Permafrost region is highly vulnerable to climate change and is easily degraded by thermal and mechanicalforces. Its extent and distribution in the Indian Himalaya region are not explored much and their mapping inHimalayan region is not carried out a lot. While around 9% of land area of Kullu district is categorized aspermafrost areas. Given the socioeconomic consequences of permafrost degradation, detecting, mapping, andmonitoring permafrost distribution in Himachal Pradesh are critical.This article provides a permafrost map for Himachal region based on continuous time-series analysis of LandSurface Temperature (LST) data using Google Earth Engine (GEE) platform. The LST from Landsat 8 (L8) andModerate Resolution Imaging Spectroradiometer (MODIS) data were calculated using the GEE platform. Oncewhole scene falling at path 147 row 037,038,039 was taken for analysis covering 5500 x 3500pixels at 30mspatial resolution for L8. and path row covering 396 x 217 pixels at1 km resolution for MODIS data. LST wasprepared from 2013 to 2021 on each pass of the satellite. Thus nearly 495 data scenes were analyzed for L8and 2913 data scenes for MODIS. The effect of presence of cloud shows sudden variations in derived LSTswhich was overcome by removing clouds using cloud masking. The Indian Meteorological Department (IMD)observed temperature data during same time was compared with the derived LST values for few Himalayanstations. While under clear sky conditions, the mean LSTs are signicantly correlated with the groundobservation temperature data. The season wise variation of derived LST correlates more with the observedvalues. The Permafrost terrains were located and mapped in regions where the temperature is consistentlylower than -1C. Land degradation in such areas is being presented with the help of long term and short termtemporal analysis.

Permafrost; Google Earth Engine (GEE); Landsat 8; MODIS; Land Surface Temperature (LST);Temporal analysis