and losses of the electromagnetic wave along different polarizations . Furthermore, the introduction of additional scattering components (e.g. from the glacier surface) will extend and complete the polarimetric model.

The objectives of the IceFRONT project are 1) to help hydropower companies to gather from satellite images, the timely information needed for operational river freeze-up monitoring and 2) to speed up and simplify the process of analyzing the satellite images and extracting the required information. The study is conducted on the Peace River (Alberta). The project has succeeded in developing an integrated automated approach to provide ice information from various sources of satellite data, based entirely on open source software. IceFRONT integrates optical (MODIS and LANDSAT-8) and radar (RADARSAT-2 and TERRASAR-X) images. The various approaches are described.

A century of expedition and adventure has turned Mount Everest into a “mortuary landscape”. There have been more than 300 deaths on Everest since records of mountain climbing began and many of these bodies remain on the mountain. New climbing seasons bring an increase to the death toll. More recently, efforts have been made to retrieve bodies from the mountain’s ‘death zone’ as part of clean-up efforts.
Everest’s high-altitude cryosphere disrupts normal cultural approaches to disposing of human remains.  Bodies enter new ontic states and new spatio-temporal regimes that render corpses ‘uncanny’. Remains are encountered within the mountain cryosphere as both fixed features in a landscape and as mobile entities in glacial systems. 
The persistence of corpses in the cryosphere and their post-mortal (im)mobilities raises important questions about the ways in which the fixity and extension of bodies in the cryosphere alters the transition of human remains from subject to object, enabling forms of post-mortal personhood to emerge on the mountain. 
2024 has seen both the centenary of the 1924 Mount Everest Expedition on which George Mallory and Sandy Irvine disappeared and the discovery of the partial human remains of Irvine on the Central Rongbuk Glacier in Tibet, China.  We take this opportunity to reflect and to invite papers that explore the intersections of high-altitude, death and post-mortal personhood on Mount Everest and invite contributions that reflect on materiality, mobilities, memory and identities in the mountain cryosphere.
In contradistinction to the highly valorised corpses of Mallory and Irvine that have mobilized search expeditions, books and films, other human remains on Everest have failed to signify in Western accounts of mountaineering on Everest, in particular the bodies of the seven indigenous high-altitude Sherpa and Bhotia porters who were the first people to die attempting to climb Everest in 1922.  Drawing on Subaltern Studies and postcolonial theory we ask to what extent is the mountain haunted by subaltern histories and bodies that have failed to materialize? 
The de-materialization and re-materialization of human remains on Everest presents new assemblages, complex new entanglements between people and things, producing new meaning and affects that raise important questions about the significance of these complex objects.  These corpses exhibit what Jane Bennet terms a vital materiality, retaining agency and moving through both space and time (appearing and disappearing), forcing us to question assumptions about post-mortal personhood and Cartesian distinctions between subject and object.
Bennett, Jane (2010), Vibrant Matter: A Political Ecology of Things (Durham, North Carolina: Duke University Press).
Heller-Roazen, Daniel (2021) Absentees: On Variously Missing Persons (New York: Zone Books).
Marder, Michael (2012) ‘On The Mountains: or, The Aristocracies of Space’, Environment, Space, Place, 4 (2) 63-74. https://philpapers.org/rec/MAROTM-6
Oh, Young Hoon (2018), ‘Dying differently: Sherpa and Korean mountaineers on Everest’, Minnesota Review, 90, 100-113.
Ortner, Sherry B. (1999) Life and Death on Mount Everest: Sherpas and Himalayan Mountaineering (Princeton university Press).

Possible topics for papers include (but are not limited to) the following subjects:
• Post mortal (im)mobilities in the cryosphere.
• (De)personalization of human remains in-situ.
• Post-mortal mediatization of human remains on Everest.
• The necropolitics of high-altitude corpses.
• Processes of post-mortem heroization and celebrity.
• Ethnographic and phenomenological approaches to human remains on Everest.
• Climate change and the challenge of identifying and managing human remains on Everest.
• Differing state, religious and nationalist attitudes to recovering and repatriating bodies.
• Spiritualism and mediumistic contact with Mallory and Irvine post-mortem.

This paper presents some applications of the Maximum Likelihood (ML) texture tracking on displacement estimation of some alpine and antarctic glaciers surfaces. This method is adapted to the statistical characteristic of the new High Resolution (HR) Polarimetric SAR (Pol-SAR) data. The ML texture tracking method is firstly reminded and a statistical model of HR PolSAR data is explained. The main part of this paper is focused on the application of this method on glaciers monitoring. Three different glaciers have been chosen to test the algorithm: a cold alpine glacier, a temperate alpine glacier and an outlet antarctic glacier. The accuracy and limits of the method are highlighted in each case and results application is discussed.

