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  • Writer's pictureArpit Shah

Mapping Snow Cover in Himachal Pradesh

Updated: Feb 3, 2022

The Cryosphere constitutes everything on the earth's surface that is frozen be it glaciers, sea ice, polar caps or snow. While invariably nothing grows on the cryosphere because of inhospitable temperatures, these regions are of vital importance as they help maintain the earth's climate by reflecting away solar radiation. Reduction in ice composition in the polar regions is often treated as a leading indicator of widespread global warming. Mapping the cryosphere and monitoring its changes is therefore, a routine activity undertaken by scientists working in the earth observation sector.

The topic of study for this article is the extent of snow cover in Himachal Pradesh. Just last month, the findings of the government study conducted by The Centre on Climate Change of the Himachal Pradesh Council for Science Technology and Environment (HIMCOSTE) and the Space Applications Centre, Ahmedabad were published in the news, the headline being - Snow cover in Himachal Pradesh reduced by 18% between October 2020 and May 2021.

The scientists had analysed satellite imagery captured using AWIFS (Advanced Wide Field Sensor) - a collaborative effort between ISRO and USGS (United States Geological Survey). For my study, I have used the imagery captured by OLCI sensor (Ocean and Land Color Instrument) onboard European Space Agency's Sentinel-3 satellite to conduct the analysis.

(Much thanks to RUS Copernicus for the training provided to perform this analysis)


Monitoring snow cover is crucial because melting snow is the primary source of water to some of the major rivers of India. Himachal Pradesh's snow cover, in particular, is the source of water for Beas, Chenab, Ravi and Sutlej and Yamuna river basins. A reduction in snowfall would result in lesser snow cover which would eventually lead to lesser melting and limited water flow into these life-sustaining rivers.

I have analysed two sets of satellite imagery - a) 4 images from 2021 and b) 4 images from 2018-2021. For the former, I have started from a winter month (February) and ended in a summer month (June). The idea was to observe the extent of snow melt. For the latter, I have taken one summer month (May or June) from each of the four years. Here, the purpose was to see how the extent of snow cover changes year-on-year.

2021 Monthly Time Series (4 Images)

2018 - 2021 Annual Time Series (4 Images)


For starters, this is how optical satellite imagery from OLCI sensor looks like in RGB view-

Satellite Imagery captured from Sentinel-3A's OLCI sensor on 21 Feb 2021. Himachal Pradesh is towards the bottom mid-to-right.

The methodology which we have used to derive extent of snow cover from satellite imagery is called Normalized Difference Snow Index (NDSI). Clouds can be easily differentiated from Snow if a satellite captures in Short Wave Infrared (SWIR) mode. However, since OLCI doesn't have a SWIR sensor onboard, Kokhanovsky et. al (2019) have adapted the NDSI computation for OLCI images.

After doing image processing using this methodology, the final output is as below-

Snow cover in Himachal Pradesh on 21st Feb 2021.

Below are the final snow cover outputs in Himachal Pradesh stacked side by side for both the sets of imagery.

Snow Cover in HP - Feb, Mar, Apr and Jun respectively in 2021

Just based on visual inspection of the images above, we can clearly see that there has been a marked reduction of snow cover in June 2021 when compared to the previous months. Himachal Pradesh appears to have had non-seasonal snowfall in April 2021. Non-seasonal snowfall is less dense and is prone to quicker melting.

Snow Cover in HP - 2018, 2019, 2020 & 2021 respectively

Just based on visual inspection of the images above, we can see that the extent of snow cover in early June 2021 is much less than that observed in May of the preceding two years, at least. 2018 appears to have less snow cover - which is backed by the findings of the same Indian science body in this news article.


In the maps below, we have combined the output of each of the four images in an individual set so as to visualize the complete story in a single map.

2021 Monthly map based visualization below -


Map based visualization of Year-on-Year Snow cover comparison below -


Post visual inspection, let's compute the snow coverage in terms of land area -

Snow Coverage for the 2021 months denoted in 'Mask Area' section

A 36% decrease in snow cover is observed between February 2021 and June 2021. To interpret this isn't straightforward. February being a winter month and May being a summer month, it is normal for a portion of the snow cover to melt away. The ideal melt-away % is unfortunately not available with me. However, if you recollect the finding of the government study I had referred to initially - an 18% decrease between October 2020 and May 2021 was attributed to climate change so I presume the ideal melt-away percentage is well below 18%.

My lack of information on ideal melt-away percentage is the reason why I chose to compare summer snow coverage year-on-year as well as that would complement my month-on-month findings and validate whether actually climate change is reducing snow coverage.

(That being said, I would definitely like to understand from the scientists, should the opportunity arise, as to why they chose October 2020 as the base month to compare May 2021 to. Autumn vs Summer doesn't seem a natural comparable to me. While I would still give the scientists the benefit of doubt as they are an authority on this matter, nonetheless we are better served if absorb news on research findings with a pinch of salt as they only highlight the outcome and not the methodology and rationale behind the methodology.)

Snow Coverage from 2018 to 2021 denoted in 'Mask Area' section

For the results above from the second set of imagery, a 42% decrease has been observed when we compare 2021's snow coverage in summer to that of 2019 and a 34% decrease has been observed when we compare 2021's snow coverage in summer to that of 2020. This finding does tend to validate the severe effect of climate change and, in a way, complements our month on month results earlier.

2018 May output

That being said, a 25% increase was also observed when we compared summer of 2021 to summer of 2018. This could be because of two reasons -

a) a small section of the Himachal Pradesh imagery is non-existent - on the right and on bottom of the satellite image cloaked in violet. This is because the 2018 image which I had selected did not capture the area of interest completely. In all likelihood, 2018 snow cover would increase by single digit percentage if we were to consider the snow cover across the entire state.

b) May 2018 could very well be a very warm month and an exception as in all the remaining 7 images, the snow coverage is well-above 10,000 sq. km.


Climate change is damaging the cryosphere around the world. In the Sierra Nevada mountain range in USA, May 2021 snow cover was 90% less than that of February 2021!

Refer to the map based visualization below -

I hope you found this study to be a grim reminder of the fragile state of our planet.

Satellite imagery analytics helps us to keep a constant check on such developments and enables us to take both proactive and reactive measures in order to mitigate nature's fury. Explore more such articles on similar topics here.


Intelloc Mapping Services | Mapmyops is engaged in selling products which capture geodata (Drones & Drone Services), process geodata (Geographic Information System) and enhance geodata (Imagery & Location Analytics). Together, these help organizations to benefit from Geo-Intelligence for purposes such as operations improvement and project management.

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