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The cryosphere plays a vital role in the climate system by changing the energy and mass transfer between the atmosphere and the surface, and it is the most important land cover type in the Himalayan and Polar Regions, which act as an important source of freshwater for rivers. This study examines Snow-Covered Area (SCA) and Snowline variations in the Uttarakhand Himalaya using the Normalized Difference Snow Index (NDSI). Three Landsat series imagery for 1990, 2000, 2010, and Sentinel Data from 2015 to 2021 were processed and analyzed through open-source software. In order to estimate the average elevation of the snowline, a digital elevation model was used and an area estimation study using multispectral imagery. The research focuses on the snowline and snow cover variations over the Uttarakhand Himalaya from 1990 to 2021 and the average snow line-height, respectively. This study shows that in the years 1990, 2000, 2010, and 2015 to 2021, snow line variations and area estimation differences in Uttarakhand, Central Himalaya, and snow line at above sea level (a.s.l.) in the western and eastern part of the study area. This study deals with the analysis of snow line shifting and cover. It suggests that the snow cover area in the Uttarakhand, Central Himalaya, is depleting steadily, which will have adverse impacts, especially upon water resources causing various economic and social disruptions in the near future.

Himalayan mountain region lying in the northern part of Indian sub-continent is among those zones which bears the most ecologically sensitive environments and is also a repository of biodiversity, fresh water storage and ecosystem services. Over the last three decades, land transformation related to exploitative land uses is among the main drivers of changing snow cover, vegetation cover and productivity in western Himalayas region. In a region where field-based research is challenging due to heterogenous relief and high altitude, quantifying the changes in temperature pattern using Remote Sensing Techniques can provide essential information regarding variating trends in different elements relating to temperature. This paper studies the trend analysis of changing temperature patterns using SWAT data (1979–2014) over Uttarakhand Himalayas and its association with altitudinal gradient. This paper investigates the trends in maximum (Tmax), minimum (Tmin) & mean (Tmean) temperatures in the annual, seasonal and monthly time-scales for 55 stations in the 5 regions of Uttarakhand’s Western Himalayan region which are categorized on the basis of elevation, from year 1979-2014. Statistical approaches are used to examine the effect of change in pattern of temperature upon the phenology of vegetation in the region under study, fresh water ecosystems, agricultural productivity, decreasing snow line & increasing tree line, change in duration of the seasons etc.

There are several causes for the increasing rate of deglaciation, such as global warming, increase in the concentration of black carbon, and extensive use of fossil fuels which causes the change in the overall climate system and shifting glacier ecosystem. This study was conducted on Pindari valley glaciers part of lesser Himalaya in Uttarakhand. This study investigates to (1) monitor and map change in the frontal length or the snout region of a glacier that can be studied with the help of remote sensing techniques and (2) evaluate the decadal and annual retreat rate of the glacier from 1972 to 2018. The study applies both the maximum likelihood classifier and NDSI spectral indices based classification for extracting the glacier region for different periods. This study reveals a significant amount of retreats taking place in the selected glaciers, Pindari, Sundardhunga, Kafni, and Baljuri base camp glaciers, from 1972 to 2018 as 1719.95 m, 1751.21 m, 1057.01 m, and 810.78 m, respectively. The highest amount of change is noticed in Pindari and Sundardhunga glaciers, higher than ~ 1700 m. The study analyses temporal variation of the annual and decadal retreat rate in the Pindari valley glaciers, which would be helpful for the further study of the other glaciers.

