The melting of glaciers in the Himalayan region is connected to the formation and expansion of proglacial lakes. The proliferation of these lakes heightens the risk of glacial lake outburst floods (GLOFs). This study employs geospatial techniques to investigate the glacial systems (glacial bodies and connected glacial lakes) near the South Lhonak glacial system. Using Corona and Landsat datasets spanning from 1967 to 2023, substantial increases in the size of the South Lhonak Glacial Lakes (SLGL) and North Lhonak Glacial Lake (NLGL) are observed. SLGL and NLGL exhibit glaciological and morphological similarities akin to sister glacial lakes. Notably, SLGL receives input from NLGL through a narrow stream, leading to a more rapid increase in its size. Similar characteristics are found in Longbasaba Glacial Lake (LGL) and Kaer Glacial Lake (KGL) in the Nepal Himalayas, categorizing them as sister lakes. Principal Component Analysis is employed to determine the mean albedo of glacial bodies since 1989, with higher glacial debris and a lower mean albedo identified in the South Lhonak glacier. The study also reveals the internal moraine wall's failure in the KGL embankment, indicating the potential instability of naturally deposited moraine embankments and the risk of future hazards. Lastly, a social vulnerability assessment for the Sikkim GLOF on 4thOctober 2023 is conducted, and a Vulnerability Scoping Diagram (VSD) is developed to prioritize resources and enhance disaster response efforts.

Snow grain size is a fundamental property of snow and is directly proportional to its surface area. The stability of the snowpack has often been investigated in snow avalanches using data from the size and shape of the snow grains. The spatial and temporal change in the snow grain size can help characterize the thermal state of the snowpack, and to estimate the temporal and spatial distribution of snowmelt. The grain size of snow becomes coarser with melting and shows lower spectral albedo. This study shows the snow grain size mapping of the South Lhonak glacier region after the flash flood event of a Lake occurred on 4thOctober 2023. The snow grain size mapping is performed using recent PRISMA hyperspectral data acquired on 8thOctober 2023 by the Italian Space Agency. The JHU spectral library of snow grain size is given as an endmember, input to spectral information divergence method for hyperspectral grain size mapping. In the absence of the in-situ measurement absorption band area method, which signifies the amount of energy absorbed by the snow/ice particles has been employed to validate the mapped snow grain size. The trend of energy absorbed by mapped snow grain size and the corresponding JHU spectral library corroborate well. The wavelength region centered at 1.03μm is found to be suitable for understanding the grain size of the snowpack. Coarser snow was found to be prominent in the study area which aggress with the Himalayan field circumstances in the month of ablation.

The eco-hydrology of the Himalayan catchments depends on their glacial and snow coverages as well as associated dynamics. These components of the Himalayan cryosphere can be seen as tracers of climate variability. In this study, MOD10A2 products have been used along with Landsat-5/8 datasets to capture the spatiotemporal fluctuations in the intra-annual snow cover of Arunachal Pradesh and its Tawang basin. Snow cover has been mapped for the past 21 years 2000-2021, for both the ablation and accumulation period using MOD10A2 products and normalized difference snow index (NDSI) (threshold: 0.4). The accumulation and ablation period snow cover shows decreasing and increasing trend respectively for the entire Arunachal Pradesh. However, for the Tawang basin, the accumulation and ablation period snow cover trend seems to be stable at 450 Km2and 100 Km2,, respectively. The contaminated snow cover of the Tawang region on 16 February 2022 (Landsat-8) has been identified as 564.42 Km2(53.7%). ALOS PALSAR digital elevation model (DEM) has been used to identify glacial lakes (slope <4°) within the Tawang basin.

Earthquakes associated with strong ground vibration are a significant factor in infrastructural damage. Since earthquake impact is observed over a large area, satellite remote sensing can be effectively used to perform seismic impact assessment. The present study attempts to investigate the damage around the Lawar Mandi region due to the Mw6.0 Afghanistan earthquake (21 June 2022) triggered at a hypocenter depth of 4 Km. The damage assessment is performed with the help of radar interferometry in conjunction with optical remote sensing techniques. The vertical seismic deformation as obtained from Sentinel-1, shows ground subsidence that reaches a maximum value of 179 mm near the epicenter. A co-seismic surface break along the northeast-southwest direction is also observed. Some of the locations around infrastructures of the Lawar Mandi region show reduced co-seismic coherence with increased tasseled cap transformation (TCT)-wetness difference and temporal difference liquefaction index (TDLI) using Landsat-8 OLI, indicating the possibility of liquefaction/cyclic mobility.