Abstract: A Synthetic Aperture Radar is an antenna which collects and stores all signals with respect to amplitude, phase, frequency, polarization and running time for gaining desired information with Special processing algorithms. This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Synthetic Aperture Radar (SAR) is a form of radar whose defining characteristic is its use of relative motion between an antenna and its target region to provide distinctive long-term coherent-signal variations that are exploited to obtain finer spatial resolution than is possible with conventional beam-scanning means. It originated as an advanced form of side-looking airborne radar (SLAR). Recent (2010) airborne systems provide resolutions to about 10 cm, ultra-wide band systems provide resolutions of a few millimeters, and experimental terahertz SAR has provided sub-millimet...

Silica sand is one of the minerals which relatively abundant in Indonesia. One of the areas with abundant of silica sand distribution is the northern coastline of Rupat Island, Bengkalis district, Riau province, Indonesia. The distribution of silica sand in this island identified only on the northern coastline in this island. Some selected sample of silica sand was measured to get the percentage of silica sand mineral's content using X-Ray Fluorescence (XRF). Two adjacent scenes of ALOS PALSAR full-polarimetry were used. The physical properties of silica sand sample such as dielectric constant were measured using dielectric probe kit in the frequency range from 0.3 to 3.0 GHz and used for calculating the backscattering coefficient and the difference characteristics of silica sand with another object. Freeman-Durdeen and Yamaguchi techniques were used to get the scattering decomposition of physical scattering from the incoherent object model based. Surface scattering is the clearest of Scattering decomposition to show silica sand identification compares with other decompositions. From surface scattering, the backscattering coefficient value of silica sand was calculated starting from-59 dB until-52 dB. These values were given by the surface roughness condition, where the roughness is slightly rough planar. The flat condition supported by the grain size of silica sand particles that have almost the same size and shape, that were conducted by using microscopic photograph testing.

Retrieval of Snow Density using hybrid polarimetric RISAT-1 SAR (Synthetic Aperture Radar) data is implemented in this study. The C-band datasets were acquired in FRS-1 mode in which microwaves EM are transmitted in the Right circular polarization from the sensor and are received in linear (Horizontal or Vertical) polarizations resulting in Hybrid polarizations-RH and RV. The datasets were acquired for the date of 23 rd February 2014 covering the Dhundi region in Manali district of Himachal Pradesh. In this season, the area experiences regular snowfall, hence the whole area was covered with the dry snow layer. Hybrid decomposition technique along with Integral Equation Model (IEM) is utilized for snow density extraction of the snowpack in the study area. The modeled and theoretical approaches are used to retrieve the dielectric constant of the snowpack. Fresnel coefficients, utilized in the IEM modeling approach, is the function of snowpack dielectric constant and the local incidence angle of the incident wave from the sensor. The retrieved snow density map is generated for the area. The validation of the retrieved results is done using ground data collected during the period.

To further our understanding of global paleoclimate variations, the European Project for Ice Coring in Antarctica (EPICA) has started to drill two deep ice cores in Antarctica, with one located on the Amundsenisen plateau in Dronning Maud Land. In order to determine an optimal drilling location, extensive glaciological, geophysical and remote sensing projects were started in 1995. In support of these projects, this study attempts to understand the influences of physical snow pack parameters on the signal strength in RADARSAT SAR imagery. Twenty-six RADARSAT SAR standard beam images acquired in May 1997 are analysed. Processing steps include radiometric calibration, geometric correction and the generation of a mosaic that covers most of the study area. Field data were collected during the Dronning Maud Land traverse (1997/1998) of the Alfred Wegener Institute for Polar and Marine Research (AWI), and include accumulation rate, firn temperature, dielectric properties and the number of layers in snow pits. The field data are interpolated spatially to cover the entire study area. To determine the influence of the different snow pack parameters on the radar backscatter signal, a linear correlation is performed on the field-derived data on a point-to-point and on an area basis. Since in the study area, the azimuthal modulation of the backscattering signal is assumed to be relatively low, variations of σ° should also be attributable to internal characteristics of the dry snow pack. Results show that the backscattering coefficient is negatively correlated to the accumulation rate, and positively correlated to the heterogeneity of the dielectric properties. The lower the accumulation rate, and the more heterogeneous the snow pack, the stronger the backscatter signal. However, correlations are still relatively poor, and therefore neither surface characteristics nor internal properties of the snow pack alone can account totally for the observed backscattering patterns.

