Nearest alert in the windowNoneno alert between the two passes
Detection confidence0.83score from 0 to 1
The pictures
Copernicus Sentinel-2, rendered by the API
Before: Sentinel-2C, Fri 30 Oct 11:10 ISTAfter: Sentinel-2C, Mon 2 Nov 11:20 IST
True colour
True colour
Short-wave infrared
Short-wave infrared
The scar as mappedCloud in the tile: before 34%, after 0%
Why the rule calls it a burn
Rule s2burn-rules-2
Pixels in the scar
21
Near-infrared darkened (dB8A)
0.189
Short-wave infrared 1 darkened (dB11)
0.233
Short-wave infrared 2 darkened (dB12)
0.148
Burned-area index after (BAIS2)
0.89
Brightness after
0.30
Greenness before, after (NDVI)
0.18, 0.11
Burn ratio change (dNBR), NBR after
0.11, −0.10
The detection rule
Sentinel-2 L2A, cropland only: NIR and SWIR darkened since the previous clear pass (dB8A>0.07, dB11>0.07, dB12>0.03) and the field now looks charred (BAIS2>=0.78, brightness<=0.34); passes at most 6 days apart; clusters of at least 0.52 ha whose mean post-burn NBR is below 0.0 (drops flooded fields and cloud shadows). Candidates: tillage can look similar.
Where and when
Nearest village
Daryapur, 0.8 km
Subdistrict
Nawanshahr
District
Shahid Bhagat Singh Nagar, Punjab
Centre
31.0233° N, 76.0751° E
Clear pass before
Sentinel-2C, Fri 30 Oct, 11:10 IST
Pass that shows it
Sentinel-2C, Mon 2 Nov, 11:20 IST
Sentinel-2 tile
43RFQ
Checked against alerts
Daily; unchanged since 13 Nov, 12:20 IST
Fire alerts near the scar
NASA FIRMS
The API found no FIRMS fire detection near this scar.
Weather between the passes
No weather for this window: no stored weather grid covers this burn window
Survey of India states + LGD/Bharatmaps districts (DataMeet / ramSeraph mirror)fetched 9 Nov, 08:47 IST · fetch 44144
When a burn counts as unseen
unseen = no FIRMS detection within max(1 km, pixel half-diagonal + 200 m) of the scar between the clear pass before it and 3 h after the pass that shows it
Known look-alikes: cloud and smoke-plume shadows in partly cloudy passes and flooded fields with mean post NBR just below 0 still pass, often with high confidence; tillage of wet soil can mimic char; a hazy pre pass can exaggerate the darkening.
Sentinel-2 scenesS2C_T43RFQ_20261030T053555_L2A and S2C_T43RFQ_20261102T053957_L2A
Candidate unseen burns as a whole: audit precision 87% (95% CI 68%–96%, n = 23), checked by eye.
How often this rule is right: when people checked a random sample of candidate unseen burns by eye, the audit precision was 87% (95% CI 68%–96%, n = 23).