One of the most devastating repercussions of an earthquake is soil liquefaction. Traditional field investigation methodologies allow for the prediction of liquefaction-related damages. However, there are numerous obstacles in doing field investigations, including inaccessibility, cost, and instrument-related drawbacks. In this study, liquefaction-triggered changes in soil moisture content have been derived using geospatial techniques as a qualitative analysis. The 3rdJan 2017 earthquake of Mw 5.7 that had hit Agartala city and its vicinity left a mark of its near Kanchabari site in the form of ground fissures. This site has been selected as the reference liquefaction site for the analysis. Pre- and post-earthquake optical satellite imageries have been used to detect changes in soil moisture using band ratios and statistical technique such as tasseled-cap transformation. The algorithms have shown an increment in soil-moisture around the liquefied site. However, a detailed field-based geotechnical investigation is a must for a quantitative analysis.

Earthquakes fall in catastrophic natural disasters that affect man-kind, buildings, and other properties. In the Himalayan region, an earthquake can be seen as an agent that triggers other natural hazards such as landslides, and lake outburst floods due to moraine-dam breach. Such events occur due to alteration in the shear strength properties of soil triggered by a tectonic event. In this study, an attempt has been made to investigate the potential of interferogram and coherence derived from Sentinel-1 SLC to identify the changes caused by MW5.7 earthquake (20-Mar-2020) around the Lake Dingmu, Tibet. The pre- and co-seismic interferogram and coherence images for the surrounding region of Lake Dingmu have been generated. Subsequently, the decreased coherence around the lake periphery have been investigated for soil liquefaction/cyclic mobility through Temporal difference liquefaction index (TDLI) using Landsat-8 OLI. The TDLI detects the changes in the soil moisture content due to the earthquake event. The results of Sentinel-1 SLC data corroborate well with the results of optical remote sensing data. It is evident from the analysis that a significant amount of changes occurred due to the earthquake. However, the topography makes the lake very stable.

The Himalayan cryosphere or the third pole is a dynamic component of the Earth System. The Himalayan landscape's weather conditions, topography, and seismicity results in various natural hazards such as landslides, outburst floods, and avalanches. Avalanches are sudden and endanger life and property, especially in the Annapurna mountain range of Nepal. In this study, an attempt is made for the first time to identify the activation zones of snow avalanches that occurred on 17th Jan 2020 around some of the major peaks of the Annapurna mountain range. The post-avalanche backscatter intensities overlaid on the topographic slope of the area from ALOS-PALSAR DEM helped in capturing possible release areas near the peaks. This helped in identifying the avalanche activation zones that can be helpful in planning the mitigation. Radar backscatter intensities derived using Sentinel-1A SLC products helped in the temporal classification of the area into recent and older avalanches.

Monitoring of glaciers has become a necessity due to the recent changes in regional climate as well as the increase in major development activities, downstream of glacier-fed rivers. Monitoring of the Zemu glacier, the largest glacier in the eastern Himalayas holds a great significance as it has a major contribution to the discharge of the Teesta River which has huge socio-economic importance. Due to lack of connectivity and harsh terrain, it is difficult to obtain field-based data from the Zemu glacier. Therefore, remote sensing methods such as Accumulation Area Ratio (AAR) are generally utilized to assess the health of the glacier. Being Summer accumulating type glacier, cloud cover and frequent snowfall during the ablation period makes it difficult to accurately map the accumulation area. This research article aims to constitute an approach to reduce this limitation to some extent by developing a relationship between equilibrium line altitude (ELA) and the specific mass balance of the glacier.