In recent years, photographs and visualisations of glacier retreat have become emblematic images of climate change and its ecological consequences. This paper presents glacier photography as a subtype of environmental photography. I argue that photographs and photographic projects that focus on glacial retreat are best conceived not only as strategies for proving climate change or as visual rhetoric for social transformation, but also as a practice that potentially plays an integral role in dealing and coping with human-induced environmental loss. To this end, I draw on praxeological accounts in theory of photography and philosophy of art as well as some exemplary photographic projects to develop a framework to analyse glacier photography. With the help of this praxeological framework, multiple orientations in glacier photography are identified: epistemic, aesthetic, emotional and evocative, social, ethical, and political orientations. All these photographic orientations, I argue, point in their own way to the process and consequences of glacial disappearance and loss. The framework presented innovatively brings together scholarship on climate change visualisation, imagery and art, the theory of photography, and philosophical aesthetics.
DOI: 10.1177/09632719231221843

Climatic studies of agricultural regions normally use gauge-based air temperature datasets, which are produced with interpolation methods. The informative quality of these datasets varies depending on the density of the weather stations in a particular region. A way to overcome this limitation is to use the land surface temperature calculated from satellite imagery. To show this, the MODIS land surface temperature was compared with the PTHRES gridded dataset for air temperature in the Douro Demarcated Region (Portugal) between the years 2002 and 2020. The MODIS land surface temperature was able to detect a more pronounced maritime–continental gradient, a higher lapse rate, and thermal inversions in valley areas in winter. This information could prove to be crucial for farmers looking to adapt their practices and crops to extreme events, such as heat waves or heavy frost. However, the use of land surface temperature in climate studies should consider the differences in air temperatur...

Climatic studies of agricultural regions normally use gauge-based air temperature datasets, which are produced with interpolation methods. The informative quality of these datasets varies depending on the density of the weather stations in a particular region. A way to overcome this limitation is to use the land surface temperature calculated from satellite imagery. To show this, the MODIS land surface temperature was compared with the PTHRES gridded dataset for air temperature in the Douro Demarcated Region (Portugal) between the years 2002 and 2020. The MODIS land surface temperature was able to detect a more pronounced maritime–continental gradient, a higher lapse rate, and thermal inversions in valley areas in winter. This information could prove to be crucial for farmers looking to adapt their practices and crops to extreme events, such as heat waves or heavy frost. However, the use of land surface temperature in climate studies should consider the differences in air temperatur...

The current study has been done using Polarimetric Synthetic Aperture Radar (SAR) data to estimate the dry snow density in Manali sub-basin of Beas River located in state of Himachal Pradesh, India. SAR data from Radarsat-2 (RS2), Environmental Satellite (ENVISAT), Advanced Synthetic Aperture Radar (ASAR) and Advanced Land Observing Satellite (ALOS)-Phased Array type L-band Synthetic Aperture Radar (PAL-SAR) have been used. The SAR based inversion models were implemented separately for fully polarimetric RS2, PALSAR and dual polarimetric ASAR Alternate polarization System (APS) datasets in Mathematica and MATLAB software and have been used for finding out dry snow dielectric constant and snow density. Masks for forest, built area, layover and shadow were considered in estimating snow parameters. Overall accuracy in terms of R 2 value and Root Mean Square Error (RMSE) was calculated as 0.85 and 0.03 g cm −3 for snow density based on the ground truth data. The retrieved snow density is highly useful for snow avalanche and snowmelt runoff modeling related studies of this region.

Developped in the Institut of Electronics and Telecommunication of Rennes (IETR), a Ground Based (GB) SAR system is proposed for soil surface roughness discrimination at C-band. By using this GB-SAR system, the multi-angular SAR measurement is realized at different resolution cell sizes. The specific levels of surface roughness are set deliberately to analyze the roughness contribution on multi-angular SAR signature in a controlled experimental condition. Based on the GB-SAR measurement, the effect of incidence angle on SAR sensitivity is studied under two resolution cell sizes for retrieving soil surface roughness. The results show that, by using our GB-SAR system, high incidence angle configuration (e.g. > 40 •) is optimal to discriminate surface roughness, which is more significant at small resolution cell size (e.g. 30 cm). This study indicates the effectivity of GB-SAR system to validate the SAR backscattering mechanisms.

This paper is focused on investigations of the improved correction of the effect of variation in incidence angle on ScanSAR data. Conventional correction methods (such as LLM, locally linear mapping) typically assume that each target class has a similarity distribution in the middle of the image. The objectives of this study are to extend the correction algorithm to full swath width without any assumptions. For a target class only distributed on one or both sides of the image, interpolation or extrapolation of the confidence interval is realized using the linear regression technique based on the exponential model. The position of the reference band is then determined and the correction is performed. Experiments were performed on ENVISAT ASAR and RADARSAT-2 ScanSAR data. The results show the effectiveness of the proposed method.

