Forest Fires in Uttarakhand, India? Remote Sensing reveals...
- Arpit Shah
- May 31, 2020
- 4 min read
Updated: Dec 4
Just earlier this week (May 2020), news portals and social media were abuzz with alarming reports of yet another tragedy in 2020—forest fires ravaging Uttarakhand, a northern Indian state nestled in the Himalayas and nearly 50% forested. As the story spiralled into hysteria, the state’s Forest Department was compelled to issue clarifications:
a) the fires were not as widespread or devastating as claimed, and
b) fire crews had them under control, aided by rain across the region.
The fallout from this misinformation was so severe that individuals responsible for circulating fake reports were charged with criminal offences.
Many may remember that Uttarakhand suffered serious forest fires in 2016. Both accidental and intentional causes were cited in that disaster. Forest fires are not surprising in such fragile ecosystems—warm temperatures, low moisture, and strong winds at high altitudes are natural triggers.
Using Remote Sensing, one can perform two key fire-related workflows:
For this study, I used Burned Area Mapping. My Area of Interest (AoI) includes a cross-section of the Kumaon division—one of the regions reportedly affected by fires—where I used two Sentinel-2 Multispectral Satellite datasets to identify the Burned areas and to classify it based on the Burn severity.
• Crisis image: 26 May 2020
• Archive image: 6 April 2020
Burned Area Mapping is possible through Multispectral Remote Sensing, a passive Imagery acquisition technique which utilizes solar radiation as its source of illumination, whose reflectance from surface features on earth is captured and classified by the receiver across multiple spectral bands of wavelength. This is because healthy and burned vegetation respond very differently to specific wavelengths:
Near Infrared (NIR):
– Healthy vegetation reflects ~40%
– Burned vegetation reflects <20%
Shortwave Infrared (SWIR):
– Burned vegetation reflects >40%
– Healthy vegetation reflects <20%
This contrast in spectral response allows analysts to detect which pixels turned from “healthy” (in April) to “burned” (in May).
Burned Area Mapping Output
The classification uses the USGS Burn Severity Index, where the bottom three categories—Moderate-Low, Moderate-High, and High—represent the most severe burn levels (orange, red, and purple pixels respectively).
Two clusters stand out:
West and central Udham Singh Nagar district (towards the south of the map), and
a portion of Almora district (just north of its label towards the north of the map).
That being said, Low-severity burned areas (yellow pixels) are visible across much of the southern portion of the map.
A Curious Anomaly: Why is Flat, Agrarian Udham Singh Nagar Showing Burned Areas?
Almora’s hilly, forested terrain makes it a natural candidate for fires. But Udham Singh Nagar is largely flat and agricultural—why would it exhibit so many burned pixels?
To investigate, I overlaid the burned-area output on Google Earth.
Slider 1: Burned areas in Udham Singh Nagar overlaid on Google Earth basemap
To my surprise, the burned pixels fell directly on farmlands.
To validate this, I contacted my friend Akhil Gupta, originally from Uttarakhand and involved in agribusiness. He confirmed that travellers in the region had indeed witnessed farmland fires. A delayed spring harvest (Baisakhi) may have compelled farmers to burn residual stubble to prepare the fields quickly for the monsoon (Kharif) crop.
This is reminiscent of the notorious stubble burning in Punjab and Haryana, which causes severe air pollution in Delhi annually.
Akhil also pointed out that timber smuggling (“Timber mafia”) significantly contributes to forest fires in the region.
Reflections
This study was particularly rewarding because the in-situ reports validated part of my analysis. One hopes Uttarakhand cracks down on timber smugglers and that farmers are educated on sustainable practices.
(Feb 2025 Update: I now offer patented solutions that help accelerate the shift to Natural Farming with higher yields at lower costs—reach out to know more)
I’m aware that Uttarakhand’s Forest Department already uses Satellite Imagery for fire detection and monitoring. Nevertheless, findings from this independent study reinforce that claims of widespread wildfires in the region were largely exaggerated or relate to fires that have already been controlled, aided by rainfall.
A much-needed respite amidst the horrors of 2020!
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