Search

Information about the surface ice velocity is one of the important parameters for Mass balance and Glacier dynamics. This study estimates the surface ice velocity of Chhota Shigri glacier using Landsat (TM/ETM+) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) temporal data-sets from a period of 2009 to 2016 and 2006 to 2007, respectively. A correlation based Particle Image Velocimetry (PIV) technique has been used for the estimation of surface ice velocity. This technique uses multiple window sizes in the same data-set. Four window sizes (low, medium, high, very high) are used for each image pair. Estimated results have been compared with the published data. The outcomes attained from the medium window size closely matches with the published results. The estimated mean surface ice velocities of medium window size are 24 and 28.5 myr−1 for 2009/2010 and 2006/2007 images pair. Highest velocity is observed in middle part of the glacier while lowest in the accumulation zone of the glacier. [ABSTRACT FROM AUTHOR]

Mountain Glaciers are natural resources of fresh water and these affect the stream flow of the rivers, regional climate and further global climate. Observed trends and projected future evolutions of climate and Cryospheric variables clearly suggest a need to monitor these changes. Accordingly, the article presents the glacier features mapping using Hyperspectral remote sensing imagery. A freely available Hyperion satellite imagery acquired over Gepang Gath glacier in Himachal Pradesh, India is used for the study. Each class is identified based on their surface characteristics of spectral reflectance properties. Identification is simplified by demarcating the study glacier into accumulation and ablation areas through snowline. Accumulation area is characterized with high reflectance clean snow/ice and reduced moderate reflectance Snow/firn. The identification of classes in Hyperion imagery is validated using the spectral library from USGS and ASTER, and field spectra obtained from literature. [ABSTRACT FROM AUTHOR]

This paper focuses on the development of a novel algorithm for deriving snowpack density over the snow-covered region of the Himalayas. The analysis utilizes fully polarimetric TerraSAR-X synthetic aperture radar data sets, field observations, and other ancillary information for the retrieval of snowpack density. The algorithm involves the development of a new generalized hybrid decomposition model. The generalized volume scattering parameter from the decomposition model is inverted for snow density estimation. A few field data measurements’ campaigns were carried out, within near-real time of satellite passing over the area, to collect various parameters such as temperature, water content, and the density of the snowpack at varying depths. These field observations are further used for validation of the results obtained from the inversion algorithm. It is also found that the model-estimated snowpack density is highly congruent with the field-measured snowpack density. The mean absolute error of snowpack density, root-mean-square error, and index of agreement are found to be 9.9 kg/ \textm^3 , 10 kg/ \textm^3 , and 0.96, respectively, which are well within the acceptable range. [ABSTRACT FROM PUBLISHER]

Bhaga Basin has complex mountainous terrain; little study has been done on the spatial and temporal characteristics of snow cover in the region. The Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day snow cover products between 2001 and 2012 for winter period (November–April) have been used to study the variation in snow cover area (SCA). The statistical analysis based on non-parametric Mann Kendall and Sen’s slope methods have been used for detecting and estimating trends for climatic variables (temperature and snowfall) and SCA for winter period. Results of statistical analysis indicate rise in minimum temperature (0.02 °C year−1) and fall in maximum temperature (0.17 °C year−1). It also shows decrease in mean seasonal snowfall (0.07 cm year−1). The seasonal SCA was found to decrease at the rate of 0.002% year−1. This study indicates that the climate change is probably one of the major causes for depleting SCA. [ABSTRACT FROM PUBLISHER]

The accuracy of DEMs shows wide variations from one terrain to another and it needs to be determined. This study evaluates NRSC (National Remote Sensing Centre, Hyderabad, India) CartoDEM V1 and V1.1R1 with respect to resampled ADS80 DEM for parts of the Himalayas. Both the test DEMs were properly registered with reference to resampled ADS80 DEM and then individually subtracted to get the difference DEMs. Visual and statistical analyses were performed to assess the quality of the tested DEMs in terms of visible terrain and vertical accuracy. For calculating the accuracies in different terrain classes, slope and aspect maps were generated from the ADS80 DEM. Properly registered Landsat5 TM data were used for the development of the land cover map with four classes. The overall vertical accuracy measured for CartoDEM V1 was 269.9 m (LE90), while CartoDEM V1.1R1 showed huge improvement in the accuracy with 68.5 m (LE90). [ABSTRACT FROM PUBLISHER]