Due to the accelerating global warming, droughts which cause severe damages especially in the agriculture became a very recurrent phenomenon in all over the world. Monitoring the characteristics of soil moisture is very important in Turkey because the major impact of the global warming on our country appears to be climate changes. In this respect, drought has become a serious threat for the country where the agriculture is one of the major income sources. Therefore, monitoring of draughts has the highest priority among the other strategies. Although the sensitivity of microwaves towards the soil moisture is well understood, retrieving soil moisture with Synthetic Aperture radar (SAR) measurements still has difficulties due to the major impact of soil texture, surface roughness and vegetation cover. In this study, SAR data gathered by different sensors for the same area in closer dates were used to estimate the relative soil moisture. The relation between the ground soil moisture and the sigma nought/backscatter values of SAR images were investigated. Sigma nought values of C band HH polarized Radarsat Fine Beam image and C Band VV polarized ENVISAT (ASAR) images as well as backscatter values of an L band HH polarized ALOS (PALSAR) satellite images were used. RADARSAT, ASAR and PALSAR images were gathered on the 28th of May, 8th of June, and 10th of June in 2006 respectively for the alluvial lands of Menemen Town, Izmir. Ground soil moisture measurements taken using gravimetric methods showed a good agreement with the backscatter values of the images obtained from different types of SAR data. A comparison among the spatial distribution of retrieved soil moisture changes from SAR images was done. The correlations between the soil moisture content and backscattering of ASAR, RADARSAT-1 and PALSAR images were found 76%, 81% and 86 % respectively. Although the resolution of RADARSAT-1 fine beam image (6.25m × 6.25m) is closer to the resolution of PALSAR image (6.25m × 6.25m), PALSAR gives better correlation than RADARSAT-1 image. Although the resolution of RADARSAT-1 and PALSAR images is far more higher than that of the ASAR image (30m × 30m), the significance of the results produced is almost similar in such flat areas.

Abstract: A Synthetic Aperture Radar is an antenna which collects and stores all signals with respect to amplitude, phase, frequency, polarization and running time for gaining desired information with Special processing algorithms. This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Synthetic Aperture Radar (SAR) is a form of radar whose defining characteristic is its use of relative motion between an antenna and its target region to provide distinctive long-term coherent-signal variations that are exploited to obtain finer spatial resolution than is possible with conventional beam-scanning means. It originated as an advanced form of side-looking airborne radar (SLAR). Recent (2010) airborne systems provide resolutions to about 10 cm, ultra-wide band systems provide resolutions of a few millimeters, and experimental terahertz SAR has provided sub-millimet...

Silica is one of the mineral needs of the industry, especially in base materials for the primary or auxiliary raw materials. Silica sand on Rupat Island was identified on the northern coastline. Selected samples were measured to get the percentage minerals/elements using X-Ray Fluorescence (X-RF). Two adjacent scenes of ALOS PALSAR full-polarimetry data were used. The dielectric constant of samples measured using dielectric probe kit in the frequency range from 0.3 to 3.0 GHz and also used for calculating the backscattering coefficient. Freeman-Durdeen and Yamaguchi techniques were used to get the scattering decomposition of physical scattering from the incoherent object model based. Surface scattering is very clear decomposition to show the silica sand identification compares with other decompositions. From surface scattering, the backscattering coefficient value of silica sand resulted from-59 dB until-52 dB. Thickness estimation from satellite and field measurement shows the minimum is 59 cm, and the maximum is 74 cm with the average differentiation between these measurements are 4.88 cm. The condition supported by the grain size of silica sand particles that have almost the same size and shape, that were conducted by using microscopic photograph testing. These values caused by a slightly rough surface. Résumé La silice est l'un des minéraux nécessaires à l'industrie, en particulier dans les matériaux de base pour les matières premières primaires ou auxiliaires. Du sable de silice sur l'île Rupat sur la Côte

Silica sand is one of the minerals which relatively abundant in Indonesia. One of the areas with abundant of silica sand distribution is the northern coastline of Rupat Island, Bengkalis district, Riau province, Indonesia. The distribution of silica sand in this island identified only on the northern coastline in this island. Some selected sample of silica sand was measured to get the percentage of silica sand mineral's content using X-Ray Fluorescence (XRF). Two adjacent scenes of ALOS PALSAR full-polarimetry were used. The physical properties of silica sand sample such as dielectric constant were measured using dielectric probe kit in the frequency range from 0.3 to 3.0 GHz and used for calculating the backscattering coefficient and the difference characteristics of silica sand with another object. Freeman-Durdeen and Yamaguchi techniques were used to get the scattering decomposition of physical scattering from the incoherent object model based. Surface scattering is the clearest of Scattering decomposition to show silica sand identification compares with other decompositions. From surface scattering, the backscattering coefficient value of silica sand was calculated starting from-59 dB until-52 dB. These values were given by the surface roughness condition, where the roughness is slightly rough planar. The flat condition supported by the grain size of silica sand particles that have almost the same size and shape, that were conducted by using microscopic photograph testing.

