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.

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.

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.

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.

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.