G. Venkataraman

Changes in the glaciers of Chandra–Bhaga basin, Himachal Himalaya, India, between 1980 and 2010 measured using remote sensing

This study reports the glacier changes of Chandra–Bhaga basin, northwest Himalaya, India, from 1980 to 2010. Satellite remote-sensing data from the Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM), the Linear Imaging Self Scanning Sensor (LISS) and Advanced Wide Field Sensor (AWiFS) of the Indian Remote Sensing (IRS) series, and the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) were used to study the changes in glacier parameters such as glacier area, length, snout elevation, and the impact of glacier topographical parameters (glacier slope, aspect, and altitude range) on the glacier changes. It was found that the total glaciated area had shrunk to 368.2 km2 in 2010 from 377.6 km2 in 1980, a loss of 2.5%. The average position of glacier terminuses retreated by 465.5 ± 169.1 m from 1980 to 2010 with an average rate of 15.5 ± 5.6 m year−1. The decadal scale analysis showed that the average rate of retreat had increased the most in the recent decade. A moraine-dammed lake located in the study region was found to have expanded in area from (0.65 ± 0.01) km2 in 1980 to (1.26 ± 0.03) km2 in 2010. Glaciers with steep slope and less altitude range have lost more area than the glaciers having gentle slope and greater altitude range.

Spatial Modeling for Base-Metal Mineral Exploration Through Integration of Geological Data Sets

This study involves the integration of information interpreted from data sets such as LandsatTM, Airborne magnetic, geochemical, geological, and ground-based data of Rajpura—Dariba,Rajasthan, India through GIS with the help of (1) Bayesian statistics based on the weights ofevidence method and (2) a fuzzy logic algorithm to derive spatial models to target potentialbase-metal mineralized areas for future exploration. Of the 24 layers considered, five layers(graphite mica schist (GMS), calc-silicate marble (CALC), NE-SW lineament 0–2000 mcorridor (L4-NESW), Cu 200–250 ppm, and Pb 200–250 ppm) have been identified from theBayesian approach on the basis of contrast. Thus, unique conditions were formed based onthe presence and absence of these five map patterns, which are converted to estimate posteriorprobabilities. The final map, based on the same data used to determine the relationships, showsfour classes of potential zones of sulfide mineralization on the basis of posterior probability.In the fuzzy set approach, membership functions of the layers such as CALC, GMS, NE-SWlineament corridor maps, Pb, and Cu geochemical maps have been integrated to obtain thefinal potential map showing four classes of favorability index.

Capability Assessment of Fully Polarimetric ALOS–PALSAR Data for Discriminating Wet Snow From Other Scattering Types in Mountainous Regions

This paper examines the capability assessment of fully polarimetric L-band data for the snow and nonsnow-area classifications. The data sets used are the fully polarimetric Advanced Land Observation Satellite-Phased Array-Type L-Band Synthetic Aperture Radar data, optical Advanced Land Observing Satellite (ALOS)-advanced visible and near-infrared radiometer-2 data close to the radar acquisition, and environmental satellite-advanced synthetic aperture radar data. Several parameters are used to discriminate the snow-covered areas from nonsnow-covered areas in the Indian Himalayan region, including backscattering coefficients, the ratio of cross/copolarized backscattering power and polarization fraction (PF) value. Supervised classification schemes are employed using polarimetric decomposition methods based on the complex Wishart classifier. The accuracy of the classification was found to be 97.95% for the Wishart-supervised classification. Among various parameters and methods, it was found that the alternative newly proposed PF scheme, based on the implementation of fully polarimetric synthetic aperture radar data, yielded the best classification result in the absence of the training samples. The PF value has been effective for discrimination of the snow-covered areas from nonsnow-covered areas, debris-covered glacier, and vegetation. The results of this investigation show that L-band fully polarimetric SAR data provide considerable improvement but may not possess the optimal capability to discriminate snow from other inherent natural and man-made scatterers in heavy snow-laden mountainous scenarios, which may require fully polarimetric S-band or C-band PolSAR measurements.