Invasive alien plant species are regarded as a major threat to among others socioeconomic systems, global biodiversity and conservation initiatives. A reliable understanding of their 2 spatial and temporal distribution is paramount for understanding their impact on co-existing landscapes and ecosystems. While traditional passive remote sensing methods have been successful in assessing invasion of such species, limiting factors such as cost, restricted coverage, image availability, terrain and inadequate resolutions hamper mapping and detection at large spatial extents. To date, the adoption of active remote sensing techniques as complimentary data to invasive alien plant mapping has been limited. In this study, we fuse two commonly used medium spatial and spectral resolution imagery (Sentinel-2 and Landsat 8) with active remote sensing data (Synthetic Aperture Rada imagery) in determining the optimal season for detecting and mapping the American Bramble (Rubus cuneifolius). Feature level image fusion was adopted to integrate passive and active remote sensing imagery and Support vector machine (SVM) supervised classification algorithm used to discriminate the American Bramble from surrounding native vegetation. Seasonal results showed that Sentinel-2 data, fused with SAR data generated the highest classification accuracy during summer (76%), while Landsat 8 imagery fused with SAR data performed best in winter (72%). These findings demonstrate that fusion of SAR with traditional optical imagery can be used to detect and map the American Bramble at a regional scale. We conclude that SAR data can be used synergistically with optical remote sensing to improve discrimination and mapping of the American Bramble.

A polarimetric two-scale scattering model employed to retrieve the surface parameters of bare soils from polarimetric SAR data is presented. The scattering surface is here considered as composed of randomly tilted rough facets, for which the SPM or the PO hold. The facet random tilt causes a random variation of the local incidence angle, and a random rotation of the local incidence plane around the line-of-sight, which in turn causes a random rotation of the facet scattering matrix. Unlike other similar already existing approaches, our method considers both these effects. The proposed scattering model is then used to retrieve bare soil moisture and large-scale roughness from the co-polarized and cross-polarized ratios.

There are difficulties associated with near-real time or frequent pavement monitoring, because it is time consuming and costly. This study aimed to develop a binary logit model for the evaluation of highway riding quality, which could be used to monitor pavement conditions. The model was applied to investigate the influence of backscattering values of Phase Array type L-band Synthetic Aperture Radar (PALSAR). Training data obtained during 3-7 May 2007 was used in the development process, together with actual international roughness index (IRI) values collected along a highway in Ayutthaya province, Thailand. The analysis showed that an increase in the backscattering value in the HH or the VV polarization indicated the poor condition of the pavement surface and, of the two, the HH polarization is more suitable for developing riding quality evaluation. The model developed was applied to analyze highway number 3467, to demonstrate its capability. It was found that the assessment accuracy of the prediction of the highway level of service was 97.00%. This is a preliminary study of the proposed technique and more intensive investigation must be carried out using ALOS/PALSAR images in various seasons.

An analysis is presented of dynamic calibration methods that can be used in the 13.3 GHz scatterometer. Four candidate methods are considered with conclusions presented regarding the effectiveness of each method. A mathematical model is derived for each design with the signal frequency spectrum computed at critical points in the receiver. It is shown that the present method of` calibration is unacceptable because the calibration signal amplitude is subject to variation. The error in scattering coefficient is shown to be especially sensitive to the bias point and linearity of the ferrite modulator. It is recommended that an injection system be incorporated in the 13.3 GHz scatterometer which uses a square-wave calibration signal. The analysis shows that this method will calibrate the scatterometer to the required accuracy with no error induced in the data record by the calibration system.

The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4-8 GHz spectral response from two types of baresoil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system mounted atop a 75-foot truck-mounted boom was used to measure the return at 10 frequency points across the 4-8 GHz band, at 8 different look angles (00 through 700), and for all polarization combinations. A total of 17 sets of data were collected covering the range 4-36% soil moisture content by weight. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear, however,over the range 15%-30% moisture content for all angles, frequencies, polarizations and surface conditions.

This study shows recent results of our efforts to develop and verify an algorithm for snow wetness retrieval from a polarimetric SAR (Synthetic Aperture Radar). Our algorithm is based on the first-order scattering model with consideration of both surface and volume scattering. It operates at C-band and requires only rough information about the ice volume fraction in snowpack. Comparing ground measurements and inferred from JPL AIRSAR data, the results showed that the relative error inferred from SAR imagery was within 25 ...

Retrieval of Snow Density using hybrid polarimetric RISAT-1 SAR (Synthetic Aperture Radar) data is implemented in this study. The C-band datasets were acquired in FRS-1 mode in which microwaves EM are transmitted in the Right circular polarization from the sensor and are received in linear (Horizontal or Vertical) polarizations resulting in Hybrid polarizations-RH and RV. The datasets were acquired for the date of 23 rd February 2014 covering the Dhundi region in Manali district of Himachal Pradesh. In this season, the area experiences regular snowfall, hence the whole area was covered with the dry snow layer. Hybrid decomposition technique along with Integral Equation Model (IEM) is utilized for snow density extraction of the snowpack in the study area. The modeled and theoretical approaches are used to retrieve the dielectric constant of the snowpack. Fresnel coefficients, utilized in the IEM modeling approach, is the function of snowpack dielectric constant and the local incidence angle of the incident wave from the sensor. The retrieved snow density map is generated for the area. The validation of the retrieved results is done using ground data collected during the period.