Rispana is an evolving river basin. The river has passed its youthful landform development stage and entered “maturity”. Over the years, the river's flow has reduced due to various reasons. Despite the reduced flow, the region's physical landscape is vulnerable to soil erosion and floods. With the current trend of urban expansion and resource use, the area will face a severe shortage of freshwater. This work uses a combination of geomorphic markers to quantify the drainage basin and trace the changes. The morphometric parameters suggest the reducing influence of geological structure and the increasing control of climate and anthropogenic factors on the river's flow. Additionally, the circulatory ratio highlights that despite the region being vulnerable to floods, it is less prone to flash floods, and flood management would be easier. Using a combination of LANDSAT and ALOS-PALSAR datasets, it was also determined that the river intends to shift its meanders.

This paper focuses on remote sensing of Radar Polarimetry to determine the snow geophysical parameters particularly snow dielectric constant and snow density in the North Sikkim region of India. The analysis utilizes the dual-polarimetric C-band of Sentinel-1A (VH&VV) synthetic aperture radar data, field observation, and other ancillary information for the retrieval of snowpack dielectric and snow density. Physical Optics Model (POM) for surface scattering-based inversion model has been employed and the C2 matrix components of both VH and VV polarization and incidence angle are given as input to develop the algorithm. The algorithm gives the snow dielectric constant which can further be related to snow density using Looyenga's semi-empirical formula. The field value of snow density in the study zone has been compared to the algorithm-estimated snow density and the root means the squared error is observed to be 0.1973.

Land Surface Temperature (LST) plays a significant role in detecting surficial anomalies such as sudden fire outbreak, geothermal leakage, volcanic activities etc. In this study, an attempt has been made to analyze the Baghjan oilfield blowout and its local impact using remote sensing as a tool. The blowout occurred due to hydrocarbon leakage on 27th May, 2020 in well-5 located at Tinsukhia district of Assam, India. Sentinel-2 MSI and Landsat-8 TIRS/OLI bands have been used to derive LST in order to identify smoulder using the split-window (SW) algorithm. The local damage to vegetation cover is quantified using normalized burn ratio (NBR) and the severity is calculated through ΔNBR. LST revealed hike in surface temperature of the nearby regions of well-5 possibly due to local heat trap resulting from heavy smoke and smoulder emission. This could be due to hydrocarbon combustion producing enormous amount of CO2 and water vapour creating a local heat island. The blowout resulted in significant damage to the nearby vegetation and forest cover affecting an area of 34,200 m2 out of which 15,300 m2 of area suffered severe damage.

Sea water carbon dioxide partial pressure is the major controlling factor in the air-sea CO2gas exchange. The seasonal and spatial distribution of Carbon Dioxide Partial Pressure (pCO2_sw) is vastly regulated by the physical, chemical and biological parameters of the ocean whereas alterations in the atmospheric pCO2is minimal. Although the global ocean is a net CO2sink, regional fluctuations in the CO2partial pressures can have potential consequences on the universal trend. Being one of the least sampled oceanic region, the chief elements regulating the Bay of Bengal (BoB) partial pressures are yet to be understood. An attempt has been made to analyse the significance of biological and chemical properties in defining the spatial distribution of the sea surface partial pressures as well as the influence of monsoonal river influx in BoB. Results revealed an equal importance of the chemical and biological factors on the partial pressure distribution. The Multiple Linear Regression (MLR) and Support Vector Regression (SVR) algorithms developed from Sea Surface Salinity (SSS) and Sea Surface Temperature (SST) showed to give better output in the post monsoon, while they tend to underestimate the values in the pre-monsoon season due to interference by biological factors. A strong influence of the fresh water discharge on the surface salinity was observed which in turn has implications on the spatial distribution of sea water partial pressures where the pre-monsoon value range of 400-430μatm was decreased to 386-417μatm range in the post monsoon.

Climate change being in the verge of all discussions points most of its focus on the change in the snow cover area which leads to increase in sea surface level in the long term and sometimes flood like scenario in the short term. So monitoring the snow areas with respect to time is a must to understand the effects of climate change more closely. This work demonstrate the application of Feature Oriented Principal Component Analysis (FPCA), also called as "Crosta technique" [1]. FPCA is a multivariate statistical technique used to transform the set of relatively correlated spectral bands of Landsat 8 to uncorrelated Principal Components. The statistical interpretation of the loadings of the SWIR wavelength band (sensitive to snow/glacier) in different PCs were used to generate a snow/glacier color composite image (Crosta image) of the Teesta river basin, Sikkim, India.