Remote sensing study of snowline altitude at the end of melting season, Chandra-Bhaga basin, Himachal Pradesh, 1980–2007

Glaciers have a direct relation with climate change. The equilibrium line altitude (ELA) is the most useful parameter to study the effect of climate change on glaciers. The ELA is a theoretical snowline at which the glacier mass balance is zero. Snowline altitude (SLA) at the end of melting season is generally regarded as the ELA. Glaciers of Chandra-Bhaga basin in Lahaul–Spiti district of Himachal Pradesh were chosen to study the ELA, using satellite images from 1980 to 2007. A total of 19 glaciers from the Chandra-Bhaga basin were identified and selected to carry out the study of ELA variation over 27 years. This study reveals that the mean SLA of the sub-basin has increased from 5009 ± 61 m to 5401 ± 21 m from 1980 to 2007. The study is in agreement with the reported increase in the temperature and decrease in winter snowfall of North–West Himalaya in the last century.

SAR interferometric coherence analysis for snow cover mapping in the western Himalayan region

Abstract Information of snow cover (SC) over Himalayan regions is very important for regional climatological and hydrological studies. Precise monitoring of SC in the Himalayan region is essential for water supply to hydropower stations, irrigation requirements, and flood forecasting. Microwave remote sensing has all weather, day and night earth observation capability unlike optical remote sensing. In this study, spaceborne synthetic aperture radar interferometric (InSAR) coherence analysis is used to monitor SC over Himalayan rugged terrain. The feasibility of monitoring SC using synthetic aperture radar (SAR) interferometry depends on the ability to maintain coherence over InSAR pair acquisition time interval. ERS-1/2 InSAR coherence and ENVISAT ASAR InSAR coherence images are analyzed for SC mapping. Data sets of winter and of snow free months of the Himalayan region are taken for interferogram generation. Coherence images of the available data sets show maximum decorrelation in most of the area which indicates massive snowfall in the region in the winter season and melting in the summer. Area showing coherence loss due to decorrelation is mapped as a snow-covered area. The result is validated with field observations of snow depth and it is found that standing snow is inversely related to coherence in the Himalayan region.

Snow permittivity retrieval inversion algorithm for estimating snow wetness

The environmental satellite (ENVISAT) advanced synthetic aperture radar (ASAR) offers the opportunity for monitoring snow parameters with dual polarization and multi-incidence angle. Snow wetness is an important index for indicating snow avalanche, snowmelt runoff modelling, water supply for irrigation and hydropower stations, weather forecasts and understanding climate change. We used a first-order scattering model that includes both volume and air/snow surface scattering based on a developed inversion model to estimate snow dielectric constant, which can be further related for estimating snow wetness. Comparison with field measurement showed that the correlation coefficient for snow permittivity estimated from ASAR data was observed to be 0.8 at 95% confidence interval and model bias was observed as 2.42% by volume at 95% confidence interval. The comparison of ASAR-derived snow permittivity with ground measurements shows the average absolute error 2.5%. The snow wetness range varies from 0 to 15% by volume.

Spaceborne InSAR Technique for Study of Himalayan Glaciers using ENVISAT ASAR and ERS Data