In the rugged mountains, the undulations of the terrain will affect the geometric and radiation characteristics of SAR imaging, resulting in SAR image distortion, which hinders its comprehensive application in the field of land subsidence monitoring, landslide disaster monitoring and so on. This article takes ALOS PALSAR as an example, combined with satellite orbit fitting technology to optimize parameters, based on the R-D positioning model, using DEM to simulate SAR images and extract parameters such as local incident angle, projection angle, and backscatter coefficient. The simulated SAR image is used to achieve the ortho-rectification of the original SAR image. The calculation method of the local incidence and projection angles and the backscattering coefficient is used to construct the terrain radiation correction model of the SAR image. The experimental results show that the research method is significantly effective, the mean square error of the radiant intensity of the image...

In the meantime, researchers at INRS-Eau have been working for many years on the development of both application of remote sensing to hydrology and distributed hydrological models able to use remotely sensed and GIS data. Within the framework of the VEGETATION Preparatory Program, we have developed a snow mapping methodology at the sub-pixel level as well as a reflectance estimation of individual land use classes from the Vegetation data. Concurrently, in the framework of similar RADARSAT programs, we have developed a software package called EQeau, for the distributed estimation of the water equivalent of a dry snowpack. Also, the HYDROTEL hydrological model has been adapted to hydrological forecasting.

This note is about the comparison of coregistration offset tracking velocities of a glacier obtained with SAR sensors characterized by different wavelengths and spatial resolutions: Cosmo-SkyMED (X band) and RADARSAT-2 (C band). The study area is represented by the initial part of the David Glacier, in Antarctica, which is the most important outlet glacier of Victoria Land. Particular attention has been devoted to understand the role of polarization and penetration depth of the incident wavelength, which represent key parameters in determining the effective incidence angle and so, for this reason, affecting also derived velocities. Further investigation is needed to complete this analysis, considering also geophysical data and tidal effects.

The current methods for retrieving SWE from space rely on passive microwave sensors. However, the use of these sensors for snow properties detection is limited by the poor spatial resolution that implies difficulty in considering mixed pixel effects over heterogeneous landscapes, such as in mountainous areas. The use of Synthetic Aperture Radar (SAR) has been suggested as a potential observation method to overcome the coarse resolution of passive microwave sensors [1,2,3].

Abstract—In this contribution, a car-borne SAR and InSAR experiment is described. The slope of a valley was imaged by means of a single-pass InSAR system mounted on a car driving on roads along the bottom of the valley. The GAMMA portable radar interferometer GPRI-II hardware with a modified antenna configuration was used for data acquisition. The experimental setup (1), SAR imagery focused along a slightly curved sensor trajectory (2), and first interferometric results (3) obtained using this configuration are presented. Index Terms—Synthetic aperture radar (SAR), ground-based SAR system, SAR imaging, SAR interferometry, car-borne SAR, CARSAR I.

Operational ice services around the world have recognized the economic and environmental benefits that come from the increased capabilities and uses of space-borne Synthetic Aperture Radar (SAR) observation system. The two major objectives in SAR based remote sensing of sea ice is on the one hand to have a large areal coverage, and on the other hand to obtain a radar response that carries as much information as possible. Although until now, L-Band SAR sensors are rarely used in an operational context, it offers greater capabilities for sea ice type retrieval and is more robust during the melt season compared to higher frequency bands. With the help of JAXA's ALOS-2 PALSAR-2 sensor, we are able to explore the potential of polarimetric L-band acquisitions for sea ice analysis and classification in an operational environment. In this study we investigated the incidence angle related variation on the L-band backscatter and recommended optimal scenarios for Artificial Neural Network based sea ice type retrieval schemes.

• Three different Synthetic Aperture Radar (SAR) frequency bands are compared regarding their response to different sea-ice characteristics. • Newly formed sea ice generate an above average response in L-band and below average response in C-band and X-band copolarization ratio • Surface roughness and snow pack structure can in some cases be a stronger influence on sea ice classification than sea-ice thickness itself.

Expected applications improvements provided by dual-and quad-polarised from RADARSAT-2 are identified. Dual-polarised data is expected to have a wide range of applications. More detailed information is provided by quad-polarised data but here applications are limited by the narrow swath width. A specific study on sea ice monitoring is focussed on as an example application. The effect of system noise on polarimetric data analysis is considered as is the potential for polarimetric interferometry. The latter will be limited by temporal decorrelation.

