Land Use/Land Cover (LULC) changes have a significant impact on Land Surface Temperature (LST). The LST is an important parameter in various environmental and climatological studies, as it plays a crucial role in understanding the Earth’s surface–atmosphere interactions. The LULC changes can modify the surface energy balance and alter the radiation budget, leading to changes in LST. Urbanization, deforestation, and agricultural land use changes are some of the primary drivers of LULC change that have a significant impact on LST. Deforestation and agricultural land use changes result in a reduction in evapotranspiration, leading to an increase in LST. The main objective of the study is to analyze the spatio-temporal change in Land Use/Land Cover (LULC) and its effect on Land Surface Temperature (LST), as well as to establish a correlation of LST with the Normalized Difference Vegetation Index (NDVI) and Normalize Difference Snow Index (NDSI). Understanding the impact of LULC on LST is essential for developing effective land use policies that can mitigate the adverse effects of LULC change on the environment and human health.

Lahaul-Spiti district is a cold desert mountain, situated in the Trans-Himalayan region. The district has the lowest population density of 2 persons/km² because of the harsh climate and rough topography that act as barriers to population growth. Specific knowledge of climate variability in the region is limited. Hence, it is essential to study the trends of temperature and precipitation for the region and also its effects on sustainable development. The objective of this study is to investigate the variability of rainfall and temperature on a monthly, seasonal, and annual basis from 1981 to 2021. Precipitation and temperature data on a monthly, seasonal, and annual basis were acquired from the National Aeronautics and Space Administration (NASA) Langley Research Center’s POWER Project. The trends of precipitation and temperature were derived using the Mann–Kendall trend test and the slope of the regression line using Sen’s slope test. Subsequently, the maximum, minimum, mean, standard deviation (SD), and coefficient of variation (CV) of precipitation and temperature were computed to analyze the range of variation in them. The results showed a significant increasing trend in the monthly temperature of October (p-value 0.011) and December (p-value 0.05), which is below the alpha value 0.05. Similarly, an increasing trend in annual (p-value 0.000), seasonal (winter p-value 0.008 and summer p-value 0.003), and monthly (January p-value 0.030, April p-value 0.032, June p-value 0.004, July p-value 0.027, and August p-value 0.002) precipitation was observed as computed p-values are less than the significance level of alpha = 0.05. This glaciated region is most vulnerable to climate change because it is already a scarce region in the context of natural resources. Changes in the pattern of precipitation and temperature affect the socioeconomic structure of the region, affecting sectors such as agriculture, livestock, forestry, tourism, and human health. According to the perceptions of people, the temperature rise has accelerated the melting of glaciers and reduced the snow cover area. The increase in rainfall can lead to a higher incidence of mudflows, landslides, floods, and other related events, as the region is made up of sedimentary rocks. Thus, it is crucial to continuously monitor the trends in temperature and precipitation.

Snow Cover and Snowline Variation in Relation to Land Surface Temperature in Spiti Valley, Himachal Pradesh, India