An endeavor is made for the study of movement of Himalayan glaciers using Spaceborne InSAR technique, which is based on preserving the coherence between two acquisitions of the same scene. Gangotri, Siachen, Bara Shigri and Patsio are major glaciers in the Himalayan region, which are showing retreat, and their respective tributary glaciers completely disconnected from main body of glaciers. ERS-1/2 observations show high correlation on glacier area and hence movement of Siachen and Gangotri glacier are measured. Information about dynamism of glaciated terrain can be retrieved by counting differential interferograms. Displacement of Gangotri glacier in the radar look direction has been observed as 8.4 cm represented by 3 fringes. Siachen glacier exhibits a displacement of 22 cm represented by 8 fringes. ERS-1/2 tandem data over all these glaciers show highest correlation over glacier areas but ENVISAT ASAR data shows coherence loss over glacier area due to decorrelation. Coherence loss is usual phenomena in glaciated terrain as repeativity of sensor is high (35 days for ENVISAT). Among all these, Siachen glacier shows highest coherence and then Gangotri, respectively. A tandem pair of ERS-1&2 acquired on April 1 and 2, 1996 in descending pass over Siachen shows high coherence than the ascending pair acquired on May 2 and 3, 1996. It is due to change in climate between two acquisitions at glacier locations. A systematic monitoring of dynamism of Himalayan glaciers can be done using Permanent Scatterer Interferometric SAR (PSInSAR) if we place a corner reflector on the glaciers.

Estimation and validation of glacier surface motion in the northwestern Himalayas using high-resolution SAR intensity tracking

We estimate two-dimensional (2D) glacier surface motion using synthetic aperture radar (SAR) X-band intensity tracking. It has been observed that the viability of SAR interferometry (InSAR) is often limited by coherence loss over glaciers in landlocked regions using SAR data pairs of more than 1 day temporal baseline. An alternative to InSAR is the intensity-tracking approach, which relies on intensity cross-correlation for the estimation of subpixel surface motion in range and azimuth direction. In this work, we apply this approach for 2D glacier surface motion estimation in the north-western (NW) Himalayas, using TerraSAR-X (TS-X) spotlight mode high-resolution data pairs of 11, 22, and 33 day temporal separation. The results are in good agreement with total station surveying measurements synchronous with the satellite data acquisition period. The technique is found to be highly appropriate for monitoring the flow rate of glaciers in the Himalayas on a multitemporal basis.

Development of an inversion algorithm for dry snow density estimation and its application with ENVISAT-ASAR dual co-polarization data

Radar remote sensing has great potential to determine the extent and properties of snow cover. Availability of space-borne sensor dual-polarization C-band data of environmental satellite- (ENVISAT-) advanced synthetic aperture radar (ASAR) can enhance the accuracy in measurement of snow physical parameters as compared with single polarization data measurement. This study shows the capability of C-band synthetic aperture radar (SAR) data for estimating dry snow density over snow covered rugged terrain in Himalayan region. The snow density is an important parameter for the snow hydrology and avalanche forecasting related studies. An algorithm has been developed for estimating snow density, based on snow volume scattering and snow-ground scattering components. The radar backscattering coefficients of both horizontal–horizontal (hh) and vertical–vertical (vv) polarization and incidence angle are used as inputs in the algorithm to provide the snow dielectric constant which can be used to derive snow density using Looyengas semi-empirical formula. Comparison was made between snow density estimated from algorithm using ENVISAT-ASAR hh and vv polarization data and the measured field value. The mean absolute error between estimated and measured snow density was found to be 0.024 g/cm3.

InSAR Coherence Measurement Techniques for Snow Cover Mapping in Himalayan Region

Snow cover area is a very important parameter for snowmelt runoff modeling and forecasting. Snow cover information is also useful for managing transportation and avalanche forecasting. Our study area includes Gangotri glacier region, Siachen glacier region and Beaskund glacier region in the North-West Himalayas of India. Our previous studies discuss the capability of several algorithms for optical sensor as well as SAR to map the snow cover area in Himalayan regions. In recent years, the SAR interferometry has provided number of attractive applications in landuse/landcover mapping. This study discusses the capability of both backscattering ratio techniques and InSAR coherence measurement techniques for snow cover mapping in Himalayan region with repeat passes data of ERSfrac12 and ENVISAT-ASAR. By analyzing the several pairs of ENVISAT repeat passes ASAR images for the study area, we find that the coherence measurement from bare soil, bare rock and vegetation are high and snow covered area and glacier area have very low coherence except in one day difference image.