This study aims at relating the stickiness parameter 1 (τ) of the dense media radiative transfer theory in quasi-2 crystalline approximation of Mie scattering of densely packed 3 sticky spheres (DMRT-QMS), to the physical parameters of the 4 layered snowpack. A relationship has been derived to express τ , 5 which modulates the attractive contact force between ice spheres, 6 as a function of ice volume fraction (φ) and coordination number 7 (n c). Since τ is not a measurable parameter, this is a step forward 8 with respect to what is commonly made in the literature, where τ 9 is assumed as an arbitrary parameter, generally ranging between 10 0.1 and 0.3, to fit simulated backscattering data with those 11 measured. As a first validation, DMRT-QMS was integrated 12 with the SNOWPACK model to simulate backscattering at 13 X-band (9.6 GHz) driven by nivo-meteorological data acquired 14 on a test area located in Monti Alti di Ornella, Italy. The 15 simulations were compared with Synthetic Aperture Radar 16 COSMO-SkyMed (CSK) satellite observations. The results show 17 a significant agreement (R 2 = 0.68), although for a limited 18 dataset of eight points in a unique winter season. 19 Index Terms-Backscattering, coordination number, COSMO-20 SkyMed (CSK), dense media radiative transfer theory in quasi-21 crystalline approximation of Mie scattering of densely packed 22 sticky spheres (DMRT-QMS), ice volume fraction, SNOWPACK, 23 snowpack, stickiness, sticky hard sphere (SHS), X-band. 24 I. INTRODUCTION 25 S NOW on Earth influences natural processes, such as 26 global radiation balance, hydrological cycle, and glacier

Assessments of forest cover, forest carbon stocks and carbon emissions from deforestation and degradation are increasingly important components of sustainable resource management, for combating biodiversity loss and in climate mitigation policies. Satellite remote sensing provides the only means for mapping global forest cover regularly. However, forest classification with optical data is limited by its insensitivity to three-dimensional canopy structure and cloud cover obscuring many forest regions. Synthetic Aperture Radar (SAR) sensors are increasingly being used to mitigate these problems, mainly in the L-, C-and X-band domains of the electromagnetic spectrum. S-band has not been systematically studied for this purpose. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest characterisation. The Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model is utilised to understand the scattering mechanisms in forest canopies at S-band. The MIMICS-I model reveals strong S-band backscatter sensitivity to the forest canopy in comparison to soil characteristics across all polarisations and incidence angles. Airborne S-band SAR imagery over the temperate mixed forest of Savernake Forest in southern England is analysed for its information content. Based on the modelling results, S-band HH-and VV-polarisation radar backscatter and the Radar Forest Degradation Index (RFDI) are used in a forest/non-forest Maximum Likelihood classification at a spatial resolution of 6 m (70% overall accuracy, κ = 0.41) and 20 m (63% overall accuracy, κ = 0.27). The conclusion is that S-band SAR such as from NovaSAR-S is likely to be suitable for monitoring forest cover and its changes.

In this study an airborne ground penetrating radar (GPR) is used to estimate spatial distribution of snow accumulation in the Samudra Tapu glacier (the Great Himalayan Range), Western Himalaya, India. An impulse radar system with 350 MHz antenna was mounted on a helicopter for the estimation of snow depth. The dielectric properties of snow were measured at a representative site (Patseo Observatory) using a snow fork to calibrate GPR data. The snow depths estimated from GPR signal were found to be in good agreement with those measured on ground with an absolute error of 0.04 m. The GPR survey was conducted over Samudra Tapu glacier in March 2009 and 2010. A kriging-based geostatistical interpolation method was used to generate a spatial snow accumulation map of the glacier with the GPR-collected data. The average accumulated snow depth and snow water equivalent (SWE) for a part of the glacier were found to be 2.23 m and 0.624 m for 2009 and 2.06 m and 0.496 m for 2010 respectively. Further, the snow accumulation data were analysed with various topographical parameters such as altitude, aspect and slope. The accumulated snow depth showed good correlation with altitude, having correlation coefficient varying between 0.57 and 0.84 for different parts of the glacier. Higher snow accumulation was observed in the north-and east-facing regions, and decrease in snow accumulation was found with an increase in the slope of the glacier. Thus, in this study we generate snow accumulation/SWE information using airborne GPR in the Himalayan terrain.

The purpose of this paper is to simulate the backscattered signal by experimental data and field working then, comparing with the backscattered signal from actual L-band SAR data over arid to semi-arid environments. The experimental data included the laboratory-measured dielectric constant of soil samples and the roughness parameter. A backscattering model used to simulate the backscattering coefficient in sparse vegetation land cover. The backscattering coefficient (σ˚) simulated using the AIEM (advanced integral equation model) based on the experimental data. The roughness data were considered by the field observation, chain method measuring and photogrammetry simulation technique by stereo image of ground real photography. The simulated backscattering coefficients were compared with the real extracted backscattering coefficient (σ˚) from the ALOS PALSAR single and dual polarization mode data. The most problem in backscattering simulation was the vegetation water content. Therefore, the water-cloud model using the water index result of optical data applied on the simulated backscatter model for enhancement the backscattering heterogeneity from vegetation water contents due to the mix pixel of vegetation in spars vegetation. At the results the AIEM model overestimated the backscattering simulation, it might be cause of high sensitivity of this model to roughness. The ALOS PALSAR HV polarization mode is more sensitive than the HH mode to vegetation water content. The water-cloud model could improve the result and the correlation function of the samples was increased but, the difficulties were the input the A and B parameters to model.

