NIR-SWIR-Temperature Version 1
NIR-SWIR-Temperature Version 1 for burn applications
Used in fire & burn mapping.
When to use
- Active fire detection and hotspot monitoring
- Fire weather and risk assessment in fire-prone regions
- Real-time situational awareness during fire events
- Smoke plume analysis and dispersion mapping
- Trigger for emergency response and evacuation planning
- Burn
Limitations
- Smoke obscures underlying surface during active fires
- Cloud cover frequently coincides with weather-driven fire events
- Thermal anomalies are short-lived — temporal resolution matters
- Confused with hot industrial sources, gas flares, and volcanic activity
- Quantitative burn severity requires pre-fire baseline imagery
What the values mean
General Formula
Sensor-Specific Formulas
Most-used sensors — click to show code below
| Sensor | Provider | Formula | Band Mapping |
|---|---|---|---|
| USGS/NASA | ((B5-B7)/(B5+B7))*T | N→B5, S2→B7 | |
| ESA | ((B8-B12)/(B8+B12))*T | N→B8, S2→B12 | |
| MAXAR | ((NIR1-SWIR6)/(NIR1+SWIR6))*T | N→NIR1, S2→SWIR6 |
Spectral Band Visualization — Landsat 8/9
Code Examples
Adapted for Landsat 8/9 bands —
Frequently Asked Questions
What is the NSTv1 (NIR-SWIR-Temperature Version 1) and when should I use it?
NIR-SWIR-Temperature Version 1 for burn applications Fire-related indices detect active combustion, map fire perimeters, and assess burn damage using thermal anomalies and changes in near-infrared and shortwave infrared reflectance caused by charring. NSTv1 is particularly suited for burn. The general formula is ((N-S2)/(N+S2))*T, which requires N and S2 spectral bands.
Which satellite sensors can I use to calculate NSTv1?
NSTv1 is supported by 3 satellite sensors in our database, including Landsat 8/9, Sentinel-2, WorldView 3. Each sensor uses different band designations — for example, Landsat 8/9 uses the formula ((B5-B7)/(B5+B7))*T, while Sentinel-2 uses ((B8-B12)/(B8+B12))*T. Select a sensor above to see its specific band mapping.
What spectral bands does NSTv1 require and why?
NSTv1 requires N (770-900 nm), S2 (2080-2350 nm). These wavelength regions target the specific spectral features that this index is designed to measure.
How do I calculate NSTv1 in Python or R?
Both Python and R code samples are provided above. In Python, use rasterio to load individual band GeoTIFF files and numpy for the arithmetic. In R, the terra package handles raster operations efficiently. The key is to load bands as floating-point arrays to avoid integer division, and to handle division-by-zero cases where the denominator equals zero. For production use, consider applying a valid data mask to exclude no-data pixels before calculation.
NSTv1 vs other fire indices
Related Fire Indices
References
Need help choosing?
Ask our AI assistant for sensor recommendations, code examples, or how NSTv1 compares to other indices for your specific use case.