Spatiotemporal Variation of Burnt Area Detected from High-Resolution Sentinel-2 Observation During the Post-Monsoon Fire Seasons of 2022–2024 in Punjab, India
Abstract
Highlights
- High-resolution Sentinel-2 observation captures spatiotemporal variability of the fine-scale burnt areas in Punjab, which are often missed by coarser-resolution observation modes such as MODIS.
- PM2.5 emissions derived from Sentinel-2 observation are much higher than those reported by the EDGAR v.8.1 global inventory.
- More accurate burnt area (BA) detection and PM2.5 emission estimation provide considerable improvement over coarse-resolution inventories to support better air quality modeling and monitoring.
- The discrepancy in PM2.5 emission estimation underscores the need for observation-driven monitoring systems, rather than the conventional statistics, to support the fire mitigation strategy and to strengthen policy responses to seasonal biomass burning.
Abstract
1. Introduction
2. Materials and Methods
2.1. Area of Interest
2.2. Data
2.3. Identification of Burnt Areas
2.3.1. Sentinel-2 dNBR
2.3.2. MODIS Fire Hotspot
2.4. Estimated PM2.5 Emissions
3. Results
3.1. Burnt Area Detection from Sentinel-2
3.2. Ground Validation
3.3. Comparison with MODIS Burnt Area Products
3.4. Estimated PM2.5 Emissions from Sentinel-2Derived Burnt Areas
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
PM | Particulate Matter |
NDVI | Normalized Difference Vegetation Index |
NDWI | Normalized Difference Water Index |
NBR | Normalized Burn Ratio |
dNBR | Delta Normalized Burn Ratio |
MODIS | Moderate Resolution Imaging Spectrometer |
VIIRS | Visible Infrared Imaging Radiometer Suite |
FHS | Fire Hotspot |
BA | Burnt Area |
GEE | Google Earth Engine |
S2 SR | Sentinel-2 Surface Reflectance |
SCL | Scene Classification Layer |
EDGAR | Emissions Database for Global Atmospheric Research |
AD | Activity Data |
NIR | Near-Infrared |
SWIR | Short Wave Infrared |
EF | Emission Factor |
AOI | Area of Interest |
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Severity Level | dNBR Range (Scaled by 103) |
---|---|
Unburnt | Less than 100 |
Low severity | +100–+269 |
Moderate severity (low) | +270–+439 |
Moderate severity (high) | +440–+659 |
High severity | +660–+1300 |
Burning Efficiency | Emission Factor (g kg−1) | PM2.5 Emission (Thousand Tons) |
---|---|---|
0.5 | 0.0042 | 44.84 |
0.5 | 0.0091 | 97.14 |
0.5 | 0.0207 | 220.97 |
0.8 | 0.0042 | 71.74 |
0.8 | 0.0091 | 155.43 |
0.8 | 0.0207 | 353.56 |
0.9 | 0.0042 | 80.70 |
0.9 | 0.0091 | 174.86 |
0.9 | 0.0207 | 397.75 |
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Arbain, A.A.; Imasu, R. Spatiotemporal Variation of Burnt Area Detected from High-Resolution Sentinel-2 Observation During the Post-Monsoon Fire Seasons of 2022–2024 in Punjab, India. Sensors 2025, 25, 5588. https://doi.org/10.3390/s25175588
Arbain AA, Imasu R. Spatiotemporal Variation of Burnt Area Detected from High-Resolution Sentinel-2 Observation During the Post-Monsoon Fire Seasons of 2022–2024 in Punjab, India. Sensors. 2025; 25(17):5588. https://doi.org/10.3390/s25175588
Chicago/Turabian StyleArbain, Ardhi Adhary, and Ryoichi Imasu. 2025. "Spatiotemporal Variation of Burnt Area Detected from High-Resolution Sentinel-2 Observation During the Post-Monsoon Fire Seasons of 2022–2024 in Punjab, India" Sensors 25, no. 17: 5588. https://doi.org/10.3390/s25175588
APA StyleArbain, A. A., & Imasu, R. (2025). Spatiotemporal Variation of Burnt Area Detected from High-Resolution Sentinel-2 Observation During the Post-Monsoon Fire Seasons of 2022–2024 in Punjab, India. Sensors, 25(17), 5588. https://doi.org/10.3390/s25175588