Syrtis Major Planum is a major volcanic construct on Mars ridden with a large number of fluvial channels mostly draining into the adjacent Isidis basin. These channels have been attributed to have formed by lava flows from the calderas of the construct onto the basin. However, with availability of high spatial and spectral resolution remote sensing datasets, new findings in the region over time have indicated possible presence of hydrological channels in Syrtis Major. We explore one such feature in the volcanic construct that seems to have been altered by hydrological activity. High abundance of hydroxylated and hydrated minerals have been found in the region which support this conclusion that lava might not be the only factor causing potential channel generation in the region.

River interventions disturb the natural flow regime of channel. The impacts generated from river interventions is categorized based on the alteration of fluvial system including channel planform and ecology. The Brahmani River, one of the major peninsular river holds a significant importance for three major states of eastern India. This river has been subjected to periodic flooding events damaging high value property. Rengali multi-purpose river valley project (since 1985), located along middle reach of Brahmani, influence the downstream stretch behavior. A planform variation of increased braiding pattern is observed for downstream river. Interaction of reservoir-catchment along with planform variation assessment embraces a substantial importance for geologists and engineers. This research article aims to quantify variation in channel planform for pre-Rengali and post-Rengali time period along a selected reach integrating Sinuosity Index (SI) and Braid-Channel Ratio (BR) parameters using remote sensing techniques.

Calcrete, the calcium carbonate duricrust generally occurs in arid/semiarid region. Globally, it has been used as a non-traditional constructional material. The recent discovery of calcrete hosted secondary uranium deposits in Australia and Namibia has kindled interest in exploration of calcretes in many parts of the world. In this study, palaeochannel related calcretes of the Thar desert, India is explored as a possible source for uranium mineralization. The adopted exploration strategy includes mapping of calcretes using hyperspectral satellite data, in-situ radiometric survey, analyses of field collected samples for mineralogy and geochemistry. Calcretes along palaeochannels were mapped using Hyperion data, field spectra and Spectral Angle Mapper (SAM) technique. It was found that the adopted technique could also differentiate high-, and low-Mg calcretes with 72% accuracy. Mineralogy of calcrete includes calcite (40-60%), quartz (30-45%) and feldspar (10-15%) with minor amount of clay minerals (montmorillonite, kaolinite, illite, goethite). In in-situ radiometric survey, the range of uranium, thorium and potassium in the calcretes varies from 2.4-11ppm, 5-28.2ppm, and 0.8-4.2% respectively.

This study evaluates the effect of grain-size, fabric, and composition of minerals on bidirectional reflectance and emission spectra. For this purpose, mineral grains of quartz (high albedo), feldspar (moderate albedo), and amphibole (low albedo) with four different grain-size ranges were analyzed using a goniometer system equipped with a spectroradiometer. Reflectance and emission spectra of bi-component mineral assemblages prearranged in seven different fabrics were analysed. It was observed that the parameters under investigation significantly influenced the intensity of reflection, scattering directions, spectral shape, and absorption depth, which in turn affected quantitative abundances estimated by techniques based on spectral similarity like Linear Mixture Model (LMM). It was observed that the error in abundances estimated by LMM varied from 3% to 15%. The authors conclude that the parameters under investigation, if neglected can introduce significant errors in geological interpretations.

This study aims at analysing the spectral characters of high turbid coastal waters to retrieve the Suspended Sediment Concentration (SSC) in Gulf of Cambay, India. For this purpose, the Ocean Colour Monitor (OCM) data was processed using quasi-synchronous field, and laboratory spectral reflectance measurements. Spectral similarity between the image-spectra and library-spectra estimated by Spectral Angle Mapper (SAM) algorithm was used to retrieve SSC. The result obtained by SAM algorithm was compared with Total Suspended Matter (TSM) and Suspended Sediment Matter Retrieval (SSMR) algorithms. It was found that for case-II waters, the longer wavelength (743 nm and 835 nm) is very sensitive to SSC changes. Hence, the SAM-based approach involving all wavelength regions is found to be very efficient and match with field measured SSC.