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy. [ABSTRACT FROM AUTHOR]

Updated and Accurate Digital Elevation Model (DEM) of snow covered and glaciated mountainous area is essential for many applications such as avalanche hazard and numerical modelling of mass movements or mapping of terrain changes. The best high resolution terrain product available for Himalayan region is the DEM, with a spatial resolution of 10 m, generated using Cartosat-1 stereo ortho-kit data. Even this spatial resolution is insufficient for many applications like avalanche hazard mapping or forecasting in complex mountainous terrain. This study reports the process of high spatial resolution (1 m) DEM generation for Manali and nearby areas using digital aerial photogrammetric survey data of 40 cm Ground Sampling Distance (GSD), captured through airborne ADS80 push-broom camera for the first time in Indian Himalayas. This DEM was also evaluated with Differential Global Positioning System (DGPS) points for accuracy assessment. The ADS80 DEM gave Root Mean Square Error (RMSE) of ∼<1 m and Linear Error, at 90 % confidence interval (LE 90) of 1.36 m in comparison with the DGPS points. [ABSTRACT FROM AUTHOR]

This study established a decadal correlation between meteorological observations (temperature and snowfall) and satellite-derived seasonal snow cover for a glacier catchment. The study area was classified into 10 elevation zones. The time period for considering climatic variables was from the start of the significant fresh snowfall of the new season to the date of satellite image acquisition. The snowfall inputs from the five meteorological stations at different altitudes were interpolated for the entire catchment using a discretised thin-plate spline technique. A local temperature lapse rate for this specific time period was calculated. It was applied throughout the catchment for interpolating the temperature, which was further used to refine the interpolated snowfall. Such a hypsometric approach along with third-order polynomial curve fitting (R2 = 0.998) finally gave an equation for estimating percent snow-covered area for different elevation zones with a good accuracy and very low average RMSE (Root Mean Square Error) of 3.16 percent. [ABSTRACT FROM PUBLISHER]

Frequent avalanche activity and poor route visibility due to bad weather make snow bound mountainous regions quite unsafe for travel during the winter months. Hence, there is a need for an accurate navigation device that can help in the safe movement of mountain travellers in avalanche prone areas. This paper presents the design and implementation of a portable GPS-based warning and navigation system, capable of providing safe navigation to mountain travellers in avalanche-prone regions. The system uses a hand-held GPS with a positional accuracy of 2–5 m. A customized application has been developed for the visualization of maps, navigation, positioning, tracking and issuing avalanche path warning. On the basis of registered avalanche path data, this application updates the traveller at predefined time intervals on whether the current position of the traveller is inside or outside an avalanche path. When the traveller enters an avalanche prone area, a warning in the form of text and voice messages is generated by the device. For the testing and accuracy analysis of this application, a part of the Manali-Dhundi highway was designated as the study area. In numerous track tests, the system has demonstrated a high level of accuracy and a repetition in locating registered avalanche sites in open slopes/bare lands but accuracy deteriorated in narrow valley/forested areas. An analysis of the trial results shows that the system can help travellers in snowbound mountain regions as a warning and navigation tool, using accurately registered avalanche sites and an appropriate buffer size around these sites. [ABSTRACT FROM AUTHOR]

A new approach is presented for the detection of deformation of snow with the help of plate waveguide for avalanche warning. Avalanches are difficult to predict due to heterogeneity of the snow media and the uncertainties associated with triggering mechanisms. Monitoring of acoustic emission (AE) is a very effective non-destructive technique, which is applied to identify micro and macro-cracks and their temporal advancement in snow. The propagation of these elastic waves in attenuated media to long distance is helpful for extracting useful information for slope monitoring. Since the snow exhibits a high attenuation during wave propagation, a less attenuative media like plate sensors (solid steel and aluminium waveguide) is essential. Preliminary experiments towards the formation of Lamb waves in a plate coupled with snow was performed with the help of piezoelectric sensors. Different deformations (1-100 mm/min) were applied to various snow samples having different densities (300-450 kg/m³). The dependence of stress-strain with AE and visible crack is examined along with the wavelet transform. The wavelet transform (WT) was used and applied on the time-frequency of AE present in plate waveguide. Lamb waves are detected from a long distance, which help in understanding the physical condition of snow stability with the help of waveguide. [ABSTRACT FROM AUTHOR]