Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Розсіювання диму× | Ступінь вигорання (dNBR)× | |
|---|---|---|
| Галузь | Лісівництво | Лісівництво |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2000 | 2006 |
| Автор методу≠ | Dave Peterson | Carl Key |
| Тип≠ | atmospheric modeling | remote sensing index |
| Основоположне джерело≠ | Larson, T., Gould, T., Simpson, C., & Liu, L. J. S. (2004). Source apportionment of indoor, outdoor, and personal PM2.5 in Seattle, Washington using positive matrix factorization. Journal of the Air & Waste Management Association, 54(9), 1175–1187. link ↗ | Key, C. H., & Benson, N. C. (2006). Landscape Assessment (LA): Sampling and Analysis Methods. General Technical Report RMRS-GTR-164-CD, USDA Forest Service Rocky Mountain Research Station. link ↗ |
| Інші назви | air quality, smoke transport, visibility impacts | dNBR, Delta NBR, burn severity index |
| Пов'язані | 3 | 3 |
| Підсумок≠ | Smoke dispersion modeling predicts how smoke from wildfires and prescribed burns travels and disperses through the atmosphere, affecting air quality and visibility. Models use fire characteristics (size, intensity, fuel type), atmospheric conditions (wind, stability, mixing height), and topography to forecast smoke plumes and estimate particulate matter (PM2.5) concentrations downwind. Used for air quality forecasting, prescribed burn planning, and public health protection. | Burn severity is a quantitative measure of fire-induced changes in vegetation and soil, assessed using satellite-based spectral indices. The Normalized Burn Ratio (NBR) and its delta (dNBR) compare pre-fire and post-fire spectral reflectance in the near-infrared and shortwave-infrared bands to detect fire-caused vegetation damage and soil exposure. Developed by Key and Benson in 2006, dNBR has become the standard remote-sensing tool for rapid post-fire assessment and is used for emergency response, recovery planning, and ecological analysis. |
| ScholarGateНабір даних ↗ |
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