Grasslands are the world's most extensive terrestrial ecosystem, which provides a variety of services for humans, such as carbon storage, food production, crop pollination, pest regulation, and are a major feed source for livestock. However, grasslands are today one of the most endangered ecosystems due to land-use change, agricultural intensification, land abandonment, as well as climate change. Grasslands are an integral part of human societies across the globe, which are broadly known as tropical savannah and temperate grasslands. In the Himalayan region, grasslands are found in more than 55% of the area and different climatic conditions lead to different varieties of grasslands like Danthonia grasslands, kobresia sedge meadow, etc. Grasslands deal with the spatial and temporal distribution of heterogeneous landscapes, which support a high diversity of various species. Owing to very rugged terrain and inaccessibility, the information on the extent of alpine grassland and percent grass cover (%) across the meadows is limited. Therefore, the present attempt was made to assess the current status of grassland in the alpine region of Uttarakhand above 3000 m asl. LANDSAT-8 (OLI and TIRS sensors) satellite data were used to delineate the grasslands using normalized difference vegetation indices (NDVIs) of the alpine region with the help of over 179 ground truth points out of which 50 points are testing points and 129 points are training points. Grass covers (%) were also assessed in the whole alpine region of Western Himalaya of Uttarakhand which nearly consists of over 75 meadows by using random plots (1 × 1 m, total 10 per site) in each meadow. Overall, 89.52% accuracy was achieved based on 50 randomly selected testing points. A total of 4949.25 sq. km area is under the different percentage of grass cover in the alpine region of Uttarakhand, Western Himalaya. Danthonia grasslands below 4000 m and Kobresia sedge meadows above 4000 m elevation are dominant in the state. In the alpine region, over 1056 sq. km grassland area have less than 10% grass cover indicating higher degraded and cold desert areas and only 565.69 sq. km area have more than 60% grass cover, which is highly favorable for rich biodiversity and grazing.

Himalayan mountain region lying in the northern piece of Indian sub-continent is among those zones which bears the most geologically fragile situations and are additionally a vault of biodiversity, new water stockpiling and environment administrations. The Himalaya is one of the world’s largest and mostly inaccessible area of glaciers outside the polar regions and provides glacier-stored water to the major perennial rivers of India throughout the year and to their river basins also. Glacier is a large ice mass formed by accumulation, compaction and re-crystallization of snow and firn due to stress of its own weight. Glacier with steep slopes of bedrock may retreat with slower rate or may even advance because downslope movement of glacier will continuously feed ice to lower altitude. Increased retreating rate of glaciers can be considered as an indicator of climate change. In the course of recent three decades, the occurred changes can be explained with exploitative land utilization which is among the primary drivers of changing snow cover, vegetation covers and profitability in western Himalayas locale. In a region where field-based research is tiring because of heterogenous and high elevation, measuring the changes in aforesaid using Remote Sensing techniques can give basic data regarding variating patterns of Snowfall and Precipitation. This paper studies the trend analysis of changing Snowfall and Precipitation patterns using SWAT and MODIS data (1979–2014 and 1999 to Present) over Uttarakhand Himalaya and its association with altitudinal gradient. This paper investigates the trends in maximum (Pmax), minimum (Pmin) & mean (Pmean) Snowfall and Precipitation in the annual, seasonal and monthly time-scales for 54 stations in the 5 regions of Uttarakhand’s Western Himalayan region which are categorized on the basis of elevation, from year 1979-2014. Statistical approaches are used to examine the effect of change in pattern of snowfall and precipitation upon the phenology of vegetation, fresh water ecosystems, agricultural productivity, decreasing snow line, increasing tree line & change in duration of the seasons etc of the study area.

The automation in man-made object extraction such as building habitation from urban area imagery has become a challenging task for photogrammetry, computer vision, and remote sensing. This study aims to automatically extract building of an urban area using high resolution intensity data and fuzzy membership logic to classify the image object by using e-Cognition software. The object oriented method was implemented and high resolution Quick-Bird imagery was used for automatic building extraction in Dehradun city of Uttarakhand district, India. We have further evaluated the performance of this automated extracted building feature by using accuracy completeness (89.74%), correctness (94.50%), and the quality (85.29%). The study however, clearly shows that the segmentation-based classification is much superior to the traditional per-pixel methods mainly used on high resolution images. It also shows that high spatial resolution satellite data and appropriate data processing play not only an important role in modern urban planning but also reduce the cost of manpower and saves time.