The highly dynamic nature of snow requires frequent observations to study its various properties. Keeping this in mind, the present investigation presents results from the analysis of fully polarimetric synthetic aperture radar (POLSAR) parameters for the development of a snow depth (SD) inversion model for SD retrieval. Snow depth retrieved using ground penetrating radar (GPR) at 500 MHz over Austre Grønfjordbreen in the Svalbard region was used to understand the behaviour of certain polarimetric parameters. A significant correlation was found between field-measured SD and POLSAR parameters, namely coherence and normalized volume scattering power (R2 = 0.84 and R2 = 0.73, respectively.) Using the POLSAR scattering powers obtained from the six-component model-based decomposition (6SD), the heterogeneity and anisotropic behaviour in the firn areas are also explained. Further, based on the analyses shown in this work, a polarimetric parameter-based SD inversion algorithm have been pro...

Snow patch distribution and snow melt patterns during the summer are important controls for terrestrial ecosystems, permafrost and active layer, as well as for infrastructure access and management in the Maritime Antarctic. The mountainous terrain of the Maritime Antarctic and relatively small extent of the ice-free areas generate complex mosaics of numerous small snow-patches, ranging from tens to hundreds of meters in extension. These can only be accurately mapped using high resolution remote sensing sensors. However, the extremely high number of days with cloud cover limits the application of optical sensors from satellites, which have provided only sporadic snapshots in the Maritime Antarctic, limiting its use for monitoring purposes. In this paper we evaluate the application of Radar scenes from TerraSAR-X obtained in High Resolution SpotLight mode for mapping snow patches at a test area in Fildes Peninsula (King George Island, South Shetlands). Field analysis of the snow condi...

Snow patch distribution and snow melt patterns during the summer are important controls for terrestrial ecosystems, permafrost and active layer, as well as for infrastructure access and management in the Maritime Antarctic. The mountainous terrain of the Maritime Antarctic and relatively small extent of the ice-free areas generate complex mosaics of numerous small snow-patches, ranging from tens to hundreds of meters in extension. These can only be accurately mapped using high resolution remote sensing sensors. However, the extremely high number of days with cloud cover limits the application of optical sensors from satellites, which have provided only sporadic snapshots in the Maritime Antarctic, limiting its use for monitoring purposes. In this paper we evaluate the application of Radar scenes from TerraSAR-X obtained in High Resolution SpotLight mode for mapping snow patches at a test area in Fildes Peninsula (King George Island, South Shetlands). Field analysis of the snow condi...

There is a strong interest in assessing the potential of space-based monitoring and mapping of state variables that are critical to hydrological and agricultural applications. Our study consists of the acquisition of ASAR imagery in single and alternating polarization modes and at different incidence angles over the Campidano plain in south-central Sardinia (Italy), the island's most important agricultural region. In tandem to image acquisition, ground data (surface soil moisture and roughness) is being collected. The project will investigate soil moisture dynamics and detection at both the large scale (multitemporal analysis for the Campidano region) and the small scale (retrieval algorithms tested on individual field plots). This paper will focus mainly on the field scale work, where ground data and imagery from the period Jun-Nov 2005 have been used to assess a semi-empirical model for surface soil moisture and roughness inversion from the radar signal.

The current study has been done using Polarimetric Synthetic Aperture Radar (SAR) data to estimate the dry snow density in Manali sub-basin of Beas River located in state of Himachal Pradesh, India. SAR data from Radarsat-2 (RS2), Environmental Satellite (ENVISAT), Advanced Synthetic Aperture Radar (ASAR) and Advanced Land Observing Satellite (ALOS)-Phased Array type L-band Synthetic Aperture Radar (PAL-SAR) have been used. The SAR based inversion models were implemented separately for fully polarimetric RS2, PALSAR and dual polarimetric ASAR Alternate polarization System (APS) datasets in Mathematica and MATLAB software and have been used for finding out dry snow dielectric constant and snow density. Masks for forest, built area, layover and shadow were considered in estimating snow parameters. Overall accuracy in terms of R 2 value and Root Mean Square Error (RMSE) was calculated as 0.85 and 0.03 g cm −3 for snow density based on the ground truth data. The retrieved snow density is highly useful for snow avalanche and snowmelt runoff modeling related studies of this region.